University Of Wisconsin-Madison

NIH Research Projects · FY 2026 · 2022-06

ABSTRACT: Over 14,000 Glioblastoma (GBM) patients annually in the US undergo a combination of cranial surgery, chemotherapy, and radiation as standard treatment for their aggressive cancer. Unfortunately, ~40% of these patients will be identified with a suspicious lesion on a post-chemo-radiation follow up MRI scan (T1w, T2w, FLAIR). A significant challenge in the management of GBM tumors is the differentiation of these lesions as tumor recurrence or benign treatment-related radiation effects (TRRE). These conditions mimic each other, clinically and radiographically. Unfortunately, in the absence of reliable diagnostic tools, patients with TRRE will undergo an unnecessary and avoidable invasive stereotactic brain biopsy (St-Bx) for confirmation of disease absence. However, even the invasive St-Bx has an accuracy of 85-90% due to sampling errors associated with obtaining a biopsy tissue which may not be representative of the underlying disease pathology. Consequently, building non-invasive decision support tools which yield a diagnostic accuracy that is non-inferior to St-Bx, represents an attractive solution for obviating unnecessary intra-cranial St-Bx in patients with benign radiation effects. Our group has developed a new Image-based Recurrence Risk Classifier (IRRisC) using routine MRI scans, that has demonstrated an accuracy of 85% in distinguishing tumor recurrence from TRRE, on n=58 studies. Our initial set of IRRisC features comprise disorder in gradient orientations on Gadolinium (Gd)-T1w MRI which have been shown to be significantly higher in tumor recurrence compared to TRRE. Interestingly, we have recently also demonstrated that construction of separate classifiers for males and females yielded significantly improved prognosis of GBM survival compared to an ‘all-comers’ model. In this R01 project, we seek to further improve and validate the accuracy of IRRisC by expanding our initial feature set (using Gd-T1w MRI) to include (1) additional features from anatomical (T2w, FLAIR) and functional MR sequences (perfusion), (2) a new class of biophysical deformation attributes from “normal” brain parenchyma, and (3) construction of sex-specific models to exploit sexual-dimorphism in GBM, for distinguishing tumor recurrence from TRRE. Overcoming limitations of previous work pertaining to small samples and lack of histopathological validation, our work will utilize the largest multi-institutional histopathologically confirmed cohort till date of n=470 studies of TRRE and tumor recurrence, to harmonize and validate IRRisC. Further we will establish the biological underpinning of our IRRisC features by evaluating their association with histopathological hallmarks of TRRE and tumor recurrence. Finally, IRRisC will be validated as decision support in a machine-reader study at 3 clinical sites. Criteria for success for IRRisC is that it will (a) be non-inferior to the accuracy of St-Bx (~85-90%), and (b) identify no more than 50% of patients with TRRE as having cancer. These criteria will ensure that IRRisC is clinically actionable as a robust and reliable classifier, by obviating at least 50% of unnecessary intra-cranial biopsies in patients with TRRE, while also maintaining a high true positive rate for cancer recurrence.

NIH Research Projects · FY 2025 · 2022-06

ABSTRACT As we age, the intrinsic ability of stem cells to self-renew and differentiate to maintain tissue integrity dramatically declines. Therefore, understanding the processes leading to stem cell dysfunction with age is essential for the future development of novel, effective stem cell-based therapies to treat disorders associated with aging. Therefore, my long-term goal is to elucidate the epigenetic mechanisms of stem cell aging, manipulate them to rejuvenate aged tissue, and promote healthy aging. More specifically, the insight provided by this proposal would be used to devise strategies to rejuvenate muscle and hematopoietic stem cell function, and therefore promote skeletal muscle recovery and reduce age-associated systemic low- grade chronic inflammation. To accomplish this objective, we will utilize mouse genetic models, models of skeletal muscle degenerative injury and moderate exercise (voluntary wheel running; VWR), cell culture systems, imaging analysis, small molecule inhibitors, flow cytometry analysis, physiological measures of recovery, genomics, and epigenomics (Cleavage Under Targets and Tagmentation; CUT&Tag). In aged mice, both muscle stem cell (MuSC) and hematopoietic stem and progenitor cell (HSPC) quiescence is disrupted, leading to reduced regenerative capacity. Recent studies used VWR to restore quiescence and rejuvenate both MuSC and HSPC function in aged mice. The epigenetic landscape in both stem cell populations changes dramatically, yet the mechanisms underlying these events as well as their contribution to age-associated dysfunction remain understudied. The lysine methyltransferase 5a (Kmt5a) is the sole enzyme catalyzing monomethylation of lysine 20 on histone H4 (H4K20me1), which is required for subsequent di- and tri-methylation by Kmt5b and Kmt5c, respectively. Methylation of H4K20 is critical for chromatin organization and regulation of transcription, yet its role in adult stem cells is entirely unknown, especially in the context of aging. Our preliminary data show that Kmt5a and H4K20me1 decrease in aged MuSCs. Specific deletion of Kmt5a in MuSCs recapitulates aging phenotype by decreasing the pool of stem cells, suggesting disruption of quiescence and impaired self-preservation of the pool. Using the recently developed epigenomic technique CUT&Tag, we assessed H4K20me1 in adult and aged quiescent MuSCs and found that H4K20me1 is mostly located at the genes’ transcriptional start site and significantly decreases with age. Further analysis revealed that age-associated loss of H4K20me1 silenced numerous Notch genes including Rbpj, critical to maintaining MuSC quiescence. Significantly, Kmt5a inhibition and subsequent loss of H4K20me1 in MuSCs led to decreased RNA Polymerase II serine 2 phosphorylation, suggesting the impaired release of promoter-proximal pausing and therefore potent gene silencing. Thus, we propose to examine if the loss of Kmt5a, and consequently H4K20me1, in aging MuSCs contributes to the disruption of their quiescence state. Also, we will determine the role of Kmt5a in regulating RNA Polymerase II promoter-proximal pausing, and how this proposed mechanism contributes to controlling MuSC fate and function. Last, we will determine if moderate exercise using a VWR model can rejuvenate MuSC and HSPC epigenome through the restoration of H4K20 methylation. The specific aims of this proposal are: 1) Determine the role of Kmt5a in MuSC quiescence regulation during aging and 2) Determine the impact of VWR on Kmt5a-mediated epigenetic remodeling in aged MuSC and aged HSPC.

NIH Research Projects · FY 2026 · 2022-06

ABSTRACT Down syndrome (DS), a genetic disorder, is associated with accelerated aging and high levels of swallowing impairments (dysphagia). This is a critical concern given the increased survival of people with DS to older ages, and the association of dysphagia, aspiration pneumonia, and death. Although dysphagia is a prominent feature of DS, little is known about its age-related progression or the genetic mechanisms that underly its etiology. There are significant knowledge gaps in DS research regarding how the extra copy of the human 21st chromosome known to be present is driving DS phenotypes. The proposed research will address these gaps through a collaboration between two laboratories with substantial expertise in translational animal models of aging, DS, and dysphagia (Connor/Glass) and in the engineering of novel DS mouse models (Yu). The overarching goals of the proposed work are to quantify effects of aging on DS-related dysphagia and to resolve a current major uncertainty concerning the mechanisms underlying phenotypes in DS. There are two proposed aims: (Aim 1) To test the hypothesis that dysphagia is exacerbated by aging in mouse models of DS by quantifying swallowing function, tongue muscle alterations, changes in brainstem regions in mice of different ages, and by performing additional analyses at the molecular and phenotypic levels; and (Aim 2) To quantify the impacts of various components of a trisomy on swallowing function in DS in crucial behavioral and biological variables. We will pursue the objective of Aim 2 by generating and analyzing a number of the novel tailor-designed mouse models. This work is significant because it will define age-related changes in swallow function in mouse models of DS using an ecologically valid assay (videofluoroscopy) that is also used clinically in humans. Further, this work will introduce clarity regarding the impact of the critical elements of a trisomy on DS-related dysphagia by using new mouse models thereby allowing us to unravel molecular contributors to dysphagia in this context and to optimize translational precision. There are currently only limited compensatory treatments for DS-associated dysphagia, and thus there is an urgent need to enhance our mechanistic understanding of this clinical manifestation to support rational development of future therapeutic interventions. This proposal is in response to NOT-OD-20-025, for the NIH INCLUDE Project on Down syndrome research.

