Yale University

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY Alzheimer's disease (AD) is a neurodegenerative disease resulting in dementia and ultimately, death. No cure exists for the disease and treatments start only after symptoms are presented. Thus, early AD detection is crucial to start the treatment to slow down the progress of the disease. Olfactory dysfunction is shown to be present as a disturbed sense of smell, proposed as an early sign of neurodegenerative diseases, but also including AD. The mechanisms underlying olfactory deficits in AD remain largely unknown. Olfactory bulb (OB) and its associated piriform cortex (PCX), a region that is involved in olfactory learning, can be a key candidate for investigating early functional changes in the brain induced by AD pathology. In addition, functional and structural changes in entorhinal cortex (EC) and hippocampus (HC) can be detected years before significant clinical symptoms, and therefore, suggested as potential biomarkers for AD diagnosis. There are a close anatomical and functional associations between olfaction (OB-PCX) and memory (EC-HC) systems. OB-PCX circuit is closely connected with the EC-HC circuit and is suggested as one of the earliest regions affected by AD. Therefore, we hypothesize that progressive neurodegeneration in AD disrupts the connectivity of the olfactory circuit to the memory circuit, leading to early deficits in olfaction followed by memory impairment. Detection of structural, functional and behavioral changes related to olfactory and memory function may result in early AD detection. Our recent work to study AD progression in a rodent model and its response to therapeutic intervention serves as the basis, as well as our recent innovation in a novel functional MRI (fMRI) method which enables simultaneous imaging of the rat cerebral cortex and the olfactory bulb. The overall goal of this project is to develop neuroimaging methodologies that enable early detection of AD and olfactory function via biomarker imaging. To achieve this goal, we will longitudinally perform imaging/spectroscopic and behavioral studies on transgenic TgF344-AD and wildtype (WT) rats from early to more advanced stages of the disease (3-12 months) (Aim 1) and assess mitochondrial energy metabolism (Aim 2). We will use in vivo multi-modal MRI/MRS (at 11.7T) in conjunction with behavioral testing to characterize AD development and progression. We will specifically examine the (a) functional connectivity alterations in the olfactory networks using resting fMRI and bulbar/cortical responses by task fMRI, (b) mitochondrial energy metabolism by 31P-MRS and (c) memory and smell abilities using behavioral measurements (novel object recognition, spatial memory and olfactory tests). The characterization of AD pathology in this rat model using highly translational MRI techniques highlights the potential of this model to be used in valuable future preclinical AD research as well as its use for potential treatment evaluation.

NIH Research Projects · FY 2025 · 2024-09

Cannabis (CB) is frequently used by people with HIV (PWH) for its claimed benefits alongside antiretroviral therapy. However, the immunomodulatory impact of CB in the context of the chronic inflammation experienced among PWH is unclear. The interaction between HIV and CB in the host genome remains poorly understood. Previous studies on the epigenetic effects of HIV and CB have been limited and most studies conducted in bulk peripheral blood mononuclear cells (PBMCs), which only provides an average view of DNA methylation (DNAm) changes across various cell types. Our recent research of DNAm in CD4+ T cells isolated from PWH identified DNAm CpG sites that were linked to HIV-1 latent reservoir and a set of druggable genes, including the target for Ibalizumab, a medication for treatment resistant of HIV infection. The result underscores the value of cell specific DNAm analysis in uncovering mechanisms of HIV pathogenesis and potential therapeutic targets. Nonetheless, the combined effects of HIV infection and CB use on DNAm, particularly considering genetic variants that influence DNAm (methylation quantitative trait loci, meQTL), have yet to be fully explored. To address these gaps, we hypothesize that CB use alters DNAm in a cell type-specific manner within the HIV-infected host, with these changes potentially modulated by meQTL specific to each cell type. Our study aims to dissect the epigenomic landscape of CB and HIV interaction by conducting cell-type based genome-wide DNAm and meQTL analyses in two large cohorts of PWH, assessing their potential for druggable targets. This will involve comprehensive profiling of DNAm across five different cell types isolated from PBMCs, alongside functional validation studies both in vivo and in vitro. The functional validation involves transcriptome-wide association analyses, single-nucleus RNA and ATAC sequencing to elucidate the functional impact of specific epigenetic modifications and their relevance to drug development. In preliminary work, we employed a computational algorithm to deconvolve DNAm data to specific cell types and validated these findings through direct sequencing. This has revealed a more nuanced understanding of HIV's impact at the cellular level, identifying cell type specific DNAm sites and highlighting the unique genetic landscapes influenced by HIV across different cell populations. Furthermore, we have developed a novel algorithm, Hierarchical Bayesian Interaction model, to uncover genetically influenced DNAm at cell type level. These preliminary findings provide the framework for this proposed project. Our team's established expertise in epigenomics among PWH, positions us uniquely to achieve our goal. Successful completion of this study promises to deliver unprecedented insights into the mechanisms of CB's immunomodulatory effects in HIV, paving the way for novel therapeutic strategies through targeted drug repositioning.

