Vanderbilt University Medical Center

NIH Research Projects · FY 2026 · 2026-03

TITLE: Advancing Statistical Methods for Next-Generation Microbiome Data Analytics Abstract: The focus of our research lab is to support human microbiome research with rigorous, robust, and practical statistical and quantitative methodology. In the next five years, our goals are to address critical data analysis gaps raised by recent advancements in microbiome epidemiology and bioinformatics, and to develop novel statistical methods that will facilitate the next generation of microbiome analytics. First, expanding microbiome consortia and public databases increase precision in testing the microbiome’s association with host conditions, but introduce more sources for unmeasured confounding such as population heterogeneity or uncollected covariates (e.g., medication). Recent statistical research has focused on confounding from the data’s compositional nature but largely ignored these unmeasured and potentially stronger factors. We propose to benchmark unmeasured confounding effects in microbiome studies with diverse real-world data, and to develop specialized latent factor modeling techniques for adjustment. This will improve false discovery control and facilitate robust findings in large-scale microbiome association studies. Second, modern bioinformatics can generate rich whole-microbiome genetic profiles with millions of microbial genes. But these profiles tend to have extreme levels of sparsity and lack functional annotations, limiting interpretability and statistical power in downstream findings. We propose to leverage recent breakthroughs in artificial intelligence and genomic large language models (LLMs) towards this problem. We will utilize the inherent functional dependency structure encoded by genomic LLMs to create putatively functional orthologs of microbial genes, which can meaningfully aggregate sparse and under-annotated “dark-matter” genes. This will empower downstream analyses and unlock the potential of modern microbiome bioinformatics. Third, metatranscriptomic (MTX) protocols are increasingly available, which characterize the microbiome beyond its functional capacities (“what can microbes do”) and reveal functional bioactivities in situ (“what are microbes doing”). MTX expressions depend on the underlying gene abundances, which are dynamic and error prone. Existing methods do not account for this and can generate biased findings. We will develop a rigorous error-in-variable model that will properly adjust for dynamic and noisy gene abundances, thus enabling robust differential expression analysis in new MTX studies. Our developed methodologies will be validated in different populations, disease settings, and microbiome ecologies, and implemented as open-source software. Derived data resources will be provided as publicly available databases. Through this proposal, our overall vision is to address critically unmet analytical needs from recent advancements in microbiome epidemiology and bioinformatics, and provide a publicly available toolkit of novel statistical methods that will support the next phase of human microbiome research and catalyze translational discoveries. 1

NIH Research Projects · FY 2026 · 2026-03

PROJECT SUMMARY This application addresses the overarching challenge of the early detection of Alzheimer’s disease (AD). It does so by proposing a novel approach to image soluble Abeta oligomer (SAbO) clearance dynamics. SAbOs occur years earlier before amyloid-b (Abeta) plaques and are thought to be the real culprits behind neurodegeneration. Importantly, this project focuses on detecting SAbO in the retina by using signals emitted from an innovative fluorescent nanobody developed by this team. The pathology of AD is characterized by the initial presence of extracellular deposits of misfolded and aggregated Abeta proteins, which subsequently spread from the hippocampus to the cerebral cortex causing neuronal death and, ultimately, loss of memory and cognition, and the ability to speak. At present, no disease- modifying therapy is effective against AD, nor is it possible to diagnose the disease’s early onset or progress. Recent findings indicate that elevated levels of Abeta proteins in brain and eyes are associated with dysfunctional neuronal network. Because AD undergoes a protracted asymptomatic stage before it reaches advanced conditions, a window of opportunity exists for early intervention. Successful detection of the onset of this disease via routine screening will improve therapeutic outcomes and save lives. The retina is part of the CNS and is densely covered with capillaries and other blood vessels. For these reasons it is possible to observe SAbO clearance in blood within the retina. We present a novel SAbO clearance process that can be visualized in the retina using a fluorescein-labeled, SAbO-specific nanobody. Because SAbO forms early in AD, we propose eventual development of retina screening as part of eye exams. In collaboration with Prof. Joanne Matsubara, using our newly developed fluorescein-labeled nanobody, we discovered a dynamic SAbO clearance process in the retina of healthy human donor eyes. In retinas, we observe SAbO with the size and shape with the dimension of nanoparticles within the blood capillary vessels of the inner limiting membrane. In contrast, we noted that this SAbO clearance process is disrupted significantly in AD human donor eyes. Based on this observation, we hypothesize that disruption of SAbO clearance could promote Abeta aggregation. These data corroborate with our recent report showing significant Abeta deposits in AD compared to control human donor eyes. Based on these results, we propose, that dysregulated SAbO clearance mechanisms results in reduced clearance of SAbO nanoparticles, and subsequent enhanced Abeta deposits in the retina. We propose to capitalize on these observable changes in SAbO dynamics as a biomarker for early AD detection. In this project, our objectives are to (i) optimize the development of a fluorescent nanobody, and (ii) evaluate early dysfunctional clearance of SAbO nanoparticles as an early biomarker of AD.

NIH Research Projects · FY 2026 · 2026-03

PROJECT SUMMARY/ABSTRACT: Critical illness syndromes, particularly sepsis, are a leading cause of morbidity and mortality worldwide spanning all demographics. Sepsis arises from a dysregulated immune response to infection leading to systemic end-organ injury. CD8 T cells, critical for pathogen defense, are profoundly impaired during sepsis, exhibiting high rates of attrition, reduced cytokine production, and exhaustion-like phenotypes. Systemic metabolic dysfunction, a hallmark of critical illness driven by hypoxemia, tissue hypoperfusion, and inflammation, exacerbates immune cell dysfunction. However, the mechanisms linking metabolic stress to CD8 T cell failure in human critical illness with and without sepsis remain poorly understood. Our preliminary studies reveal that effector CD8 T cells from critically ill and septic patients exhibit abnormal mitochondrial phenotypes, including heightened glutamine metabolism that correlates with elevated exhaustion markers, impaired effector function, and worse clinical outcomes. Using single-cell RNA sequencing, we further identified a distinct effector CD8 T cell subset (CXCR4hi IL7Rlo) unique to critical illness, characterized by high levels of terminal exhaustion markers TIM-3 and TOX, reduced cytotoxic features, and profound hypometabolism. Among the most highly downregulated genes in this CXCR4hi IL7Rlo subset was phosphoglycerate mutase 1 (PGAM1), a glycolytic enzyme that regulates both ATP production and biosynthesis. Accordingly, we hypothesize that metabolic alterations in effector CD8 T cells drive their failure in human critical illness with and without sepsis. Aim (1) will determine how glutamine metabolism modulates effector CD8 T cell fitness and function. Using patient-derived CD8 T cells, we will employ advanced techniques, including high-dimensional spectral flow cytometry, 13C-glutamine tracing, and pharmacologic manipulation of glutaminase activity. These will assess how blocking glutaminolysis affects cytokine production, cytotoxicity, and exhaustion marker expression, and directly trace glutamine usage for energy, biosynthesis, and antioxidant generation. Aim (2) will test the role of PGAM1 as a metabolic switch controlling energy production and biosynthesis in effector CD8 T cells. We will evaluate whether PGAM1 inhibition recapitulates the functional and metabolic impairments observed in CXCR4hi IL7Rlo CD8 T effector cells, test whether rescuing glycolysis and biosynthetic pathways with pyruvate and ribose-5-phosphate, respectively, can restore effector function in CXCR4hi IL7Rlo CD8 T cells, and correlate CXCR4hi IL7Rlo CD8 T effector frequencies and phenotypes with clinical metrics in critical illness with and without sepsis. These studies hold the promise of directly linking systemic metabolic dysfunction to CD8 T cell immune failure in human critical illness and sepsis, providing key insights into immunometabolic regulation and identifying new therapeutic targets. This award will provide essential training in translational immunometabolism and human critical illness research, supported by mentorship and guidance from leading investigators in these content areas, to develop the PI into a successful, independent physician-scientist.