NIH Research Projects · FY 2026 · 2022-06

PROJECT SUMMARY One of the most deployed molecular targeting agents in the treatment of head and neck cancer (HNC) is the Epidermal Growth Factor Receptor (EGFR)-targeted monoclonal antibody cetuximab (CTX). Cetuximab is a central component of the first-line EXTREME regimen and in combination with radiation therapy and is the only drug that exhibits efficacy in both locally advanced and recurrent/metastatic HNC. Although many HNC patients see CTX over the course of their cancer therapy, research over the past decade has revealed that many patients that do respond initially will eventually become refractory to CTX. To identify drivers of CTX resistance (CTXR) in HNC, our lab utilized HNC human tumor specimens, patient-derived xenografts (PDXs) and a series of acquired and intrinsically resistant in vitro and in vivo model systems. This work led to the identification of the receptor tyrosine kinase (RTK) AXL as a central driver of CTXR. To define the molecular mechanisms of how AXL signaling leads to CTXR, three tyrosine residues of AXL (Y779, Y821, Y866) were mutated and mapped for their sensitivity to CTX. Both in vitro and in vivo analysis revealed that 1) CTXR emanates from signaling from Y821 of AXL via the c-Abl kinase, 2) pre-clinical modeling (PDX) indicated that the combination of CTX plus imatinib (IMT), a c-Abl kinase inhibitor, lead to complete tumor regression without recurrence in HNC models and 3) preliminary data for this application suggests that AXL, via Y821, sequesters c-Abl in the cytosol and prevents it from moving to the nucleus, which is induced by IMT, to promote apoptosis. Collectively, we hypothesize that AXL plays a critical role in CTXR by sequestering c-Abl in the cytosol and that therapeutic targeting c-Abl in combination with CTX will lead to profound responses in HNC patients. We plan to conduct this interdisciplinary project, spanning from basic biology to a pilot clinical trial through the three following aims: 1) To investigate if a) cytoplasmic sequestration of c-Abl is responsible for AXL mediated CTXR and if b) if AXL and c-Abl association is a predictive biomarker of CTX response, 2) determine if targeting EGFR and c-Abl simultaneously in CTXR PDXs can enhance and re- sensitize to CTX, and 3) To perform a pilot window-of-opportunity study of CTX plus imatinib in patients with recurrent or metastatic HNC. Ultimately, our goal is to improve treatment outcomes for HNC patients. Successful pursuit of these investigations has the potential to significantly improve and refine current HER family-centric therapeutic approaches in HNC by understanding the molecular mechanisms of how Axl and c-Abl impart CTXR. In addition, this project has high significance by repurposing two FDA approved drugs in a new cancer setting to improve outcomes. Collectively, this work will impact future clinical treatment paradigms and identify patients most likely to benefit from targeting EGFR and c-Abl in HNC.

NIH Research Projects · FY 2025 · 2022-06

Elevated levels of TGFβ2 levels in the trabecular meshwork (TM) are thought to the major cause for the increased deposition of extracellular matrix (ECM) that restricts aqueous humor outflow (AHO) and causes an elevation in intraocular pressure (IOP) in primary open angle glaucoma (POAG). Yet the pathway(s) that increase TGFβ2 expression in POAG patients is unclear. We hypothesize that the coordinated activation of the transcription factor, NFATc1 and a αvβ3 integrin signaling pathway forms a positive feedback loop that drives the elevated levels of TGFβ2 in POAG. In support of this hypothesis, our studies have shown that activation of αvβ3 integrin signaling triggers an increase in TGFβ2 expression in human trabecular meshwork (HTM) cells and that αvβ3 integrin expression is controlled by the transcriptional activity of NFATc1. Understanding how NFATc1 and αvβ3 integrin activity work together to control TGFβ2 levels is important as it could demonstrate novel ways (using combinational therapies) to control POAG. Aim#1 will test the hypothesis that activation of NFATc1 is involved in regulating the expression of TGFβ2 and ECM proteins in HTM cells and in C57BL/6J mice. Adenoviral (Ad5) vectors expressing a constitutively active (CA)-NFATc1 will be used to activate NFATc1 in HTM cells and in C57BL/6J mice. Lenti-NFATc1 shRNAs and a NFATc1flox/flox mouse transduced with Ad5-cre vector will be used to silence NFATc1 expression in vitro and in vivo, respectively. Dexamethasone or the Ca2+ ionophore ionomycin, known activators of NFATc1, will be used to confirm NFATc1 activity and its role in regulating TGFβ2 and ECM expression in HTM cells and in mice. Changes in TGFβ2 and ECM expression will be measured using immunofluorescence microscopy, western blots, and PCR. IOP and AHO will be measured using a tonometer, and anterior chamber cannulation, respectively. Aim#2 will test the hypothesis that αvβ3 integrin activity drives TGFβ2 and ECM expression by generating a Ca2+-dependent feedback loop coordinated by NFATc1. Ad5 vectors expressing a CA-αvβ3 integrin or inactive (D119Y) αvβ3 integrin will be used to alter the expression/activity of αvβ3 integrin in HTM cells and in C57BL/6J mice in vivo. A NFAT-luciferase reporter mouse transduced with Ad5-αvβ3 integrin or an Ad5-bioactive TGFβ2 transgene will be used to detect the effect of αvβ3 integrin and TGFβ2 on NFATc1 activity in vivo. The Ca2+-chelator (BAPTA-AM) will be used to inhibit Ca2+ signaling. Changes in TGFβ2 and ECM expression will be measured as described in aim#1. Aim#3 will test the hypothesis that mechanical forces associated with an elevated IOP perpetuate the elevation in Ca2+ that increases NFATc1 and αvβ3 integrin activity in the TM. Ex vivo monkey and human anterior segments will be subjected to elevated pressure. The Ca2+ ionophore ionomycin will be used to activate NFATc1 while a Ca2+ chelator (BAPTA-AM) will be used to block it. A Ca2+ indicator, Fura2-AM will be used to measure Ca2+ levels. Changes in TGFβ2, αvβ3 integrin and ECM expression will be measured as described in aim#1