NIH Research Projects · FY 2025 · 2024-09

Psychosocial stress profoundly affects neuroendocrine (hypothalamic-pituitary-adrenal, HPA) and immune function in both central and peripheral cells. People living with HIV (PLWH) show heightened distress and increased inflammatory burden, leading to greater complex morbidity (CM) including high prevalence of cannabis use disorder (CUD) and major depressive disorders (MDD). However, the mechanisms governing stress-immune interactions in PLWH, and their associated distress and drug use are not well understood. Notably, MDD and CUD each disrupts HPA-immune responses but their effects on stress-related HPA-immune function and homeostasis in PLWH are not known. Epigenetic aberrant of the “stress genome” has been shown to disrupt HPA function and stress adaptation. In the HIV infected host genome, the epigenome landscape is profoundly altered by HIV-1, including genes that are part of the stress genome, highlighting the interactive role of the stress and immune genomes in development of CM in PLWH. But the epigenetically regulated gene expression of stress-immune effects in PLWH with MDD and CUD has not been studied. This proposal aims to address these research gaps using a powerful and novel cross-diagnostic approach with multiple complementary approaches to examine the overarching hypothesis that PLWH+CM exhibit impaired stress-related HPA and HPA- immune function due to alterations in epigenetic mechanisms, and that these stress-related HPA- immune and related epigenetic maladaptations predict distress, craving and substance use symptoms underlying CM in PLWH. In this study, we defined complex morbidity as PLWH with CUD and MDD. This hypothesis will be tested using a combined human experimental approach with prospective longitudinal assessment of daily distress, and substance use symptoms as well as assessment of chronic stress (C-stress), social determinants of health, and resilience in the experimental cohort with corroboration in a population-based analysis of a well-established large cohort of PLWH. We aim to 1) Determine HPA and immune response to acute stress among 40 healthy controls (HC), 40 PLWH, and 40PLWH+CM by experimentally stress-challenging all participants and measure HPA-immune for each participant; 2) Identify cell-type epigenetic regulation of HPA- immune response to acute stress in 3 groups by profiling the DNA methylome (DNAm) and transcriptome at 3 timepoints for each subject in bulk blood cells following the deconvolution of DNAm and RNA expression to five major cell types. snRNA-seq and snATAC-seq will be conducted in a subset of samples; 3) Link acute stress HPA-immune dysregulation to retrospective stress and prospective future daily subjective distress and CM symptoms in the real world by using ecological momentary assessment. We will explore demographic and individual differences in psychosocial stress, acute stress-immune response and identify potential biomarkers of PLWH+CM. If successful, this project will not only identify new psychobiological-epigenomic mechanisms for PLWH+CM but also identify stress biomarkers in PLWH to predict who is most susceptible to complex morbidities.