NIH Research Projects · FY 2026 · 2026-02

The ML/AI Tools to Advance Genomic Translational Research (MAGen) consortium is a national, highly functional, network infrastructure that will enhance the accuracy and precision of predicting how individuals with pathogenic variants manifest disease. Our MAGen Coordinating Center (CC) Team is composed of leading experts at Vanderbilt University Medical Center. As the CC, we will support the Development Sites (DS) to synthesize Genetic variant Evidence using Novel tools to Elucidate Pathophysiology: Accelerating Translation to Health’ (called ‘GENEPATH’) as well as support the Consortium in defining critical connections to optimally create tools that provide a holistic prediction with explanation of how a variant causes disease in an individual in the context of their life along with exploring the ethical, legal, and social implications (ELSI) of integrating ML/AI tools into genomic medicine. This work requires that GENEPATH bring together experts on variant interpretation, protein function, genomic medicine, genetic anthropology, informatics, genomic consortium coordination, and all aspects of ELSI, along with our unique skills in consensus building to support DSs in coordination, ELSI research projects, and development of a common data model. Functionally, 1) we will serve as a central home for the Consortium by implementing the Scientific Operations Unit. This Unit will coordinate all Consortium activities including supporting the Consortium and its Steering Committee to establish, monitor, and reach program goals, providing project management with deep knowledge of machine learning, ELSI, and genomic medicine to ensure milestones are met, and structuring Consortium collaboration to promote synergy. 2) We will establish a flexible technical architecture adoptable by development sites through the Data & Machine Learning Unit which will create common data models that handle multi-domain, structured and unstructured data, and plan the cross-validation protocols, as well as collaboratively define specifications for AI/ML variant characterization tools. 3) We will build trust and credibility through the Engagement in ELSI Unit by ensuring authentic communication with patients, communities, and providers to guide Consortium planning. GENEPATH efforts will allow us to broaden our understanding of how variants manifest in disease, leading to a more precise and effective use of genetic variation in research and healthcare.

NSF Awards · FY 2026 · 2026-02

The Committee on New Researchers of the Institute of Mathematical Statistics will hold its 25th conference at Vanderbilt University during the three days prior to the Joint Statistical Meeting. The event will include oral and poster presentations by new researchers, plenary talks by established researchers, and open discussions on future directions for statistics, probability, and data science. There will also be panel discussions on teaching and mentoring, publishing, funding, and collaborations. The New Researchers Conference is an annual event organized under the auspices of the Institute of Mathematical Statistics by its Committee on New Researchers. It serves as the flagship meeting for early-career researchers in statistics, probability, and data science. In 2025, Vanderbilt University will host the 25th New Researchers Conference on the three days prior to the Joint Statistical Meetings. The primary objective of the conference is to provide a platform for interaction among new researchers and offer opportunities for mentorship from leaders in the field. This conference is explicitly aimed at developing the next generation of researchers in statistics and probability. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2026-02

PROJECT SUMMARY Cochlear implants (CIs) are the standard of care for adults with severe-to-profound sensorineural hearing loss. Unfortunately, a sizeable portion of adults receiving CIs experience relatively poor CI benefit: up to 50% of CI users are unable to use the telephone without captions, and 13% of patients are unable to repeat 10% of the words presented auditorily. I have spent the last 12 years of my career working to identify “top-down” cognitive- linguistic abilities that explain and predict CI outcomes, in addition to “bottom-up” auditory abilities. Extensive evidence suggests that a poor speech recognition outcome may be attributable to deficits in bottom-up processing, top-down processing, or both. However, prior work has not yet led to interventions to improve CI outcomes, especially for poor performers, which the proposed project aims to address. I am also devoted to mentoring the next generation of surgeon-scientists in the field of Otology/Neurotology and specifically patient- oriented research. The number of physicians pursuing patient-oriented research is declining. Maintaining a strong pipeline of surgeon-scientist trainees devoted to patient-oriented research is crucial for continued development of our specialty and scientific advancement. The proposed project will be a clinical trial feasibility study to characterize the top-down and bottom-up profiles of a group of adult CI recipients who demonstrate relatively poor speech recognition outcomes, and to determine the feasibility of two different interventions for these individuals including an “auditory” intervention approach and a “cognitive” intervention approach. Results of this project will advance our basic knowledge of factors contributing to poor outcomes in adult CI users and will form the foundation for a larger randomized controlled trial of auditory and cognitive interventions to optimize outcomes for poor-performing adult CI users, while providing opportunities for surgeon-scientist mentees to develop their skills in patient-oriented research.

NIH Research Projects · FY 2026 · 2026-02

Anemia is common in the elderly and a risk factor for adverse cardiovascular events, cognitive decline and poor quality of life. It is often due to underlying inflammation or chronic kidney disease (CKD). Major etiological factors in the pathogenesis of anemia in CKD or inflammation are relative erythropoietin (EPO) deficiency and dysregulation of iron metabolism. Relative EPO deficiency refers to the reduced ability of the diseased or inflamed kidney to produce adequate amounts of EPO in response to hypoxia or anemia. EPO is a glycoprotein hormone and essential for erythropoiesis, with the kidney being its main production site under most physiological conditions. In the kidney, EPO is produced by interstitial perivascular fibroblast-like cells and pericytes, which, under injury conditions, can transdifferentiate into fibrosis-promoting, collagen- producing myofibroblasts, thus linking EPO deficiency to kidney fibrogenesis. The major regulator of EPO synthesis in the kidney is hypoxia-inducible factor (HIF)-2, a heterodimeric transcription factor that consists of an oxygen-regulated alpha-subunit and a constitutively expressed beta-subunit. HIF-2 activity is controlled by 2-oxoglutarate-dependent dioxygenases, which function as the oxygen sensors of the HIF pathway. Despite the significant advances in understanding oxygen-dependent regulation of EPO transcription, relatively little is known about the molecular identity of EPO- competent renal interstitial cells and the molecular mechanisms that lead to EPO-deficiency associated with CKD. Under Aim 1 of this exploratory grant, we use single-cell RNA sequencing in rats to characterize the molecular signatures and pathways that inform about EPO competence of renal interstitial perivascular cells in normal kidneys and in a model of chronic kidney injury and inflammation induced by adenine. These studies aim to identify and validate molecular markers and pathways that differentiate renal interstitial cells with EPO-producing capacity from cells that do not produce EPO. Under Aim 2, we leverage high-definition spatial transcriptomics in mice to map EPO and associated HIF-induced transcriptomic responses in healthy and injured kidneys.