NIH Research Projects · FY 2024 · 2022-06

PROJECT SUMMARY/ABSTRACT Adult mammals possess a limited ability to regenerate cardiac tissue after an injury, such as a myocardial infarction. Following a myocardial infarction, up to a billion or more heart muscle cells die and are replaced by scar tissue that contributes to heart failure and sudden death. In contrast, adult zebrafish remarkably regenerate injured hearts with no residual scarring. Although zebrafish and mammals share homologs of genes vital for heart regeneration, their transcriptional responses to cardiac injury are distinct. However, the mechanisms governing gene expression during heart regeneration remain poorly understood. My research aims to elucidate how injury-responsive gene expression is regulated to facilitate heart regeneration. My lab identified the cardiac leptin b-linked regeneration enhancer (cLEN), which activates gene expression upon cardiac injury. Using in vivo transgenic assays, I found that multiple activation elements are required for injury-dependent cardiac enhancer activity. Surprisingly, I also found that cLEN contains a repressive element that is required for preventing enhancer activation in uninjured hearts, providing the first example of an inhibitory element within a cardiac regeneration enhancer. Based on these data, I hypothesize that cardiac regeneration enhancers are dually governed by activation and repression to direct injury-restricted expression for heart regeneration. In Aim 1, I will utilize pharmacological and genetic approaches to test the model that injury-induced MEK–ERK– AP-1 pathway signaling activates cardiac regeneration enhancers. I will also utilize ATAC-seq, ChIP-seq, and RNA-seq using FACS-sorted endocardial cells from uninjured and regenerating hearts to test whether AP-1 regulates chromatin accessibility, deposition of active histone marks, and injury-induced paracrine factor expression. In Aim 2, I will use transgenic assays to determine whether cLEN-like enhancer candidates I identified in the zebrafish, mouse, and human genomes drive regeneration-induced expression. The functionality of candidate repressive elements will be determined via mutational analyses. I will also utilize in vivo loss-of- function assays to determine whether prdm1a, a transcriptional repressor that is predicted to bind to the repressive element in cLEN, mediates heart regeneration and repression of regeneration enhancers in uninjured hearts. These studies will utilize genetic tools and the endogenous regenerative ability of the zebrafish heart to improve our understanding of transcriptional mechanisms underlying heart regeneration, build gene regulatory networks, and identify potential targets for improving heart repair.

NIH Research Projects · FY 2026 · 2022-06

Uncovering Life Course Constellations of Exposures through Big Data on Place, Time, and Family Factors Project Abstract This project will trace the mortality of birth cohorts of the early 20th century in the US by place, time, and family factors. Combining “big data” with a large array of contextual exposures, we substantially deepen our understanding of the complexities of how childhood exposures to disease, economic change, and natural disasters shape old age mortality profiles of cohorts born ~1910-1930. We fuse together hypothesis driven tests, data driven discoveries, and omnibus measures from variance decompositions. Our proposal combines the massive CenSoc data, which contains >15 million death records between 1975-2005 to test specific hypotheses as well as generate new hypotheses around the main, interactive, and cumulative effects of exposures during sensitive periods of development that may shape mortality experiences of these cohorts. Our interdisciplinary group of sociologists, demographers, economists, epidemiologists and others combines our expertise with the CenSoc data as well as with testing hypotheses from the Developmental Origins of Adult Health and Disease theories to pursue an interconnected set of specific aims to push forward the frontier of understanding the complex links between early life exposures and later life mortality. Aim 1 begins with a set of variance decompositions stratified by time and place across the early 20th century in order to construct an “Atlas” of estimates of the importance of family background (sibling correlations) as well as shared environmental factors (childhood neighbor correlations) determining old age mortality experiences at the close of the 20th century. We then ask whether these estimates are shaped by major disease events and the extent to which the patterns are explained through socioeconomic status markers in mid life. Aim 2 pivots from the forest to the trees by leveraging “natural experiment” research designs to estimate causal main and interactive effects of specific early life exposures and how these effects vary by sex, geography, and family background. We then make use of machine learning tools to synthesize estimates that may vary by age of exposure, sequence of exposures, and domain of exposures during early life. These models explore impacts of cumulative exposures, dynamic complementarity of exposures and potential for reversibility of early insults using well powered analysis not available elsewhere. Aim 3 concludes our analysis by pushing the frontier of intergenerational analysis by using data in previous aims to link back to parental information on exposures and ask whether parental exposures affect the next generation’s old age mortality as well as whether the effects of exposures interact across generations.

NIH Research Projects · FY 2025 · 2022-06

Project Summary/Abstract This project addresses fundamental controversies regarding the extent to which benefits of cognitive training may reflect, at least in part, placebo effects. Cognitive training is increasingly studied and applied as a potential approach to enhance cognitive capabilities in healthy young-to-middle-age adults as well to ameliorate and/or prevent age-related cognitive decline in individuals that may be at risk for developing ADRD. While extant data suggest that well-designed cognitive training paradigms can produce positive real-world change in cognitive functions, some researchers have suggested that the positive effects attributed to cognitive training may, in fact, reflect placebo effects. This criticism stems from the fact that, in even the best designed cognitive training studies, participants cannot be truly blinded to condition. While many cognitive training studies attempt to blind participants to the intent or purpose of the training (e.g., using an inert control training that participants might find plausible as an active intervention), because such control training experiences necessarily differ in key ways from the active training experiences, it has nevertheless been suggested that participants in cognitive training studies are able to intuit their condition and associated expectations and then show outcomes that are rooted purely in these expectations. Despite this suggestion appearing frequently in commentaries over the past several years, there exists little empirical work that directly addresses whether placebo effects may be at play in cognitive training and whether such effects can be of a magnitude that explains previous results in the field. Here we propose to overcome this fundamental gap in the field with a large-scale research study designed to explicitly examine placebo effects in cognitive training. In particular, taking lessons from outside domains that have more rigorously examined the induction of placebo effects, we utilize both “pure expectation” methods (i.e., verbally telling participants that an inert training protocol will enhance their cognitive functions) and “associative learning” methods (i.e., pairing training with subjectively experienced improved performance) in the attempt to purposefully drive maximal amplitude placebo effects. This will not only serve to resolve the proximal controversy regarding whether placebo effects in the domain, but if such effects are found, it will serve as a benchmark for future research (e.g., to potentially harness such effects). We will examine how the size of such effects may differ across age groups (younger and older adults), across cognitive domains (e.g., fluid intelligence, working memory, selective attention), and across testing contexts (in-lab versus remote). Finally, as outside domains have shown that there can be individual differences in the extent of placebo-responsiveness, we will also examine a set of individual difference variables (e.g., personality) as possible moderators for these differences. This research will provide a unique and foundational dataset that addresses directly and in a rigorous manner the extent to which cognitive training effects can be explained by, and/or augmented by, placebos, and inform future interventions addressing ADRD.