NIH Research Projects · FY 2024 · 2024-09

Project Summary/Abstract In development, the embryo generates many cell types with distinct gene expression programs, leading to heterogeneity across cells. In cancer, mutation generates heterogeneity, with a growing recognition that non- genetic (epigenetic) mechanisms contribute to tumor heterogeneity and treatment failure. The ability to take the same genetic template and form different cell states, exhibiting cell-to-cell variation in gene expression and behavior, is fundamental to many cell systems across problems in human health including stem cells, cancer, and immune cell function. Yet, the mechanisms by which cell systems encode heterogeneity in gene expression are unclear. Pluripotent embryonic stem cells give rise to all the cells of the adult mammal, and primary embryonic stem cells are genetically stable in culture, making them an ideal system for studying the emergence of non-genetic heterogeneity in cell systems. Cell-to-cell variation in gene expression that arises in the absence of environmental signals has previously been termed `noise', or attributed to stochastic processes of gene expression. However, gene expression heterogeneity is reproducible, suggesting regulation. The goal of this proposal is to identify regulatory mechanisms by which the genome encodes non-genetic heterogeneity in cell systems. We will use embryonic stem cells as a model system for gene expression heterogeneity. First, we will identify transcription factor pairs whose combined activity at enhancers leads to transcriptional heterogeneity of the regulated gene. In order for heterogeneity to result in forming distinct states with the potential to prime stem cells into different lineages, heterogeneity must be heritable. Second, using a modified Luria-Delbruck fluctuation analysis, we will identify memory loci capable of heritable transmission of non-genetic heterogeneity across cell generations. Motifs such as autoregulation, whereby a gene's product can regulate its own production, may contribute to the formation of different cell states and therefore to heterogeneity across a cell population. Third, we will manipulate a single factor within or outside of an autoregulatory loop to determine how it impacts heterogeneity. To accomplish these goals, we will leverage an assay we have developed which allows the identification of actively transcribed regulatory regions and genes in small subsets of cells. Completion of these goals will address longstanding questions about the origins of heterogeneity in cell systems and will advance a systems level approach for understanding cell state. If successful, the proposal may unlock future studies applying similar approaches to identify non-genetic drivers of tumor heterogeneity and treatment failure. Therapeutic targeting of these mechanisms may unlock new treatment strategies for cancer.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY The medical and functional needs of nursing home residents impose a differential risk of morbidity and mortality due to severe weather events, including hurricanes. A potential explanation for the increases observed in adverse resident outcomes after hurricane exposure is inadequate compliance by nursing home facilities to federal emergency preparedness standards; however, prior research has not rigorously evaluated this association. Furthermore, nursing home characteristics, such as private versus not-for-profit or public ownership, are known to affect resident outcomes, but the impact of ownership on emergency preparedness and post-disaster outcomes is unknown. To address these knowledge gaps, we propose a retrospective cohort study using data from the Centers for Medicare and Medicaid Services (CMS) and National Oceanic and Atmospheric Institute (NOAA) to evaluate facility-level and resident outcomes as a function of exposure to Hurricane Michael (2018) and administrative emergency preparedness. Within our analytic sample of 1,423 nursing homes, we have classified 317 nursing homes as exposed to Hurricane Michael. Evaluating the post- disaster outcomes of 30-day all-cause mortality (primary), 30-day hospitalization, and 120-day functional decline, we will use predictive modeling to identify which of the 250 federal emergency preparedness deficiencies identified in CMS Life Safety Code inspections are most predictive of the facility-level rate of adverse post-disaster outcomes (Aim 1). We hypothesize that deficiencies pertaining to evacuation and sheltering preparedness will be included within this subset of “critical deficiencies.” In Aims 2 and 3, we will construct a dichotomous measure of noncompliance from the subset of critical deficiencies identified in Aim 1 (i.e., a nursing home with ≥1 critical deficiencies will be classified as noncompliant). In Aim 2, we will evaluate whether the impact of hurricane exposure on the resident-level likelihood of adverse post-disaster outcomes is modified by noncompliance. We hypothesize that noncompliance will confer an increased risk of adverse post- disaster resident outcomes. Lastly, we will assess whether private nursing home ownership is associated with the resident-level likelihood of adverse post-disaster outcomes, and whether this potential association is mediated by noncompliance (Aim 3). We hypothesize that residents from privately owned nursing homes will have worse post-disaster outcomes, and that these associations will be mediated by noncompliance. Our integration of geospatial data with administrative health and compliance data positions us to provide the first empirical assessment of the relative importance of individual federal emergency preparedness standards and the mechanisms by which they affect nursing home resident outcomes. The proposed research responds to federal priorities regarding the need to improve emergency preparedness for an aging population, and will identify modifiable factors that can be intervened upon by nursing home staff and regulators to improve resident outcomes after exposure to severe weather events.