NIH Research Projects · FY 2026 · 2026-02

Project Summary/Abstract - The All of Us Research Program’s overarching goal is to transform our understanding of the factors that contribute to health and disease, and ultimately, to leverage this understanding to inform how we prevent and treat disease. The All of Us Data and Research Center (DRC) supports operationalizing this vision, serving as a hub for robust data infrastructure and facilitative support of researchers.

NIH Research Projects · FY 2026 · 2026-01

PROJECT SUMMARY The mission of our laboratory is to pursue answers to essential questions in the field vascular aging that will advance our basic understanding and translate into more effective treatments to optimize human vascular healthspan. The central thesis of this project is that endothelial cells differentiated from hiPSCs, obtained from a diverse group of healthy adults and those with vascular contributions to cognitive impairment and dementia (VCID), can be leveraged to study endothelial aging in dementia. Using a computational model to identify biosignatures that predict endothelial cell aging, we will leverage this information to probe mechanisms relevant to dementia. Our research bridges the fields of vascular biology, stem cell biology, epigenetic clocks, multi -omics, and computational modeling to close the gap in the availability of models for the study of endothelial aging in dementia. There is a tremendous opportunity to address outstanding questions in this field using the novel human induced PlurIPotent stem cell-endothELIal cell model of aging for the study of vascular coNtributIoNs to coGnitive impairment and dementia (PIPELINING) described in this application. We will (1) passage human induced pluripotent stem cells differentiated to endothelial cells (hiPSC-ECs) and identify aging endpoints modeled in vitro (mitochondrial function, senescence, and angiogenesis). (2) A computational multi-scale model will be developed to predict the aging endpoints using multi -omic biosignatures for each human donor and passage. (3) Biosignature covariates judged to be critical contributors to the PIPELINING model will be selected for further mechanistic study. Achievement of the PIPELINING model would represent a significant advance in the application of contemporary technologies (iPSCs, epigenetic clocks, -omics, computational multi-scale modeling) to VCID.

NIH Research Projects · FY 2025 · 2025-12

ABSTRACT The overall goal of this work is to refine a novel magnetic resonance imaging (MRI) protocol to assess a cerebrovascular resistance index (CVRi), to apply this protocol in patients with Alzheimer’s disease (AD) to test fundamental hypotheses regarding how CVRi is altered in the setting of elevated amyloid-beta () plaque retention, and to assess how CVRi adjusts following pharmacological reduction of cerebral . Findings are intended to serve as a necessary prerequisite for a larger, longitudinal study that will assess how CVRi may help to triage patients for emerging anti-amyloid therapies based on personalized signatures of parenchymal health. More specifically, accumulation of cerebral  in the arterial vessel walls of patients with AD can reduce vasoreactivity and increase cerebrovascular resistance, and this effect can be assessed using the CVRi defined as the ratio of the mean arterial blood pressure (MAP; mmHg) and cerebral blood flow (CBF; ml blood/100g tissue/min). CVRi has been reported to be directly related to  accumulation in the setting of AD and partly reflects vasotoxicity, vasoconstriction, and decreased response to changes in blood pressure. Furthermore, heterogeneous distribution of  can result in variable vascular resistance and capillary blood transit time heterogeneity, which our lab has shown in other populations to alter oxygen extraction at the tissue level. I have shown that it is possible to non-invasively measure altered capillary transit times by modeling arterial, tissue, and venous blood arrival on non-invasive arterial spin labeling MRI. This method has primarily been applied in patients with cerebrovascular diseases, however, in preliminary data provided here I provide evidence that vascular transit dynamics are also altered in the setting of  accumulation, elevated vascular resistance, and neurodegeneration. This issue is fundamental, as recently approved anti-amyloid therapies alter vascular dynamics and can lead to extravasation events, such as cerebral microbleeds. As such, it is becoming even more relevant to develop an understanding of how  alters vascular health and whether measures of vascular health have relevance for portending cerebral microbleeds, which occur in a significant group of treated patients. Here, I propose to refine methods for assessing the CVRi non-invasively in vivo with MRI, and to pair this assessment with our established measures of vascular transit to better characterize these relationships in patients with AD before and after pharmacological manipulation of cerebral  The study will also be overseen by mentors with complementary expertise in imaging science, cognitive neurology, amyloid angiopathy, neuroradiology, and statistics with an ongoing collaboration, and will leverage recruitment and resources available from an ongoing longitudinal neuroimaging study of anti-amyloid treatments.

NIH Research Projects · FY 2025 · 2025-12

PROJECT SUMMARY The goal of this work is to use non-invasive quantitative neuroimaging methods to test hypotheses regarding cerebral oxygen utilization in patients with sickle cell disease (SCD) undergoing current standard treatments as well as emerging curative and disease-modifying treatments. Completion will improve our understanding of neurological injury in anemia, which is critical for development of biomarkers that can be used to triage patients for therapies based on personalized risk profiles as well as evaluate the impact of these therapies on established indicators of brain health. More specifically, while cerebral oxygen delivery depends on the cerebral blood flow (CBF; ml blood/100g tissue/minute) and blood oxygen content, it is becoming increasingly recognized that blood capillary transit time itself can also influence tissue oxygen extraction. In individuals with anemia where accelerated capillary flow velocities may be present as a result of hyperemia and cerebral autoregulation, reduced arterial-to-venous transit time (AVTT) can lead to reduced times for tissue oxygen offloading. Compelling evidence has been provided for such heterogeneous capillary flow underlying abnormal oxygen delivery in multiple conditions including expansion of infarcts in acute ischemic stroke, traumatic brain injury, and Alzheimer's disease1. Despite evidence of increased risk for cerebral vasculopathies and stroke, the mechanisms by which these occur is not fully understood. In SCD, we have observed that rapid arterial-to- venous transit, visible on arterial spin labeling (ASL) CBF-weighted MRI, is present in more than 50% of adults and children2, 3. Importantly, we have observed that rapid arterial-to-venous transit is associated with reduced oxygen metabolism 2, suggesting that these transit times may provide a biomarker of cerebral ischemia in individuals with SCA who have greater than a 50% risk of cerebral infarcts by age 30 years4, though less than 16% show conventional stroke risk factors. In SCD, decreased AVTT can play a role in the breakdown of the blood-brain barrier (BBB) through increased shearing forces along the vascular endothelium, and further potentiate vaso-occulsive crises. Here, we propose to utilize noninvasive neuroimaging methods to assess hemodynamic changes such as AVTT in SCD across a variety of hemoglobin-altering therapies to provide quantifiable metrics of expected improvement to triage patients for new or more aggressive therapies. Furthermore, this project aims to evaluate how rapid arterial-to-venous transit times are related to BBB permeability, and overall brain health. In Aim (1), we hypothesize that in adults with SCD, there is a linear reduction in cerebral blood flow and arterial-to-venous flow velocity for treatment-induced increases in Hb. In Aim (2) of this study, we hypothesize that there is an inverse relationship between cerebral arterio-venous transit times and circulating markers of BBB impairment.