NIH Research Projects · FY 2026 · 2022-05

PROJECT SUMMARY/ABSTRACT Brain tuberculosis (TB), the most severe form of tuberculosis, is associated with a complex inflammatory response, tissue damage and cerebral edema. Typically, management of fluid, waste, and immune- surveillance in the periphery is performed by tissue infiltrating lymphoid vessels. While the brain parenchyma does not have lymphoid vessels, recent research has identified that brain fluids (cerebrospinal fluid and interstitial fluid) are collected by meningeal and cribriform lymphoid vessels surrounding the brain, which are crucial for waste clearance and tissue homeostasis in the CNS. It has been shown that inhibition of lymphatic transport accelerates disease pathology and cognitive decline in Alzheimer’s disease, traumatic brain injury, and Parkinson’s disease, but little is known about the potential modulatory role of lymphoid vessels in CNS tuberculosis. Recently we reported that autoimmune inflammation induces lymphangiogenesis at the cribriform plate through the production of VEGFC from inflammatory dendritic cells. Functionally, the induction of new lymphoid vessels upregulates immunoregulatory molecules, and blocking new lymphoid vessel formation has consequences in regulating the severity of the autoimmune disease. In this proposal, we will test how CNS tuberculosis affects meningeal and cribriform lymphoid vessels formation and consequently, their fluid and cell draining function (Aim 1) To understand the impacts on immune-surveillance, we will study how CNS mycobacterial tuberculosis (Mtb) infection alters the expression of immune regulatory molecules on draining lymphoid vessels and how these lymphoid vessels modify brain-derived dendritic cells and their ability to influence downstream T cell priming in the lymph node (Aim 2). Lastly, we will use agents that block or promote lymphangiogenesis to test how brain inflammation, bacterial load, dissemination, and anti-bacterial immunity are affected by alterations of brain drainage with the hope of decreasing CNSTB associated pathologies (Aim 3). CNS tuberculosis is one of the most common bacterial infections of the brain with high mortality with a pressing need for new therapies, and these studies will lead to novel therapeutic strategies in CNSTB. The objectives of this proposal are (1) to test whether infiltrating or resident immune cells produce VEGFC that contributes to cribriform plate-associated, dorsal meningeal, or basal meningeal lymphangiogenesis during central nervous system tuberculosis (CNSTB) (Aim 1); to define cellular and bacterial interaction between Mtb- infected dendritic cells, Mtb, and lymphoid endothelial cells (LECs) (Aim 2); and to understand the translational value of lymphangiogenesis regulators on CNSTB pathogenesis, bacterial control, anti-bacterial responses, and bacterial dissemination (Aim 3). These studies will lead to a new aspect of brain TB pathology and reveal novel information comparing lymphatic vessel responses and brain drainage in different brain inflammations. These studies' long- term objective is to define how the lymphatic system represents a novel target in combating CNSTB.

NIH Research Projects · FY 2026 · 2022-05

Project Summary Embryonic development requires the dynamic remodeling of epithelial sheets as the embryo transforms itself during morphogenesis. Understanding these events has important implications for understanding common human birth defects and common cancers. Our aim is a multidisciplinary, integrated analysis of morphogenetic movements in embryos that unites detailed structural analysis, single-molecule biophysics, genetics, and dynamic in vivo analysis, using the C. elegans embryo as a model system. Our recent focus has been in two broad areas of cytoskeletal regulation: the mechanisms by which mechanotransduction occurs through the cadherin/catenin complex during morphogenesis, and cellular mechanisms of epithelial cell rearrangement driven by basolateral motility. We will continue these emphases here: 1. Define mechanisms of α-catenin mechanotransduction during morphogenesis: We will examine the tension-dependent interaction of SRGP-1/srGAP with HMP-1/α-catenin and how SRGP-1 recruitment positively modulates cadherin complex function. 2. Define mechanisms of self-healing of junctional actin networks under tension during morphogenesis: We will test a model in which different LIM-domain containing repeat (LCR) proteins stabilize different substructures with the junctional proximal F-actin network under tension to prevent self-injury. 3. Define mechanisms of local actin polymerization in during epithelial cell rearrangement: We will use an integrated approach to determine how CRML-1/CARMIL negatively regulates motility via effects on the barbed end actin capping machinery. 4. Define local signaling pathways that promote polarized motility during cell rearrangement: We will determine how additional signaling components regulate epithelial cell rearrangement. As a result of these studies, we will gain new insight into how adherens junctions are able to withstand and respond to tension in a living organism, and we will elucidate a novel pathway regulating cell intercalation via basolateral protrusive activity. Each project has widespread implications for understanding processes crucial for diverse cellular events during human development and disease.

NIH Research Projects · FY 2026 · 2022-05

PROJECT ABSTRACT Sepsis, a life-threatening organ dysfunction syndrome due to infection, is common in hospitalized patients and leads to significant morbidity, mortality, and costs. Over 1.7 million patients develop sepsis in the United States each year, a number that will increase as the population ages. Patients with sepsis contribute to over $24 billion in healthcare costs yearly, and a recent study found that sepsis contributed to up to half of hospital deaths. Furthermore, survivors of sepsis suffer long-term cognitive impairment and physical disability. Therefore, improving the care of patients with sepsis would be enormously beneficial to society. However, there are several critical gaps in the field that need to be addressed: 1) delays in identifying infected patients are common and associated with increased mortality; 2) errors in risk stratification of patients with impending critical illness and sepsis are common and deadly; 3) current treatment strategies for infected patients utilize a one-size-fits-all approach, which neglects the wide range of clinical presentations and underlying biology due to the complex interactions between patient characteristics, the infectious organism, and the host immune response. The overall vision of the PI’s research program is to address these knowledge gaps by utilizing detailed multicenter electronic health record (EHR), clinical trial, and biomarker data combined with machine learning approaches to improve the identification, risk stratification, and discover important subphenotypes of sepsis to decrease preventable death from infection. Over the past five years, the PI has successfully secured independent funding through an NIGMS R01 and Department of Defense award. The PI has published over 80 peer-reviewed publications during this time, is an active member on several national and international committees, has participated in several NIH study sections, and has 40 mentees, including six with NIH K-level awards. Importantly, the PI has also developed and implemented a machine learning risk stratification tool, called eCART, in over 20 hospitals, which has decreased mortality in high-risk ward patients. The goal of the next five years is to build upon these successes and address key gaps in the field through three future directions: 1) using natural language processing and deep learning to improve the identification and risk stratification of infected patients, 2) identifying important subphenotypes using research biomarkers, and 3) using machine learning to develop personalized treatment algorithms. These projects are innovative because they will utilize advanced machine learning methods in a large, multicenter collection of structured and unstructured EHR and biomarker data for developing novel tools in patients with sepsis. In the future, these models will be implemented for earlier identification, accurate risk stratification, and to deliver personalized care at the bedside. This has the potential to revolutionize the care of one of the most common and deadly conditions in hospitalized patients.

NIH Research Projects · FY 2026 · 2022-05

Project Summary Half of children with cerebral palsy (CP) have dysarthria, which has well documented negative effects on speech intelligibility. A primary aim of treatment is improving speech intelligibility. Current pediatric dysarthria interventions focus on clear and/or loud speech, phonation, speech rate, or some combination of these. While several interventions have resulted in intelligibility gains, there is substantial variability in outcomes. Additional interventions are needed to ensure that intelligibility can be maximized for all children. Laboratory studies have consistently identified the articulatory system as the largest contributor to intelligibility deficits in dysarthria, implicating variables such as vowel space and F2 slope. However, these measures are not clinically accessible, nor do they translate to specific treatment targets. Given the primacy of the articulatory system to intelligibility and developmental malleability associated with the acquisition of speech in children, there is a need for sensitive metrics to quantify articulation using clinically meaningful units (i.e., speech sounds). Such metrics would enable us to understand how different speech sounds contribute to intelligibility and would lead to advancements in the development of data-driven interventions for improving intelligibility in children with dysarthria, complementing existing therapies. Our goal is to develop a clinical tool that yields objective, continuous, and automatic quantification of speech sound articulation from connected speech in children; we will use this tool to quantify the contributions of individual phonemes to intelligibility. To do this, we will use state-of-the art speech analytics involving machine learning for acoustic modeling, and clinical research in speech pathology to refine and validate algorithms that specify a phoneme log-likelihood ratio (PLLR) for each phoneme in English. We will use the PLLR to create growth curves for the development of phoneme articulation based on data from 750 typically developing children between the ages of 2 ½ and 10 years, and to characterize the contribution of individual phonemes to intelligibility by age in these children. We will then examine 700 longitudinal speech samples from children with dysarthria between the ages of 2 ½ and 10 years, and identify how they differ from typical children in phoneme development and how speech sound articulation contributes to intelligibility. The outcome of this research is an algorithm that can quantify phoneme articulation in children, indicating a child’s performance relative to norms for each phoneme. Results will specify the relative contribution of individual phonemes to intelligibility, and how this changes developmentally and in the context of dysarthria. A fine-grained understanding of the impact of dysarthria on phoneme development and subsequent contributions to intelligibility has never before been feasible and will have direct clinical and theoretical implications. Results will lay the foundation for new assessments and treatments for improving intelligibility in childhood dysarthria.