NIH Research Projects · FY 2025 · 2024-09

Project Summary/ Abstract Cell-cell interactions (CCI) play crucial roles in nearly all important biological processes, including cell differentiation, inflammation, wound repair and oncogenesis. CCI typically occurs when a sender cell's ligand interacts with a receiver cell's receptor, leading to changes in the target cell's transcription factor (TF) activities. Despite the advances in high-throughput methods, there is still a gap in the identification of CCIs from these data, relying largely on low-throughput manual methods. To address this gap, the proposed research aims to develop computational frameworks to model the impact of external signals on a cell's internal TF activity using a combination of single-cell multiome (scMultiome) and spatial transcriptomics (ST) data. The PI plans to create a series of computational methods based on his prior work, including: 1) DeepPrism, an improved version of BayesPrism, to more accurately deconvolve cell type fraction and cell type-specific gene expression from bulk RNA-seq and ST. 2) SpaceNiche, a method for jointly modeling the relationship between CCI and downstream gene expression using ST and provide interpretable biological insights about CCI. 3) RegulatoryVAE, a tool to infer TF activity and the relationship between regulatory elements and target genes from scMultiome which contains both the chromatin accessibility (ATAC) and gene transcription information. 4) NicheOT, a method to integrate TF activity learned from scMultiome and the spatial context learned from ST. 5) CARCell, a tool to quantify the impact of CCI on TF activity and their changes in diseased states. These tools will be able to address the significant limitations in existing methods including 1) inability to account for heterogenous gene expression and to use multiple scRNA-seq reference to perform statistical deconvolution, 2) the reliance on the transcription level of receptor/ligand to impute CCI, which may not reflect active protein levels and may fail to account for ineffective interactions due to physical separation or epigenetic states, and 3) the reliance on incomplete motif information to infer TF activity and the existing model’s inefficiency in capturing the complex relationship between DNA sequence and TF activity. The proposed methods will be applied to study the impact of CCI on inflammatory bowel disease (IBD) using scRNA-seq, scMultiome, and Visium data collected by a collaborator. IBD affects nearly 1.3% of adults in the US and its prevalence is increasing globally. Mis-regulated CCI is a key feature of the disease. By providing a generalizable tool for understanding CCI using ST and scMultiome, this work aims to fill the current gap in computational methodologies and advance the understanding of IBD, with the goal of developing new therapeutic targets.

NIH Research Projects · FY 2024 · 2024-09

Project Summary Built on the success of the GTEx project, the recently launched dGTEx project will recruit 120 donors to identify genetic variants affecting gene expressions across tissues at four developmental stages (postnatal, early childhood, pre-pubertal, and post-pubertal). Because there are considerably fewer samples in the dGTEx project than that in the GTEx project, there is a critical need to develop powerful and robust statistical methods to best use the dGTEx data for eQTL analysis. Moreover, single-cell sequencing is planned for the dGTEx project, creating additional challenges and opportunities. The overall objective of our project is to develop and apply novel statistical and computational methods to integrate different data sets to facilitate eQTL analysis of the dGTEx data, and share the results with the research community. We will accomplish this objective through three specific aims. For the first aim, we will infer tissue-specific eQTLs based on the total read count data by borrowing information across tissues and developmental stages. We will then develop a hierarchical Bayesian method to infer cell-type-specific eQTLs across developmental stages by jointly analyzing single-cell data and bulk samples with computationally estimated cell-type proportions. We will also consider isoform eQTLs for this aim. For the second aim, we will develop methods for identifying allele-specifically expressed genes in different cell types. To gain more power, we will develop methods to jointly call allelic events across tissues and cell types, correct for the specific biases in single-cell expression data, and develop methods for integrating allele- specific chromatin accessibility and allele-specific expression using single-cell multiome data. Single-cell data will then be combined with bulk RNA-seq data to improve allele-specific expression inference across subjects further. Finally, we will jointly analyze total read counts and allele-specific data for eQTL inference for this aim. In the third aim, we will develop methods to integrate data from other sources to complement the data collected from the dGTEx project, such as data from the GTEx project. We will leverage chromatin data to "transfer" known eQTLs from bulk tissues and larger cohorts to the specific (smaller) single-cell cohorts. We will also incorporate predicted effects of genetic variants from deep learning approaches in our modeling and analysis. To facilitate transcriptome-wide association studies for complex traits rooted in early development, we will develop gene expression imputation models based on our eQTL results. We will work with the dGTEx team to share our results with the broader scientific community via the dGTEx portal and ANVIL.