NSF Awards · FY 2025 · 2025-10

The growing use of artificial intelligence in healthcare and medical research has created a difficult challenge: researchers need to share their computer models to advance scientific discovery, but these models can reveal private information about the patients whose data was used to create them. Organizations are often reluctant to share their computer models because of privacy risks, even though withholding these models prevents broader societal benefits from medical research. This creates a barrier to scientific collaboration that could otherwise lead to better treatments, improved public health outcomes, and medical breakthroughs. This project addresses this challenge by developing methods that allow organizations to safely share models trained on sensitive patient data without compromising individual privacy. Proposed research will result in new techniques for auditing models, certifying their privacy guarantees, and providing actionable tools to fix any identified issues. This work serves the national interest by advancing medical research and scientific discovery, enhancing national health and prosperity through improved healthcare technologies, supporting American competitiveness in artificial intelligence innovation, and enabling secure collaboration while protecting personal privacy rights. This project develops an end-to-end framework for privacy-preserving sharing of machine learning models trained on sensitive data. Despite growing interest in sharing models rather than raw data, machine learning models remain vulnerable to privacy attacks, such as membership inference attacks, which can reveal whether an individual's data was used during training. The research activities include four technical components. First, the project will evaluate the privacy properties of shared models by subjecting them to existing and newly tailored privacy attacks, establishing a foundational understanding of their vulnerabilities. Second, the team will develop formal privacy guarantees using methods like differential privacy and establish privacy-utility tradeoffs, creating privacy certificates for machine learning models that may include legal and usage constraints. Third, the project will design explainable auditing tools and privacy patching mechanisms such as machine unlearning to help developers mitigate risks without compromising model utility. Fourth, the research will build user-friendly tools to deploy these methods, focusing on real-world applicability in healthcare and biomedical research. The project will introduce a novel privacy-risk scoring system, enabling developers and regulators to assess the privacy risks associated with a given model. Unlike existing point solutions, this comprehensive framework integrates auditing, certification, and remediation into a unified system. Results will be disseminated through tools, publications, and educational modules to support broad adoption and training. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Candidate: Kevin P. Seitz MD, MSc is an Instructor in Medicine and, by the time of this award, will be an Assistant Professor in the Division of Allergy, Pulmonary, and Critical Care Medicine at Vanderbilt. Dr. Seitz has a strong background in randomized trials among critically ill adults. His long-term plan is to be an independent physician-scientist and a leader in randomized trials of complex interventions in the ICU. During this career development award, he will lead a multicenter trial and develop the expertise in implementation science needed to optimize adherence during pragmatic trials of complex interventions in the ICU. Research Project: Every year, millions of adults in the United States receive invasive mechanical ventilation in ICUs, with a high risk of mortality. When using a mechanical ventilator, clinicians must choose from ventilator modes that control the tidal volume (volume control), the inspiratory pressure (pressure control), or a dual-control of volume and pressure using adaptive algorithms (adaptive pressure control). Data to inform the choice of mode are limited, and arbitrary variation in current practice may be harming patients. A multi-center trial is needed to understand the effects of ventilator mode on clinical outcomes. A pragmatic trial embedded in clinical care is appropriate for this goal. Ventilator mode use is a complex, multi-disciplinary, longitudinal intervention. Implementation science provides tools to identify and mitigate barriers to adherence for complex interventions in clinical care across varied settings that are well-suited to optimizing adherence to the assigned ventilator mode in a pragmatic trial. The Specific Aims of the proposed research are: Aim 1) Conduct the Mode Of ventilation During critical illnEss at Multiple centers (MODEM) trial, a 4,785-patient randomized cluster- crossover trial of critically ill adults testing the hypothesis that adaptive pressure control will increase the number of days alive and free of mechanical ventilation compared with volume control or pressure control. And Aim 2) Apply mixed methods to identify and intervene upon contextual factors that affect the adherence to the treatment group assignment in the MODEM trial, testing the hypothesis that this approach will result in at least 90% fidelity to assigned treatment in a pragmatic, multicenter trial of a complex intervention. Career Development: Dr. Seitz’s plan integrates coursework, experiential learning, and training with mentors to: 1) become expert in designing and leading comparative effectiveness trials embedded in clinical ICU care, 2) develop expertise in implementation science methods and proficiency in qualitative methods to improve the conduct of pragmatic trials, and 3) develop leadership skills to lead large, multi-center clinical trials. Environment: As a supportive and well-resourced institution with international leaders in clinical trials, critical care, human subjects protection, implementation science, bioinformatics, and biostatistics, Vanderbilt is the ideal environment to foster Dr. Seitz’s development into a national leader in trials of complex interventions.