NIH Research Projects · FY 2026 · 2022-05

Project Summary Abstract There is a critical lack of information regarding how radiology residents develop interpretive skills for screening mammography. Consequently, little is known how to avert or correct errors in perception and cognition. The majority of radiology residents have only the required minimum 12 weeks of breast imaging training. Yet, the majority of mammograms in the United States are interpreted by general radiologists, not board-certified breast imagers. The negative impact on patient care by not filling this gap in education is continued missed cancers and unnecessary additional imaging and biopsies. The long-term goal of this project is to reduce interpretive errors in breast imaging for improved patient outcomes by providing objective tools and resources to improve trainee education. The overall objectives of this proposal are to understand cognitive and perceptual skill development in a specialized simulation system by bringing together experts in radiology, computer science, educational psychology, and psychology. In residency there is no opportunity for residents to interpret mammographic studies independently from attending radiologists. Thus, offering no opportunity to ‘practice’ their skills. Our education system needs improvement. This project will implement a specialized simulation system with sequential evaluation of radiology resident performance in screening mammography providing objective measures and feedback to trainees. The central hypothesis of this project is that a systemized simulation screening mammography system within residency training will aid in identifying critical cognitive and perceptual errors that negatively impact patient care and outcomes. This hypothesis will be tested by three specific aims: 1) Use machine learning tools to develop congruent case sets for consecutive simulation sessions. 2) Assess the impact of sequential simulation training and examine predictors of individual differences in learning trajectories, by a) assess interpretive skills of radiology residents and fellows in the breast screening simulation system, b) assess real-time perception skills with eye tracking in simulation sessions, and c) assess the resident’s fundamental cognitive and perceptual abilities as well as personality traits. 3) Assess and quantify the effects of sequential simulation training. This research proposal is innovative, in that it provides sequential opportunities for radiology residents to independently interpret screening mammograms in a specialized simulation system that will obtain information about the development of interpretive and perceptive skills over time during real-world practice. This research proposal is significant because simulation training is effective at taking high-risk stakes skills and putting them in a low risk encounters to assess and improve performance. Improving the preparation of radiology residents to interpret screening mammograms will have far reaching impact on women’s health and overall public health.

NIH Research Projects · FY 2026 · 2022-05

Project Summary Axonal degeneration within the corticospinal tract leads to several neurological diseases, including hereditary spastic paraplegias (HSPs), which are a clinically and genetically heterogeneous group of gait disorders characterized by poor balance, spasticity, and progressive muscle weakness that can ultimately result in paralysis. Leveraging parallel animal (rat) and induced pluripotent stem cell (iPSC)-based models, our goal is to develop a better understanding of the pathomechanisms that underlie neurodegeneration resulting from mutations in genes that cause HSP, with a longer term goal of using these models as platforms to identify new therapeutics to combat disease. Using CRISPR-mediated genome editing, we have developed physiologically relevant models that recapitulate phenotypes exhibited by patients suffering from HSP. Specifically, CRISPR- modified rats expressing pathological variants of SPG4 (spastin) and SPG57 (TFG) demonstrate early onset hind limb spasticity and ataxia, which rapidly progresses to hind limb paralysis. Other rat models, including those harboring a truncation of SPG80 (UBAP1) identified previously in patients, exhibit later onset disease phenotypes, enabling us to examine disease progression in multiple, unique contexts. We now have an unprecedented opportunity to determine the mechanistic basis of the axonopathies observed. In particular, we plan to use high- resolution, live cell confocal imaging and electron tomography to test the hypothesis that changes in the trafficking of specific factors, including neurofilament proteins implicated previously in neurodegenerative disease, contribute to impaired neuronal function in HSP. We will also determine how neurofilament trafficking defects observed relate to disease onset based on a combination of electromyography studies, histopathology, and comprehensive gait and kinematic analysis of rodent movement as spasticity and muscle weakness ensues. Furthermore, we will determine mechanisms by which mutations that underlie HSP impact neuronal excitability, again using live cell imaging approaches, but also in vitro biochemistry and genetic studies. Collectively, this work will help to uncover several of the mechanisms that contribute to neuronal dysfunction observed in patients with HSP and lay the foundation for the future development of drug screening approaches.

NIH Research Projects · FY 2026 · 2022-05

PROJECT SUMMARY/ABSTRACT Neurons and endocrine cells release signaling molecules through Ca2+‐triggered exocytosis. Ca2+ enters a nerve terminal or endocrine cell, binds to a Ca2+ sensor protein, and triggers the fusion of vesicle and plasma membranes to expel neurotransmitters and hormones. To investigate the mechanisms of exocytosis our research focuses on fusion pores and Ca2+. Ca2+ triggers the opening and evolution of the fusion pore; the fusion pore is an aqueous passage between the vesicle interior and cell exterior. All secreted molecules pass through a fusion pore, which is strategically situated to exert finely tuned control over secretion. We use biophysical techniques to probe fusion pores at the single‐pore level, track their transitions, and monitor their responses to biological signals. Studies of the fusion pore have given us valuable insights into the roles of specific proteins in the control of exocytosis. We showed that SNARE protein transmembrane domains alter flux through initial fusion pores in both endocrine and synaptic exocytosis. We have made important advances in understanding the nascent fusion pores of endocrine exocytosis, but progress has been slow in understanding endocrine fusion pore expansion, and how fusion pores impact synaptic transmission. Innovations from this laboratory have created opportunities to take on these new challenges. Project 1. We have developed a new method for analyzing amperometric recordings to probe the dynamics of late‐stage endocrine fusion pores. This method tracks fusion pore permeability as vesicles lose catecholamine, and led to the novel findings that a fusion pore sequentially expands, contracts, and settles into a metastable state. We will use measurements of late‐ stage fusion pores to address long‐standing questions about the biological control of secretion. We will probe late‐ stage fusion pores for control by lipid bilayer elasticity, Ca2+, synaptotagmins, and synaptophysin/dynamin. Project 2. To study synaptic fusion pores we developed a co‐culture system with neurons and HEK293 cells expressing 4 postsynaptic proteins, neuroligin 1, GluA2, stargazin, and PSD95. These HEK cells serve as sensors of synaptic release, yielding miniature synaptic current data of exceptional quality in which fusion pore contributions are more clearly resolved. In parallel with Project 1, we will use HEK cell‐neuron co‐cultures to determine how synaptic fusion pores are controlled by bilayer elasticity, Ca2+, synaptotagmins, and synaptophysin/dynamin. The results on endocrine and synaptic fusion pores will be synthesized into a comprehensive framework for regulated secretion. We will then adapt this co‐culture system to the study of synaptic kiss‐and‐run and presynaptic contributions to synaptic plasticity. Project 3. We will adapt HEK cell synaptic sensors to the study of synaptic release from neurons derived from human stem cells. Collaborators have been recruited to provide neurons, which we will use to evaluate synaptic release and fusion pores in Down syndrome, fragile X mental retardation, aging, Parkinson's disease, and tuberous sclerosis complex. This work will provide insight into the molecular mechanisms of exocytosis, illuminate its molecular control, and show us how synaptic release goes awry in diseases.