NIH Research Projects · FY 2025 · 2024-09

Project Abstract: Faithful epigenetic maintenance of repression is essential to developmental processes and is frequently disrupted in diseases like cancer. Repression is maintained, in part, by chromatin-associated proteins, like HP1 and Polycomb (Pc) groups that biochemically alter chromatin by depositing histone marks and spatially reorganize chromatin by compaction and/or phase separation mechanisms. As such, a physical mechanism of repression through stable compaction or phase separation of chromatin has been proposed as the function of heterochromatin organization, resulting in discrete open (active) and closed (repressed) chromatin states. My prior studies challenge this dogma by revealing that while Pc-repressed regions are compact and separated on average, at the single-locus level there exists a continuum of repressed chromatin conformations. I propose that instead of providing a physical mechanism of transcriptional repression, heterochromatin indirectly represses chromatin by regulating epigenetic memory. A mechanism of spatial feedback, through which dynamic chromatin folding permits distal loci to reinforce the deposition and maintenance of histone marks, serves as an epigenetic memory regulator without the need for a stably compact or phase-separated organization. In this model, the rates of interaction frequencies, facilitated by cell type- or locus-specific HP1/Polycomb proteins, refresh epigenetic marks in the face of nucleosome turnover and cell division. This dynamic chromatin organization can regulate stability of epigenetic memory such that a balance between maintenance of the existing epigenetic state and reprogrammability scales with cell plasticity. In this proposal I will rigorously investigate this functional feedback between 3D genome organization and the repressive epigenetic memory that underlies developmental gene regulation and cell plasticity. In Aim 1, I will evaluate how dynamic chromatin organization regulates epigenetic memory during development through a highly multiplexed epigenetic state and chromatin imaging methodology. This will enable me to analyze single-locus epigenetic states and chromatin folding in an organoid model, unveiling how spatial feedback shapes cellular reprogramming and fate commitment. In Aim 2, I will perform live imaging of heterochromatin dynamics which will allow me to define the motion of HP1 and Pc-bound chromatin and measure how chromatin motion influences epigenetic memory. Finally, I will develop a super-resolution imaging methodology to quantify protein-DNA interactions and chromatin folding to better understand the role of Pc associated proteins’ ability to alter chromatin organization and create different levels of chromatin spatial feedback.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY As many as 42% of American Samoan women develop gestational diabetes (GDM) in pregnancy, which substantially elevates their risk of progressing to Type 2 diabetes (T2DM). Genetic factors play a substantial role in diabetes risk, underscoring the importance of utilizing genomic data for targeted screening, treatment, and prevention. However, historical exclusion of PI populations from genetic research has hindered advancements in inclusive precision health initiatives, particularly related to women's health. In >10 years of research with Samoan communities our team identified a novel missense variant (rs373863828) in the CREBRF gene that is common among Pacific Islanders, including American Samoans. The CREBRF variant is associated with increased body mass, but is paradoxically protective against T2DM, making it an attractive potential biomarker of diabetes risk. The impact of the CREBRF variant on GDM risk, progression to postpartum T2DM, and the variant's mechanism of action remain unclear. However, preliminary data suggest that CREBRF may protect against GDM and that the mechanism of protection may be improved insulin secretion. To test these hypotheses, we will recruit a prospective cohort of 350 pregnant American Samoan women enrolled in the first trimester and followed until 18 months postpartum. Through three pregnancy (10-14 weeks (w), 24-28w, and 32-26w) and four postpartum (6-12w, 6 months (m) 12 m, 18m) visits we will comprehensively evaluate glucose homeostasis (frequently sampled oral glucose tolerance tests, HbA1c, and continuous glucose monitoring) and insulin response. We will use cutting-edge statistical approaches to examine how changes in glucose homeostasis and insulin secretion/action associated with CREBRF, which are not currently captured by routine 24-28w oral glucose tolerance tests, influence GDM and postpartum T2DM risk. Specifically, we will examine associations of CREBRF with glucose homeostasis during pregnancy (Aim 1) and postpartum changes in glucose homeostasis and incident pre-DM/T2DM risk (Aim 2), whether improved insulin secretion mediates the protective effect of CREBRF on diabetes risk (Aim 3), and explore the connections between CREBRF, insulin secretion, and birth outcomes (Exploratory Aim 4). Our work has strong potential to shift clinical practice and reduce diabetes disparities by proving insight into the potential for CREBRF to serve as a genetic biomarker of GDM or T2DM risk. More broadly, uncovering important insight into how the CREBRF variant regulates glucose homeostasis will inform future molecular studies to further understand CREBRF's mechanism(s) of action, potentially leading to pharmacogenomic approaches and future diabetes therapeutic targets for all populations. With expertise in epidemiology, diabetes, obstetrics, endocrinology, and biostatistics, our team is ideally positioned to carry out this ground-breaking work to reduce diabetes-related health disparities for American Samoan women.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY/ABSTRACT Childhood neglect accounts for 60% of all early life adversities and is associated with profound cortical thinning, hyperactivity, and cognitive deficits that include impaired hippocampal dependent memory. The molecular and cellular mechanisms responsible for these neurodevelopmental changes are difficult to study in humans and no animal models have yet replicated key structural and behavioral features of early deprivation/neglect. Here we show that mice pups raised under impoverished conditions of limited bedding and no nesting material (LB) show behavioral and structural changes that resemble those seen in children exposed to early neglect and that enrichment during the 2nd-3rd week of life corrects the hippocampal-dependent deficits seen in LB mice. In this proposal we hypothesize that LB inhibits the expression of the TREM2 receptor on microglia during peak synaptic pruning in the hippocampus. Abnormal synaptic pruning during the 2nd-3rd weeks of life leads to the retention of immature/non-functional spines resulting in immature and inefficient hippocampal circuitry characterized by low synaptic maturity index, reduced local functional connectivity in resting state fMRI, lower density of glutamatergic synapses, and impaired hippocampal function. Work in aim 1 will test whether overexpression of TREM2 is sufficient to correct the synaptic and cognitive abnormalities seen in adolescent LB mice. Chemogenetic activation of microglia and exposure to enrichment both increase levels of TREM2 and normalize microglial phagocytic activity. Studies proposed in aim 2 will test whether localized chemogenetic activation of microglia in the dorsal hippocampus from P13-17 can reverse the synaptic and cognitive deficits seen in LB adolescent mice. In aim 3 we will use Trem2 knockout mice to test whether the improved hippocampal function seen with enrichment, requires Trem2. Successful completion of this proposal will be the first to demonstrate that early neglect impairs synaptic pruning by reducing the expression of Trem2 and that these developmental abnormalities can be reversed with enrichment. These findings will provide a conceptually novel model to explain how deprivation and enrichment impact cognitive development and will hopefully inspire future collaborations to examine the effects of early neglect/enrichment on rsfMRI local functional connectivity in children.