NIH Research Projects · FY 2025 · 2025-09

Debra Dixon, MD, MS is an Instructor at Vanderbilt University Medical Center. Her goal is to lead a research program focused on reducing heart failure (HF) incidence and mortality as an expert in intervention design, evaluation, and implementation. This application details the complementary career development and research activities foundational to Dr. Dixon’s successful transition to an independent investigator. With the primary mentorship of Deepak Gupta, MD, MSCI, Dr. Dixon will acquire new expertise in 4 domains: (1) conduct of clinical trials, (2) community engaged research (3) qualitative methods, and (4) intervention design and adaptation. Black individuals, particularly those with low socioeconomic status (SES), experience disproportionately higher rates of incident HF. Suboptimal risk factor management in Black individuals with low SES contributes to this difference. In a predominantly Black population with low SES in the Southern Community Cohort Study (SCCS), we demonstrated depressive symptoms and hypertension (HTN) were highly prevalent and independently associated with greater HF risk. Dr. Dixon demonstrated 1) depressive symptoms partially mediated the association between SES and incident HF and 2) the risk of incident HF associated with greater depressive symptoms was attenuated among individuals using anti-depressant medications. Thus, both depressive symptoms and HTN may be modifiable HF risk factors. Yet, rates of treatment and control for depressive symptoms and HTN are low in Black individuals with low SES, raising the need for novel approaches to optimize management. Socio-culturally informed approaches to treatment are guideline recommended and can improve treatment uptake and adherence. Furthermore, mobile health technology can reduce barriers to accessing effective interventions that support self-management. Emerging data indicate mindfulness-based interventions (MBI) not only address depressive symptoms, but also may improve HTN control. App-based MBI (MBI-app) are available but have not been adapted to be culturally relevant for Black individuals with low SES and for management of depressive symptoms and HTN. Thus, this project aims to: 1) characterize socio-culturally informed approaches to treat depressive symptoms and HTN, 2) adapt an MBI-app using a community engaged approach, and 3) evaluate the feasibility and acceptability of the MBI-app and randomized trial protocol for management of depressive symptoms and HTN in Black individuals with low SES. Dr. Dixon will leverage Vanderbilt’s extensive resources and her mentorship team’s complementary expertise to execute her career development plan and research aims. This study will inform future R01s evaluating treatment plan development using a socio-cultural lens and the effect of an MBI-app on HF risk factor management. Through this award, Dr. Dixon will develop a unique combination of expertise in intervention design, adaptation, and implementation and prepare to be an independent clinical investigator focused on reducing the burden of HF and improving public health.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY The objectives of this K08 proposal are twofold: 1) development of a specific skillset that will facilitate transition to an independent clinician scientist focused on mechanisms driving pulmonary vascular remodeling in PAH and 2) investigate a novel mechanism of apoptosis resistance in pulmonary arterial smooth muscle cells (PASMCs). Incorporating hands on laboratory experience, enrollment in didactic course work, and activities to enhance career development, Dr. Niedermeyer and her mentors, Dr. Larissa Shimoda and Dr. Mahendra Damarla, have designed a 5-year training plan providing the research and career skills needed to transition to an independent investigator. Pulmonary arterial hypertension (PAH) remains a disease of high morbidity and mortality with a 3-yr survival of only 55% in high-risk patients despite available therapies, and there are no current therapies which target the underlying pathobiology driving pulmonary vascular remodeling. Extensive work exploring underlying mechanisms driving apoptosis resistance in other diseases has shed light on the cell membrane protein aquaporin 1 (AQP1). Our lab was the first to show AQP1 protein is present in PASMCs28 and significantly upregulated in PASMCs isolated from the Sugen-Hypoxia (SuHx) PH model. Furthermore, we found SuHx PASMCs are resistant to apoptosis and suppressing AQP1 restores apoptosis susceptibility. The exact role of AQP1 in the development of apoptosis resistance remains unclear, but I have substantial evidence to indicate it may be via a direct interaction with the pro-apoptotic enzyme caspase-3 (casp3). Using proximity-based biotinylation assays, I established a novel interaction between AQP1 and caspase-3. Based on preliminary data, I hypothesize that in PASMCs with increased and/or mutant AQP1, binding of pro-casp3 to AQP1 reduces the amount of activatable casp3, conferring apoptosis resistance and driving vascular remodeling in PH. To test this hypothesis, I propose three specific aims: 1) determine the structural and functional components of casp3 that regulate binding to AQP1, 2) investigate features of AQP1 that influence casp3 binding and activation, and 3) determine whether modulating AQP1 abundance and/or casp3 binding alters vascular remodeling and PH. I will utilize a combination of techniques including unique protein constructs in complementary binding assays, measurements of casp3 activity in total cell lysates and subcellular compartments paired with advanced live cell imaging, and a novel transgenic murine model which allows for conditional knockout of AQP1 in PASMCs. Completing these aims will provide a rigorous training program for Dr. Niedermeyer and uncover mechanisms of PASMC apoptosis resistance that could provide potential therapeutic targets.

NIH Research Projects · FY 2025 · 2025-09

Our mechanistic understanding of delirium after cardiac surgery (CS-Delirium) is limited and few pharmacologic treatments exist. Acute kidney injury (AKI) is a strong risk factor for delirium. However, in the cardiac surgery patient population, the incidence of AKI-associated delirium (CS-AKI-Delirium) and the risk factors for CS-AKI-Delirium are unknown. Our preliminary data suggest that the CS-AKI-Delirium subgroup accounts for 55% of CS-Delirium patients, develops a unique intraoperative cytokine and chemokine profile, and develops higher intraoperative endothelial activation than the non-AKI CS-Delirium subgroup. Further, our data suggest that an association between higher intraoperative endothelial activation and a greater odds of delirium exists only in the CS-AKI-Delirium subgroup. We hypothesize that CS-AKI and CS-Delirium are mechanistically linked by systemic inflammation and endothelial activation in the CS-AKI-Delirium subgroup. If data supporting a linked mechanism were generated, these data would rapidly advance the study of CS- Delirium by facilitating the translations of a portion of CS-AKI mechanistic knowledge and therapeutic targets to CS-AKI-Delirium. We propose the first prospective study of CS-AKI-Delirium, involving 300 adults undergoing on-pump coronary artery bypass surgery. This study will determine the incidence and clinical phenotype of CS- AKI-Delirium (Aim 1), delineate signaling pathways composed of intracellular and extracellular mediators of inflammation and endothelial activation associated with CS-Delirium and CS-AKI-Delirium specifically (Aim 2), and test the hypothesis that higher endogenous high-density lipoprotein capacity to suppress endothelial activation is associated with less CS-AKI and less CS-AKI-Delirium (Aim 3). During this study, inflammatory signaling pathways will be characterized using comprehensive and complementary methods including high throughput biomarker analysis of plasma collected before and after surgery, and total RNA sequencing, RNA in situ hybridization, and immunohistochemical staining of ascending aortic tissue collected during surgery. Our research team has over 70 years of combined experience identifying and deeply characterizing such pathways. The innovation of this proposed study is the recognition that CS-AKI and CS-Delirium may not be independent postoperative co-morbidities, but instead may be mechanistically linked disease states in a large subset of CS-Delirium patients. Data generated in this study about the incidence of CS-AKI-Delirium and the statistical tool developed during this study to identify this patient subgroup will facilitate designing and powering future CS-AKI therapeutics trials to add CS-AKI-Delirium as a secondary endpoint if scientifically justified. This single change in scientific thinking and addition of our clinical study data to the field of CS-Delirium could increase the number of CS-Delirium therapeutic trials many-fold in a highly-cost effective manner. Our research team has over 25 years of combined experience performing prospective observational studies of AKI and delirium at the proposed study site and is highly qualified to complete this proposed study.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Cirrhotic cardiomyopathy (CCM) is a recognized but understudied and not well understood complication of cirrhosis. CCM is defined as subclinical diastolic or systolic dysfunction by echocardiography in patients with cirrhosis in the absence of overt coronary artery, valvular, or pericardial disease. Drs. Izzy (PI) and VanWagner (co-I) cofounded the multidisciplinary CCM consortium in 2018 that established diagnostic criteria for CCM in 2020 incorporating contemporary echocardiographic methods. Since then, mostly retrospective, and relatively small studies applying these criteria suggest CCM may be common affecting 24-45% of patients with cirrhosis and associated with adverse hepatic and cardiac outcomes and ~2-to 9-fold greater risk of death. Further, the pathophysiology of CCM in humans is not well understood, but preclinical evidence from our group and others implicates bile acids (BA) as a causal and potentially modifiable driver of CCM. Appreciating limitations of retrospective human and preclinical studies, the estimates for CCM prevalence and prognosis are concerning and motivate deeper and larger prospective investigation in humans to address unanswered questions highly relevant to clinical care and those of biologic importance. These include 1) what are the associations between CCM and all-cause mortality, cirrhosis-related outcomes, and adverse cardiac events, 2) what clinical factors associate with presence of CCM, and 3) do BA associate with adverse cardiac remodeling and features of CCM? Therefore, in this study we will conduct the first US based prospective investigation of CCM in humans with decompensated cirrhosis enrolled from two high-volume hepatology and liver transplant (LT) centers. Our study design will address limitations of prior studies by including a) larger sample size inclusive of both eligible and ineligible patients for LT, b) serial assessment every 6 months of clinical, laboratory, and echocardiographic data, and c) longitudinal ascertainment of hepatic, cardiac, and mortality outcomes. Our specific aims are to: 1) test the hypothesis that addition of CCM status to MELD-3.0 improves accuracy of risk stratification for 1-year all-cause mortality, 2) define clinical risk factors associated with CCM, and 3) test the hypotheses that higher circulating levels of total BA and altered composition of BA (ratio of conjugated primary BA [cholic and chenodeoxycholic acids] to secondary BA [ursodeoxycholic acid]) associate with the cardiac alterations seen in CCM. By providing foundational prospective data needed to advance the field of CCM, our study will exert a powerful and enduring scientific and clinical impact. We will refine clinical risk stratification for adverse outcomes in patients with end-stage liver disease and inform clinical screening and surveillance for CCM. Establishing a CCM risk profile and a BA-myocardial link are critical to designing future trials testing BA modifying therapies specific for CCM, particularly as pharmacotherapy for CCM are lacking. Our team of experts in hepatology, BA, cardiology, epidemiology, and biostatistics has the requisite resources to successfully complete the study, which will transform understanding of and the clinical approach to CCM.