NIH Research Projects · FY 2026 · 2022-04

PROJECT SUMMARY / ABSTRACT In response to PAR-20-036: Getting to Zero: Understanding HIV Viral Suppression and Transmission in the United States, we propose a hybrid type 2 effectiveness-implementation study that will evaluate an innovative clinic-level intervention featuring an evidence-based mobile health (mHealth) application (CHESS) and peer- driven social support. Within the infrastructure of a large HIV/AIDS Service Organization offering an integrated, patient-centered model of care in Colorado, Missouri, Texas and Wisconsin, we will implement an mHealth system designed to close information gaps, build intrinsic motivation, and develop behavioral skills needed for sustained adherence to treatment. Peer support will be provided through activities delivered by patients recruited and trained to serve as peer mentors. The mHealth system and peer mentoring will be integrated into the existing care model, known as the HIV Medical Home. We hypothesize that the integrated intervention will increase the proportion of patients with viral suppression and reduce missed clinic appointments by supporting three needs: (1) It will facilitate real-time, community-based capture of data reflecting social and behavioral determinants known to precede lapses in HIV care (e.g., housing and food insecurity, unhealthy alcohol or drug use, or poor medication adherence); (2) It will improve engagement in care by increasing social connectedness among patients, and between patients and peer mentors; and (3) It will support retention in addiction treatment and mental health care that help maintain engagement in HIV care. Project Year 1 will be devoted to planning and refinement of the intervention in close collaboration with organizational leaders and people living with HIV who are members of the local communities. Beginning in Project Year 2, we will conduct a stepped wedge cluster randomized trial of the intervention in seven clinics. We will leverage data collected through the integrated electronic health record system serving all seven clinics to test intervention effectiveness on viral suppression and retention in care. We also will conduct an implementation cost analysis and cost-effectiveness analysis to inform future sustainment of the intervention model. The study builds on a solid foundation of prior research demonstrating the promise of mHealth and peer strategies for enhancing engagement in HIV and addiction treatment and care for other complex conditions. The findings from this study, if successful, will contribute a new and innovative set of tools with high potential impact for improving HIV viral suppression in multiple geographic settings.

NIH Research Projects · FY 2026 · 2022-04

PROJECT SUMMARY Approximately 70% of breast cancers (BC) are estrogen receptor (ER)-positive, also characterized as luminal- type BC; thus, are treated with endocrine therapy (ET). The transition from ER+ luminal cells to ER-negative ‘stem-like cells’ (SLCs) is a major mechanism of ET resistance; however, the underlying mechanism remains largely unknown. We discovered that Ctr9, a subunit of PAFc transcriptional activator complex, is a determi- nant of luminal cell identity. Using inducible and stable Ctr9 knockdown (KD) BC cell lines, a substantial decrease of ER stability and increase of H3K27me3, a repressive histone mark on chromatin, were observed upon Ctr9 depletion, indicating of a transition from luminal BC cells to SLCs. The cellular plasticity manifested by Ctr9 engages two downstream effector proteins, Jarid2 and KDM6A, that control the levels of repressive histone mark, H3K27me3. Ctr9 silencing leads to decreased Jarid2, a subunit of PRC2, and triggers a PRC2 subtype switch from less active PRC2.2 to PRC2.1 with higher H3K27me3 activity. In addition to enhancing PRC2 H3K27me3 deposition activity, Ctr9 KD results in a decrease of KDM6A, the ‘eraser’ enzyme for H3K27me3. Furthermore, Ctr9 depletion generates vulnerability that renders BC cells hypersensitive to EZH2 inhibitors (EZHi). EZH2 is highly expressed in SLCs for stem cell maintenance and expansion. Recently, tazemetostat, an EZH2i, is FDA-approved for the treatment of follicular lymphoma. We hypothesize that loss of Ctr9 leads to the transition from a Ctr9-expressing luminal lineage to an EZH2-governed SLC, thus the cells become sensitive to EZH2i. We will test our hypothesis by pursuing three aims: (1) Dissect how Ctr9 depletion results in transition from ER+ luminal cells to SLCs; (2) Determine the roles of Jarid2 and KDM6A during luminal to SLC transition and sensitivity to EZH2i; (3) Determine whether Ctr9 and H3K27me3 are predictive biomarkers for EZH2i sensitivity in vivo and study the inverse correlation of Ctr9 levels with H3K27me3 in human specimens. Because of the higher levels of expression of EZH2 in ER-negative BC as compared to ER+ BC, EZH2 inhibition has been extensively investigated in ER-negative BC. The study is of high impact because our findings that Ctr9 demarcates EZH2 activity and H3K27me3 levels in luminal cells opens an excit- ing possibility to target Ctr9low/H3K27me3high ER+ BC using EZH2i. Successful completion of this study will justify a clinical trial to use Ctr9/H3K27me3 as independent biomarker to select ER+ BC patients for treatment with EZH2i.

NIH Research Projects · FY 2025 · 2022-04

PROJECT SUMMARY: The overall goal of this application is to develop, implement and test a “single button push”, integrated combination of innovative MRI solutions to enable widespread and generalizable implementation of quantitative evaluation of chronic liver disease in < 5 minutes. We aim to design a reliable, efficient, low variability, and fully automated, MRI exam. This goal will be enabled by artificial intelligence (AI), reengineered chemical shift encoded (CSE)-MRI to provide “error-free” free-breathing measurement of liver fat and iron, an innovative MRI suite design, and automated analysis. In this way, we aim to achieve high-throughput, low-cost evaluation of liver disease with high accuracy, precision and reproducibility. Abnormal accumulation of triglycerides in hepatocytes, or steatosis, is the earliest feature of non-alcoholic fatty liver disease (NAFLD), affecting ~100 million people in the US. Liver iron overload is common in patients with hereditary hemochromatosis and those receiving repeated blood transfusions. Early, affordable, and accessible non-invasive detection and quantitative staging of liver fat and iron would impact the health of millions of people at risk for NAFLD and its comorbidities, as well as those with liver iron overload. Confounder-corrected CSE-MRI provides simultaneous estimation of liver proton density fat fraction (PDFF) and R2*, which are accurate, precise and reproducible biomarkers of liver fat and iron. A primary determinant of the cost of MRI is scheduled MRI suite time. Minimum slot times to accommodate the majority of patients are driven by variability in exam duration and MRI suite turnaround time. As MRI scan times are shortened, the largest contributor to exam duration is the time needed for i) manual image prescription, ii) repeated scans (rework), and iii) room turnaround time. Many patients, including children, are unable to hold their breath for the duration of CSE-MRI (~20 seconds) leading to ghosting artifacts that corrupt PDFF / R2* maps, necessitating repeated CSE-MRI acquisitions and exacerbating exam time variability. We will address these challenges by developing fully automated AI-based image prescription based on multi-center, multi-vendor data at 1.5T and 3T, in parallel with a novel “error-proof” high SNR “snapshot” CSE-MRI method that is insensitive to breathing motion. This will be performed using a novel MR “Smart Suite” design, capable of patient turnaround in less than 2 minutes, followed by automated quantitative analysis and reporting. We will implement and test a fully automated, single button push CSE-MRI exam by aiming to: 1). Develop and optimize motion insensitive, high SNR, free-breathing CSE-MRI for accurate and precise measurement of PDFF and R2*, 2). Confirm the accuracy, repeatability, and reproducibility of the proposed CSE-MRI method in patients with liver fat and iron overload, and 3). Implement and validate a fully automated CSE-MRI protocol in less than 5 minutes of MR room time. If successful, this work will provide a high-throughput, high value solution for liver fat/iron quantification. The innovations proposed in this application will also have broad applicability beyond CSE-MRI, and ultimately reduce cost and increase access, through improvements in MRI scanner utilization.