NIH Research Projects · FY 2024 · 2024-09

Scientific Abstract Clonal Hematopoiesis of Indeterminate Potential (CHIP) is a condition of aging that has been associated with increased risk of heart disease and heart failure. CHIP is evaluated by DNA sequencing of peripheral blood. However, not all patients with CHIP will develop heart failure or myocardial infarction. Our preliminary data demonstrate that CHIP patients (cancer and non-cancer patients) have a higher burden of nonischemic scarring in their hearts on cardiac MRI compared to patients without CHIP. In a pilot cohort using a machine learning technique of convolutional neural networks (CNN), we are able to predict who have CHIP with 86% accuracy and predicted future cardiomyopathy with an accuracy of 73%, thus opening the door to possible image guided risk stratification for identifying patients with CHIP as well as predict future cardiac outcomes. We also find through our novel deep learning algorithm that we can identify extended somatic variants that are CHIP-like that can impact heart failure outcomes and through integration of patient data, genomic and imaging signatures, we are able to develop partition risk scores that can weigh the variables such as CHIP and their contribution to heart failure and the pathways involved. We hypothesize that using cardiac MRI, novel machine learning techniques on large imaging datasets can identify CHIP vs non-CHIP patients as well as predict who will develop adverse cardiovascular outcomes and that CNNs can be used on both imaging and genomic signatures in large cohorts like the TOPMED, UKB and All of Us to predict cardiovascular outcomes while pathway analyses will reveal mechanisms and novel targets for CHIP-mediated cardiomyopathy Specific Aim #1 will use a novel CNN with multi-view cross-attention to identify MRI features that can accurately predict CHIP as well as future adverse outcomes such as heart failure and myocardial infarction that will be validated in large datasets like TOPMed, UKB and All of Us with a collective ~13000 cardiac MRIs. Specific Aim #2 will use artificial intelligence approaches and a novel analysis pipeline that combines patient data, cardiac MRI signatures and genomic signatures of CHIP and extended somatic variants that are predictive of cardiovascular outcomes to help reveal mechanisms behind CHIP’s contribution to cardiomyopathy.