NIH Research Projects · FY 2025 · 2025-09

Abstract: Scaling Up Task-Shifted Epilepsy Care (SHIFT) has the potential to benefit half of the world’s people with epilepsy (PWE) - those who are currently untreated, many of whom are undiagnosed. As many as 60%-95% of people with epilepsy in Africa are undiagnosed and/or untreated, and rates of undiagnosed and untreated epilepsy vary across every country in the world. The 2022 Intersectoral Global Action Plan on Epilepsy (IGAP) established goals by 2031 among the world’s people with epilepsy (PWE): (1) 90% will know their diagnosis, (2) 80% will have access to anti-seizure medications (ASMs), and (3) 70% will achieve seizure control. In LMICs where physician shortages, lack of neurodiagnostic services, high epilepsy prevalence and high treatment gaps co-exist, IGAP suggests that task-shifting epilepsy care to community health workers (CHWs) could reduce the number of untreated people with epilepsy. A recent 60-site non-inferiority cluster randomized clinical trial (RCT) (BRIDGE-1; R01 NS113171) has documented that epilepsy outcomes among those treated by epilepsy-trained CHWs were not inferior to epilepsy outcomes among those treated by physicians, and that malnutrition is a major contributor to mortality among children with epilepsy. Task-shifted malnutrition care to CHWs is also promising based upon a recently completed clinical trial. We have developed, validated and implemented community-based epilepsy screening, and implemented curricula for training community health workers (CHWs) in epilepsy and in malnutrition task-shifted care. In SHIFT we propose to integrate task-shifted epilepsy care and task-shifted malnutrition care in five communities with populations of over 100,000, each community with a different dominant local language. We will train local community health volunteers (CHVs) in screening for epilepsy and for malnutrition, implement door-to-door screening, and refer those who screen positive for epilepsy and/or malnutrition to epilepsy- and malnutrition-trained CHWs for diagnosis and treatment at community-based primary healthcare centers, under supervision by physicians. Previously untreated PWE, including children with epilepsy with and without malnutrition, will be followed for 24 months to determine outcomes including epilepsy- and malnutrition-associated mortality. The implementation of integrated task-shifted screening, diagnosis and care for epilepsy and for malnutrition will be studied using the RE-AIM framework, and the cost-effectiveness of integrating epilepsy and malnutrition task-shifted care will be determined. SHIFT outcomes will include an online task-shifted epilepsy and malnutrition toolkit that will include: (a) an integrated epilepsy and malnutrition task-shifted protocol; (b) an online flipped classroom epilepsy and malnutrition training program for CHWs; (c) REDCap-based health record systems for coordinating task-shifted care, combined with (d) statistical software to help health authorities determine local treatment needs and epilepsy prevalence needed to plan task-shifted care at the state and local levels.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY / ABSTRACT Each year, 2-3 million critically ill adults in the United States receive invasive mechanical ventilation, of whom 30-40% die before hospital discharge. Approaches to patient care that decrease mortality for mechanically ventilated adults are urgently needed. For all mechanically ventilated adults, the fraction of inspired oxygen (FiO2) is titrated to maintain arterial oxygen saturation (SpO2). Using a higher SpO2 target (96-100%) provides a margin of safety against hypoxemia, but increases exposure to excess FiO2, hyperoxemia, and tissue hyperoxia. Using a lower SpO2 target (88-92%) minimizes these risks but may increase exposure to hypoxemia and hypoxia. We conducted a randomized trial of higher vs lower SpO2 targets among 2,541 mechanically ventilated critically ill adults (Semler, NEJM 2022). In addition to reporting the effect of a higher vs lower SpO2 target on mortality among all patients in the trial population (“average treatment effect”), we analyzed the trial using machine learning methods to derive a statistical model estimating the effect of a higher vs lower SpO2 target on mortality for each individual patient (“personalized SpO2 target”) (Buell, JAMA 2024). When we validated these personalized SpO2 targets in the dataset from a second randomized trial (Mackle, NEJM 2020), we found that the model accurately identified which individual patients would benefit from receipt of a higher vs lower SpO2 target. We calculated that, had each patient received the personalized SpO2 target predicted by the statistical model to be best for him or her, overall mortality would have been reduced by 6.4%. Before the use of personalized SpO2 targets can be widely implemented into clinical care, the key next step is to prospectively evaluate whether using the personalized SpO2 targets decreases mortality for mechanically ventilated critically ill adults, compared to usual care. The EXamination of PeRsonalizEd SpO2 TargetS (EXPRESS) randomized trial proposed in this application will compare use of a personalized SpO2 target vs usual care with regard to 28-day in-hospital mortality among 3,000 mechanically ventilated patients. The trial will address two specific aims. Aim 1 will determine whether use of a personalized SpO2 target decreases mortality compared with usual care. Aim 2 will evaluate for differential treatment effects across patient subgroups to test the hypothesis that the effect of a personalized SpO2 target vs usual care on 28-day mortality will be greater for patients with a greater predicted benefit from use of the personalized SpO2 target (Aim 2a), will be greater for patients with greater medical complexity and severity of illness (Aim 2b), and will not differ by patients’ age, sex, race/ethnicity, or socioeconomic status (Aim 2c). The results of the trial will inform care for millions of critically ill patients each year. The methodological innovation of using machine learning analyses of randomized trial data to deliver care that is both evidence-based and personalized has the potential to fundamentally change the way we generate and apply evidence in medicine.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY/ABSTRACT Diverticulitis is a disease marked by inflammation of diverticula in the colon. In the US, it is highly prevalent and costly, accounting for more than 2.6 million outpatient visits (combined emergency department and ambulatory clinic) and 200,000 inpatient admissions for diverticulitis at a cost of more than $2 billion. Patients can present with a wide spectrum of disease severity, from localized inflammation (uncomplicated) to frank perforation (complicated). Traditionally in the US, treatment for acute uncomplicated diverticulitis (AUD) has been antibiotic therapy. However, antibiotics can have significant side effects, both on the patient and population level. Patients can experience side effects as well as life-threatening superinfections. At the population level, inappropriate antibiotic use is the primary driver of antimicrobial resistance (AMR), a critical national and global threat. Results from recent studies conducted in Europe suggest that antibiotics may be unnecessary to treat mild acute diverticulitis. However, these trials have significant flaws and concerning trends in secondary outcomes which have limited implementation in a US population. Additionally, the US population differs fundamentally from the European population in race and ethnicity as well as the effect of socioeconomic drivers of health. A recent study cites the lack of US data as the strongest barrier to implementation. This knowledge gap – whether antibiotics improve recovery from AUD in current US clinical practice – leads to the proposal of a pilot, randomized trial of placebo versus antibiotic treatment of AUD in 100 patients with oversampling based on race and ethnicity. We aim to 1) determine differential rates of recruitment, treatment acceptance/adherence, cross-over, clinical endpoint assessment compliance and loss to follow-up at 30 days and 6 months by race and ethnicity to assess feasibility of a large scale, multicenter trial. 2) acquire preliminary data regarding the effects of a placebo compared to antibiotics for AUD on a range of key patient-centric efficacy and safety endpoints These results will inform the design, sample size, and endpoint selection for the subsequent efficacy trial that will generate critical evidence to assess the role of antibiotics in the treatment of AUD. This proposal is an outstanding fit for PAS-23-086 (Small R01s for Clinical Trials Targeting Diseases within the Mission of NIDDK). This small, short-term clinical trial in humans will acquire preliminary data regarding the effects of non-antibiotic management of acute, uncomplicated diverticulitis, as well as feasibility data related to recruitment and retention, and study conduct. Completion of this award will lay the foundation for larger, multicenter clinical trials to further our understanding of the optimal role of antibiotics in the management of acute uncomplicated diverticulitis.