NIH Research Projects · FY 2026 · 2022-04

PROJECT SUMMARY/ABSTRACT Radical intermediates generated through chemoselective single electron reduction have broad utility in the development of valuable synthetic transformations. As a consequence, photoredox catalysis, which induces single election transfer with exceptional selectivity for radical pathways, has shown great promise as an enabling technology in biomedical research. However, the design underpinning current photoredox catalysts limits the accessible reduction potentials and excludes numerous abundant feedstocks. The selective generation of radical intermediates from substrates inert towards conventional photoredox catalysis is a long- standing challenge with no general solutions. This proposal is based on the discovery that electrochemistry can generate new radical anion photocatalysts that are exceptionally potent excited state reductants but retain the selectivity of typical photoredox catalysts. We will study how these new catalysts can be exploited to develop radical coupling reactions infeasible with modern synthetic tactics. The three specific aims of this research center on exploring distinct but interwoven aspects of this new catalytic platform. Aim 1. We are exploring the ability to generate and exploit the reactivity of aryl radicals from aryl chlorides Aim 2. We are exploring the ability to engage carbonyl compounds in reductive radical coupling reactions Aim 3. We are exploring operationally simple strategies to access radical anion photocatalysts These methods address long-standing challenges in a fundamental class of organic reactions, reductions. These new catalytic systems will offer an expanded and diversified pool of starting materials from which the next generation of drugs and molecular probes will be discovered.

NIH Research Projects · FY 2026 · 2022-04

Breast cancer is the most commonly diagnosed malignancy in women worldwide. Mitotic Arrest Deficient 1 (Mad1) is commonly upregulated in breast cancer where it serves as a marker of poor prognosis, and upregulation of Mad1 is sufficient for tumorigenesis in orthotopic breast cancer models. Mad1 was identified and characterized for its function in mitosis, where it serves to prevent chromosome missegregation/chromosomal instability (CIN). CIN has been implicated in promoting both primary and metastatic tumors. However, Mad1 is expressed throughout interphase and we have recently shown that a non-canonical interphase function of Mad1 in destabilizing the p53 tumor suppressor is critical for Mad1 upregulation to promote orthotopic mammary tumor growth. Additionally, we identified a previously unrecognized pool of Mad1 that localizes to the Golgi apparatus. At the Golgi, Mad1 performs another non-canonical function in the maturation and secretion of newly synthesized α5 integrin, a critical metastasis promoter and marker of poor prognosis. Thus, Mad1 upregulation results in three tumor- and metastasis-promoting phenotypes: CIN, p53 destabilization and α5 integrin secretion. Aim 1 will determine which functions of Mad1 upregulation are necessary and sufficient for tumor promotion using separation of function mutants, competition experiments, specific inhibitors, and novel CRISPR/Cas9 edited mouse models. Aim 2 will define the mechanisms by which Mad1 functions in the secretion of newly synthesized α5 integrin, which will provide novel opportunities to inhibit α5 integrin activity in promoting metastasis. Together, the proposed experiments will identify the mechanistic basis of the tumor promoting activity of Mad1 and define the α5 integrin biosynthetic trafficking pathway, which will expand our fundamental understanding of breast cancer and reveal novel therapeutic targets.

NIH Research Projects · FY 2025 · 2022-04

PROJECT SUMMARY/ABSTRACT The underpinnings of sudden cardiac death are related to genetic and acquired ion channel abnormalities and many are related to potassium channel variants. Gains in phenotype-genotype correlative studies have revolutionized our understanding of a range of sudden arrhythmic death syndromes, yet currently, identification of coding variants has far outpaced our ability to correctly classify the variant, and for most genes there are more unclassified variants (variants of unknown significance, VUS) than classified. This creates barriers for clinical care, familial cascade screening and, moreover, a functional link to disease. The importance of physiologic and functional analysis for variant classification has been emphasized, yet contemporary methods are cumbersome (time and resources) decreasing efficiency in unraveling the arrhythmic risk associated with genetic variants. Our lab’s work focuses on functional genomics of abnormal cardiac repolarization and cardiac arrhythmic sudden death syndromes, and we have developed high volume assays to understand variant pathogenicity. Yet most variant characterization proceeds in a reactive manner (clinical variant identification followed by functional study) and clinical association is often lacking (siloed research); this creates gaps in optimal and efficient variant classification. We aim to address these major gaps in knowledge by creating a pro-active, data driven and mechanistic variant classification scheme cross-validated with clinical data. In Aim 1, Deep Mutational Scanning (DMS) of Kir2.1, a K+ channel essential for repolarization, and MAVE (multiplexed assay of variant effects) creation will unveil functional annotation of all possible variants simultaneously to create a comprehensive fitness landscape. In Aim 2 MAVE will be applied to all K+ channel variants identified from TOPMed and the UK Biobank that have effects on repolarization to triangularly validate phenomic-genomic-functional data for genetic variant classification. Lastly, in Aim 3 we integrate genetic variant and MAVE results with traditional cellular markers of abnormal repolarization using an iPS-cardiomyocyte model and molecular computational modeling. Our central hypothesis is that DMS will uncover loss of function variants in regulatory regions of Kir2.1, MAVE of low frequency K+ channel coding variants from the TOPMed and UK Biobank will reveal common thematic and mechanistic readouts, and these can be validated in iPS-CMs and computational molecular modeling. The outcomes of this study will allow the field of functional genomics to begin to keep pace with rapidly evolving genetic discovery through high integrity, high throughput, and highly reproducible and unbiased techniques. We will create a methodologic template to catalog all other high-impact repolarization associated variants as a vital step to transition from reactive to proactive classification. Moreover, we will help establish the methodology to correlate clinical findings with variant characterization using parallel mechanistic techniques. This is an innovative proactive, data-driven approach, usable by clinicians and research teams alike to determine actionability of a given variant and to inform predictive models to reveal new structural-functional insights.