NIH Research Projects · FY 2024 · 2024-09

Driving lymphoid potential in multipotent hematopoietic progenitors by linker histones Abstract Functionally impaired hematopoietic stem and progenitor cells (HSPCs) often display differentiation skewed toward the myeloid lineage, underlying disease states such as myeloproliferation, inflammation and cancer1-3. The molecular mechanisms responsible for the myeloid versus lymphoid decision within the multipotent HSPCs remains poorly understood, and intervention strategies to boost lymphopoiesis are limited. Chromatin organizes as DNA wrapping around the core nucleosomes, with linker histones binding to the nucleosome dyad. Linker histone binding stabilizes nucleosomes, compacts chromatin, reduces accessibility, and is enriched in heterochromatic regions. We have generated a doxycycline (Dox) inducible H1.0 overexpression transgene (iH1.0). Using this mouse model, we discovered that H1.0 overexpression in HSPCs leads to dramatically expanded lymphoid biased and committed progenitors as well as more mature lymphocytes in circulation. Based on the strong lymphoid differentiation potential of H1.0+ HSPCs, we aim to define a molecular pathway that regulates the lineage output of multipotent HSPCs by linker histones via three specific aims. Aim 1 will test the hypothesis that either a specific linker histone isoform, i.e. H1.0, or the abundance of total H1, drive the lymphoid potential of multipotent HSPCs, by examining the lineage potential of various H1 null and re-expression models. Aim 2 will address how lineage specificality is accomplished, as H1s do not have sequence specificity. Our preliminary data show that H1.0 overexpression leads to sharply reduced chromatin accessibility at the Hepatic Leukemia Factor (Hlf) gene, and reduced Hlf mRNA expression. As Hlf has strong myeloid-promoting effect, we will test whether linker histone promotes lymphoid potency by restricting chromatin accessibility at this myeloid- specifying factors to reduce its expression. As our preliminary data show that H1.0 protein undergoes aspartyl protease-dependent turnover, Aim 3 will test the hypothesis that inhibiting aspartyl proteases prevents the drop in H1.0 protein and sustains lymphoid differentiation potency. The effects of several inhibitors of the HIV protease, an aspartyl protease, on the endogenous H1.0 and lymphopoiesis will be examined. This proposal will yield novel insights on how lymphoid fate specification is controlled by nucleosome/chromatin compaction via linker histones, and approaches to adjust the hematopoietic lineage output for therapeutic gains.