NIH Research Projects · FY 2025 · 2025-09

Colorectal cancer (CRC) arises mostly from pre-existing colorectal adenoma (CRA). Removal of these precancerous lesions significantly reduces CRC incidence. However, ~30% of CRA patients will develop metachronous (recurrent) adenomas after their initial polypectomy. Yet, understanding of the genetic basis of CRA and recurrence, and identification of therapeutic drugs are currently very limited. Addressing the gap in genetic studies of CRA, we have recently established genome-wide association studies (GWAS) of ~8,000 CRA cases from European Americans (EA) and African Americans (AA) from the Vanderbilt DNA BioBank (BioVU). Furthermore, we have recently established Vanderbilt Colonoscopy Cohort of CRA cases after polypectomy (N=76,664), though a large-scale analysis of electronic health records (EHRs) and pathology reports. In this application, we propose to extend our efforts to establish the first large GWAS of EA and AA leveraging unique resources primarily from the BioVU, the Mass General Brigham (MGB) Biobank and All of Us, and conduct transcriptome-wide association studies (TWAS), methylome-wide association studies (MeWAS) and proteome-wide association studies (PWAS) to identify risk variants, DNA methylations, genes and proteins for CRA and recurrence. Specific aims are: Aim 1: Conduct GWAS, MeWAS, TWAS and PWAS among 25,000 CRA cases (~9,000 recurrence) and 140,000 controls in EA and 6,500 CRA cases (~2,000 recurrence) and 47,000 controls in AA participants. Existing data on colon or adenoma tissue DNA methylation, RNA-seq, and proteomics from EA (n=1,538) and from AA (n=465) from our parent studies, will be used to build racial-specific prediction models for DNA methylation, alternative splicing, and alternative polyadenylation, gene and protein expression. These prediction models will be applied to the GWAS data to identify risk DNA methylations, genes and proteins, both overall and by recurrence of CRA in AA and EA, respectively. We will integrate findings from EA and AA to identify risk genes across both populations and those contributing to racial disparity. We will also perform omics-based drug analysis to identify potential therapeutic drugs for CRA recurrence. Aim 2: Identify repurposing drug candidates to reduce CRA recurrence after polypectomy: Combing Vanderbilt (N=76,664) and MGB (N=~55,000) Colonoscopy Cohorts, we have identified ~39,400 CRA patients (~30% of total CRA cases after polypectomy) with a surveillance colonoscopy at least one year after previous polypectomy (with ~31,700 CRA recurrence and ~2,600 CRC). We will build a machine learning and statistical framework upon real-world EHRs to create and compare treated and control patient groups, and systematically screen repurposable drugs to reduce CRA recurrence and/or CRC risk. Aim 3: Perform functional assays to test the efficacy of six promising drugs in both in-vitro and mouse models. Given the unique resources and methodological strengths, we anticipate that the study will have significant potential for the optimization of colorectal polyp surveillance and therapeutic intervention of CRA/CRC.