NIH Research Projects · FY 2026 · 2022-04

PROJECT SUMMARY Every year, more than 795,000 people in the United States have a stroke, with currently around 4.7 million survivors. Approximately 20% of survivors develop vascular contributions to cognitive impairments and dementia (VCID) which is second only to Alzheimer’s disease (AD). While several putative biomarkers are known, a considerable gap exists in stroke research in terms of validation and interaction of biomarkers of VCID. There is a critical need to better understand the complex interactions of VCID risk factors, baseline cognitive and brain health, and incident stroke lesion burden on post stroke brain changes and subsequent development of VCID. The specific aims of this project will address this need innovatively by (1) utilizing a novel neighborhood disadvantage atlas to geo-spatially map and quantify socio-economic disadvantage, (2) quantifying vascular risk burden, (3) incorporating baseline brain and cognitive health, (4) leveraging technical advances in state-of-the- art connectome MRI, and (5) applying network neuroscience and machine learning. In addition, we will recruit participants from underrepresented minority groups (African Americans, Hispanics, Native Americans), rural/urban, low/high SES who might be at increased risk for VCID. Our central hypothesis is that VCID risk factors, baseline cognitive and brain health, incident stroke damage, and post stroke brain changes will act in concert through brain perfusion, structure, and connectivity pathways in determining whether a stroke patient develops VCID. We will collect longitudinal connectome MRI and Neuropsychological data from a prospective cohort of patients 55-90 years old with incident ischemic stroke in the left (n=50) or right (n=50) middle cerebral artery territory. We will prospectively collect data on n=50 and retrospectively use n=100 from AD connectome project for matched healthy controls. Aim 1 (Brain changes): Characterize how the interaction of VCID risk factors (e.g., cardiovascular, demographics), baseline brain health and the extent of incident stroke damage will affect post stroke brain changes at 6 months. Aim 2 (Brain-cognition relationships): Characterize specific relationships between VCID risk factors, baseline cognition, brain, incident stroke, post stroke brain changes and post stroke cognitive function at 6 and 12-months across 5 cognitive domains including executive function, attention, language, memory and visuospatial. We will use advanced machine learning to build predictive models that will identify contributory and deleterious brain changes associated with post stroke cognitive outcomes. Successful completion of the project will provide currently lacking scientific understanding of the intricate biological relationships between VCID risk factors, stroke MRI biomarkers, and their interactions, that underlie the biology of cognitive outcomes after an ischemic stroke. The results will lay a strong foundation for building accurate diagnosis, prognosis, disease monitoring tools, and future clinical studies that can aid in positively altering disease progression and reducing illness burden on patients due to post ischemic stroke VCID.

NIH Research Projects · FY 2026 · 2022-04

ABSTRACT Functional specialization in a multicellular organism arises when cell fate is established by a specific gene expression pattern. Epigenetic modifications working with transcription factors enable cell identity. During early development a few cells migrate at the epiblast stage to the gonad to become Primordial germ cells (PGCs), which are the precursors of gametes. PGCs undergo an ordered series of global epigenetic changes that decimates the repressive modifications: H3 lysine 9 methylation (H3K9me2) and DNA methylation, which suppress expression of repetitive elements to maintain genomic integrity, and is replaced by other marks such as H2A/H4 arginine methylation (H2A/H4R3me2). How the precise temporal regulation of these epigenetic events is coordinated and their interdependence remains poorly understood. Incorrect or partial erasure at specific locations could lead to imprinting defects as well as inadvertent transgenerational inheritance. We have discovered that the H3K9me2 demethylase, KDM3B, controls DNA demethylation by the Tet enzymes and interacts with PRMT5, a H2A/H4R3 methyltransferase. Despite H3K9me2 being a repressive histone modification, we have found that KDM3B and KDM3A interact with mRNA processing machinery. Taken together we hypothesize that proteins of the KDM3 family orchestrate post-implantation development to PGCs by epigenetic and post-transcriptional mechanisms, which will be investigated in this proposal.

NIH Research Projects · FY 2026 · 2022-03

ABSTRACT Pregnancy-induced vascular adaptations, adequate placental vascularization, and optimal flux of nutrients across the placenta to the fetus are critical to support fetal growth. Disruption in one or more of these processes leads to fetal growth restriction (FGR). FGR affects up to 15% of all newborns, and no treatment is available. The cause of FGR is not known, but the environmental exposure to per- and poly-fluoroalkyl substances (PFAS) and its bioaccumulation in the placenta may hold important keys to understanding the origins of the disease and the underlying causes of maternal organ dysfunction. Perfluorooctane sulfonate (PFOS), a legacy PFAS, is the most produced and well studied PFAS. Elevated maternal PFOS is shown to be associated with maternal vascular dysfunction and FGR in humans. Whether this increase in PFOS is directly involved in endothelial dysfunction and manifestations of FGR is unknown. Our pilot studies show that elevated PFOS in pregnant rats increases maternal blood pressure, blunts endothelial function, and decreases in placental size, VEGF expression, and nutrient transport. Based on these findings, we hypothesize that elevated PFOS levels impair maternal cardiovascular function and reduce placental vascularization and flux of nutrients to lead to FGR. We will examine this premise in 3 aims employing in vivo animal studies, ex vivo tissue-level functional analysis and in vitro molecular analyses. Aim 1 will first establish the functional effects of elevated PFOS on systemic blood pressure and uterine artery blood flow and define the PFOS-mediated signaling. To test the PFOS-mediated vascular mechanisms, EDHF, NO, and PGI2 relaxation pathways will be determined. Also, the expression of eNOS and its activity state—signaling components of EDHF and PGI2 pathways as well as nitrate/nitrite and PGI2 production and changes in membrane potential—will be measured. Then translational studies will test whether PFOS affects the endothelial pathways and mechanisms in pregnant women by examining the effects in isolated omental and placental vessels. Aim 2 will examine placental vascular effects. We will determine if elevated PFOS decreases growth, diameter, and length of spiral arteries, central arterial canals, fetoplacental arterial branches, and umbilical arteries. We will also measure the expression of pro- and anti-angiogenic factors in the placenta, and then determine if PFOS disrupts signaling mechanisms in endothelial cells isolated from pregnant women. Aim 3 will examine placental nutrient transport effects. We will determine if elevated PFOS decreases glucose, amino acid, and fatty acid transport across the placenta to the fetus and measure the expression of nutrient transporters in the placenta. Then, determine if PFOS disrupts nutrient transport in pregnant women by examining the effects in primary trophoblasts. These results are expected to have an important impact because they will contribute substantively to a mechanism-based understanding of PFOS's role in pregnancy complications and alert environmental agencies to devise policies to curtail PFOS exposure to reproductive-age women.

NIH Research Projects · FY 2026 · 2022-03

New antifungal drugs are needed to address the emergence of pan-drug resistant fungal pathogens that threaten a growing immunocompromised patient population. Underscoring this urgency is the recent global spread of Candida auris, which is resistant to all three of the available antifungal classes. Natural products from bacteria have served as an important source of anti-infectives, including antifungals. We leveraged new sources of bacteria harvested from marine invertebrate microbiomes to generate natural product screening libraries and identified turbinmicin, a novel antifungal targeting multidrug resistant (MDR) fungal pathogens. Turbinmicin displays potent in vitro and in vivo efficacy toward multiple MDR-fungal pathogens, exhibits a wide safety index, and functions through a fungal-specific mode of action, targeting the vesicular trafficking pathway. We subsequently synthesized turbinmicin analogs to modulate the pharmaceutical properties including solubility. Based on our promising results, our premise is that turbinmicin analogs represent the next generation of safe and effective antifungal targeting drug resistant fungal infections. In this project, the Wisconsin Drug Discovery and Development Center will use lead optimization to develop turbinmicin, a novel natural product representative from a new class of broad-spectrum and non-toxic antifungals. The aims are focused on efficacy (specific aim 1), safety (specific aim 2), and production/formulation (specific aim 3). We divide each of the three aims into two sequential Stages. Stage 1 will identify the most promising lead analog based upon efficacy, safety, and solubility screens. Stage 2 will delineate IND-enabling PK/PD efficacy and safety in established murine models and rat models, respectively. Impact: As there are no effective therapies for emerging pan-drug resistant fungal pathogens, our work fills a critical unmet need. Our studies will provide several IND-enabling datasets for clinical development of a new class of antifungal targeting high threat drug-resistant fungi. The investigations use complementary, cutting-edge technologies to test the efficacy and safety of the turbinmicin compound series, and optimize drug production. The research will be performed in outstanding environments by a cohesive group of PIs and industry partners, with complementary expertise in preclinical and clinical antimicrobial pharmacology and natural product chemistry.