NIH Research Projects · FY 2025 · 2025-09

Project Summary/Abstract Obesity affects nearly half of the U.S. population, impacting health outcomes including diabetes, cardiovascular risk, longevity, and quality of life. While bariatric surgery such as gastric bypass stands as the most effective intervention, 65% of individuals experience persistent obesity when undergoing surgical weight loss alone. Given the wide-ranging impact of obesity on health outcomes, a critical need exists to explore the efficacy of adjuvant weight loss therapies after gastric bypass surgery. Tirzepatide (TRZ), a type of glucagon- like peptide-1 receptor agonist, shows remarkable effectiveness in medical obesity with 25% weight loss after sustained therapy. However, nearly two-thirds of patients taking medications like TRZ have mild to moderate gastrointestinal (GI) symptoms, including nausea, vomiting, and abdominal pain. These medication side-effects could be a consequence of gastroparesis via vagal stimulation of the stomach, and may represent a major driver of weight loss. Limited data exist regarding use of these newer agents, such as TRZ, in patients who have undergone gastric bypass, which disrupts vagal nerves responsible for managing food transit and gastric emptying. This is a major and timely scientific gap in understanding whether gastric bypass surgery might mitigate these GI symptoms while allowing for enhanced weight loss with adjuvant TRZ use in the post- operative period. We propose a pilot, phase II, open-label trial enrolling patients twelve months after gastric bypass with a nadir Body Mass Index ≥ 30 kg/m2. Study subjects will be randomized to either 24 weeks of TRZ or post-surgery standard of care. Our proposal consists of two aims. First, we will determine the impact of adjuvant TRZ administration on weight, total fat mass, and lean body mass in patients with a history of gastric bypass (Aim 1). Second, we aim to investigate the frequency and severity of GI discomfort associated with TRZ utilizing a validated patient reported outcome questionnaire, and we will investigate the impact of TRZ on GI motility in patients with prior Gastric Bypass (Aim 2). This proposal delineates Dr. Samuels’s career development plan, "Use of Adjuvant Anti-Obesity Medication to Enhance Surgical Weight Loss." With a robust background in caring for over 500 bariatric surgery patients, Dr. Samuels’s time on this K23 will be dedicated to developing him as a leader in clinical trials investigating multimodal treatment strategies for obesity. This career development award is critical to Dr. Samuels’s efforts to become an independently funded investigator following the completion of Dr. Samuels’s career development plan. Dr. Samuels’s mentorship team carries expertise in surgical clinical trials (Mayur B. Patel), anti-obesity pharmacotherapy trials (Kevin D. Niswender), clinical trials investigating behavioral interventions for obesity (Luke Funk), large database comparative effectiveness studies (Christianne Roumie), and pragmatic, electronic records-based clinical trials (Wesley Self). This award will position Dr. Samuels to become a leader in obesity-related clinical trials.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Common ways to measure M. tuberculosis transmission are via acquisition of Th1-skewed T-cell immunity (e.g., interferon gamma release assays; IGRA) or new TB cases. However, these measurements may oversimplify and, in some cases, entirely miss M. tuberculosis transmission. For example, a substantial minority of highly-exposed individuals have T-cell responses to M. tuberculosis antigens that are not Th1- based. In addition, subclinical or asymptomatic TB is common, but often not captured clinically. Different strains of M. tuberculosis may have evolved different solutions to optimize transmission, which may associate with distinct phenotypes. In addition, as M. tuberculosis encounters hosts with different genetic backgrounds, immune status, age, and sex, the manifestations of infection outcomes may vary, due to both bacterial and host factors. We hypothesize that M. tuberculosis transmission outcomes are affected by both bacterial and human host (contact and index case) factors. We will test our hypothesis in the well-established RePORT- Brazil cohort study of TB cases and their close contacts. There were 1,188 TB cases and 1,930 contacts enrolled in Phase 1 (2015-2021), and ~1,000 TB cases and ~2,000 contacts will be enrolled in Phase 2 (2022- 2026). We will identify M. tuberculosis bacterial genetic and phenotypic features associated with M. tuberculosis transmission outcomes, including M. tuberculosis infection, subclinical TB, and clinical TB disease through bacterial association studies and mechanistic evaluation. We will also define M. tuberculosis transmission outcomes using multi-parameter profiling of human cellular immune responses in close contacts. Clinical and epidemiologic characteristics of the close contacts and their index TB cases will also be addressed, in prediction models of M. tuberculosis transmission that also incorporate M. tuberculosis genetic and host immune factors. Findings from this study could guide the development of targeted interventions, such as diagnostics for detecting highly transmissible M. tuberculosis strains, and host-directed therapies aimed at modulating immune responses to reduce transmission risk. The results will also provide insights for optimizing public health strategies, including contact tracing and targeted preventive therapy, specifically tailored to high- transmission settings.

NIH Research Projects · FY 2025 · 2025-09

Project Summary. It is well-accepted that altered gait can precede the clinical diagnosis of cognitive impairment and is a significant risk factor for cognitive decline. Older adults with combined altered gait and cognitive changes (dual-decline) are at greater risk of developing dementia than older adults with changes in only gait or cognition and stable function. Dual-decline incidence is high, estimated to have a pooled prevalence of 10.2% of older adults, and is additionally impactful because altered gait in those with Alzheimer’s disease (AD) and related dementias (ADRD), and leads to more frequent and injurious falls and greater healthcare costs. Unfortunately, an important knowledge gap persists regarding the pathophysiological changes that link declines in gait with dementia. There is a critical need to identify underlying pathophysiological changes to improve early detection and inform interventions for the dual-decline population. The overall objective of this application is to use a systems biology approach of proteomics to understand the pathophysiological changes associated with dual decline. Recent advances in proteomics technology have contributed to many breakthroughs in disease-related biomarker discovery and in understanding the pathways contributing to increased disease risk. Plasma proteomics has identified both AD-related proteins and altered gait-related proteins in cognitively unimpaired cohorts with potentially overlapping pathways. The proteome of dual decline, however, has not yet been determined. We will leverage a deeply phenotyped cohort, the Vanderbilt Memory and Aging Project (VMAP), with plasma proteomics (Olink Explorer 3072) at study entry and repeat measures of clinical gait speed, actigraphy, and neuropsychological assessments. This study proposes both cross-sectional (Aim 1) and longitudinal methods (Aim 2) to examine the unique proteome of dual decline. In each aim, we will also investigate gait changes derived from clinically measured gait speed (clinical gait) and gait characteristics extracted from actigraphy during everyday living (free-living gait). Free- living gait differs from clinically measured gait and may provide additional novel insights into the etiology of dual decline. Analyses will then be replicated in the Baltimore Longitudinal Study on Aging and compared with dual decline proteins and pathways identified in the VMAP cohort. Discovery of a unique proteome may identify predictors and treatment targets, potentially transforming early detection and intervention strategies for aging adults with an elevated risk of functional and cognitive decline. This K76 research proposal and parallel training plan will expand upon my expertise in motor control (gait) and signal processing (free-living gait) with neuropsychological assessment, advanced statistical methods, and aging systems biology (proteomics). Accomplishing the proposed training and research project will uniquely position me as a leader and expert in the intersection of physical function and systems biology, enabling me to lead the way in developing precision detection and treatment strategies in ADRD.

NIH Research Projects · FY 2025 · 2025-09

The goal of this application is to create a new T32 mentored training program, Pediatric Cardiorespiratory Research Training Program: Childhood origins of diseases across the lifespan for Pediatrics fellows and PhD scientists who possess both the aptitude and passion to become a new generation of basic, translational, and clinical scientists. The overarching goal is to provide a nurturing mentored environment for fellows for 2 years (with an optional 3rd year) of highly rigorous research training to facilitate successful transition to a subsequent appointment as tenure track faculty. The ultimate goal is to expand the pipeline of those achieving independence as clinician-scientists. Each fellow investigator participates in workshops, may complete a Master’s program (MSCI,MPH, MSACI), and leverages VUMC societies for clinician-scientist development, and will develop and complete a mentored research project in an area of focus consistent with the missions of NHLBI. Investigation may be basic, translational, clinical, or population health. This training program will have 2 training slots per year at any given time to support fellows for a minimum of 80% protected research time for at least 2 years. There is a formal program selection process to identify the most competitive applicants. The program will provide intense scientific mentorship and personalized career development. The fellows will have access to a cadre of >26 carefully selected preceptors with sustained NIH funding coupled with successful track records of mentoring early career scholars. Each fellow will have a personalized Scholarly Oversight Committee to assist in achieving program goals, to provide independent evaluation of their progress, and to develop, advise on, and track their career development plan. Assessment of fellows includes competency-based milestone assessments. There will be equally rigorous mentor and program assessments. Key outcomes for the program include: Academic productivity (presentations, peer-review publications, grants and rates (and success) of appointment to early career academic faulty positions, and applications for initial individual K career development awards. Long-term follow-up of all fellows will be performed using FlightTracker and through personal contact. The Department Pediatrics is fully integrated into the Vanderbilt School of Medicine and Medical Center and consistently ranks in the top 10 in NIH funding. All departments, hospitals, research laboratories and core facilities reside on a single campus offering an integrated research environment for early career clinician-scientists. Our proposal is consistent with the NHLBI’s current Strategic Vision Statement.