NIH Research Projects · FY 2024 · 2024-09

Project Summary/Abstract Options to reduce bleeding risk in persons living with hemophilia A are expanding. The issue is important because the expense of factor concentrates, the most expensive drugs per beneficiary under Medicare Part B, account for >80-90% of discounted lifetime hemophilia treatment costs (-$12-18 million per person). Options currently include i) standard half-life factor products, ii) extended half-life factor products, iii) non-factor substitutes, and iv) gene therapy. Analyses of optimal prophylactic strategies for persons living with hemophilia A are complicated by study heterogeneity, a result of different inclusion criteria and disease severity categories. To date, most health economic analyses have been funded by industry. A public-facing, easilyupdatable, transparent, and independent health economic model does not exist for treatment decisions faced by persons living with hemophilia A. Accordingly, the overarching goal of this research is to quantify value- and equity-informed resource allocation thresholds for subpopulations living with hemophilia A. The applicant will achieve the proposed aims of this K01 award under the guidance of established researchers who span health decision science, health policy, hematology, and pharmacoepidemiology. The applicant will create a publicfacing, transparent, and independent microsimulation model to evaluate all existing prophylactic treatment strategies for persons living with hemophilia A. He will use a combination of intermediate and advanced health decision science and pharmacoepidemiologic methodological techniques to derive equity weight thresholds, assess the value of collecting information with future studies, and quantify annualized bleed rates from realworld data. The research will make available needed information on the risks, benefits, and costs of bleed prevention strategies in persons living with hemophilia A. The proposed career development and training goals will provide the applicant with training in microsimulation, budget, and equity impact analyses, value of information research, and pharmacoepidemiology - and lay the groundwork for future research. The proposed training, infrastructure, and Yale institutional support will ensure the applicant's transition to independence.

NIH Research Projects · FY 2025 · 2024-09

Project Summary/Abstract Spatial organization of the genome, nucleome and transcriptome is key to their control of many essential genomic and cellular functions. Yet existing tools limit our ability to identify regulators of these spatial organizations. We are developing a high-content, image-based CRISPR screen to discover three-dimensional (3D) genome regulators, a first-in-kind technology to uncover the regulatome of 3D genome architectures across multiple length scales. Our proof-of-concept screen targeting hundreds of candidate regulators identified many novel chromatin organization regulators. The goal of this application is to advance our technology to develop a highly-efficient, large scale, and multi-omic screening platform to discover the molecular regulators of the spatial genome, nucleome and transcriptome. In Aim 1, we will develop a generalizable, large scale screening platform compatible with in situ spatial omics techniques. In Aim 2, we will develop multimodal detection and perturbation methods for comprehensive large scale screens of 3D nucleome regulators. In Aim 3, we will develop integrative methods for large scale screens of spatial transcriptome phenotypes to allow efficient discovery of the regulatory mechanisms of subcellular RNA transport and localization. We expect that these proposed developments will provide the research field with brand-new, broadly applicable technologies for mechanistic studies of the spatial genome, nucleome and transcriptome in a wide range of biomedical contexts.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY/ABSTRACT The overarching goal of this research project is to enhance the understanding and prediction of heavy drinking episodes during initial recovery (IR) from alcohol use disorder (AUD). Leveraging the latest advancements in wearable biosensor technology and artificial intelligence (AI), this project aims to address the significant gap in current scientific knowledge regarding the fluctuating nature of AUD recovery. Our objective is to utilize cutting- edge wearable biosensors, like the VitalConnect VitalPatch and SCRAM-CAM, combined with sophisticated AI methodologies, including convolution neural networks and Hidden Markov Models, to elucidate the complex interplay of physiological and neuroclinical factors in AUD recovery. Preliminary studies utilizing AI to analyze wearable sensor data have shown promising results in identifying behavioral phenotypes indicative of alcohol use risk, highlighting heart rate variability (HRV) as a particularly sensitive biosignal. The proposed research encompasses two primary aims: 1) To develop real-time predictive models using wearable sensor data that can accurately forecast heavy drinking episodes during IR. By integrating data from electrocardiograms and transdermal alcohol sensors with traditional self-report and behavioral assessments, we aim to construct comprehensive profiles that can anticipate periods of heightened drinking risk. 2) To identify and understand the neuroclinical and physiological mechanisms that contribute to or mitigate against shifts toward heavy drinking during IR. Through repeated biopsychosocial assessments and application of explainable AI techniques, we intend to uncover critical factors influencing recovery trajectories. Crucially, this project is supported by a dynamic and interdisciplinary team, bringing together experts in AUD treatment research, wearable biosensor technology, and cutting-edge AI and computational methods. This collaborative approach ensures a multifaceted perspective on the challenges of AUD recovery and enhances the project's capacity for innovative solutions and advanced data analysis. This project represents a novel integration of mobile health technologies and AI analytics in the study of AUD recovery. It has the potential to transform our understanding of IR, leading to the development of personalized, just-in-time interventions for individuals battling AUD. The collaboration with a state-funded community-based outpatient clinic specializing in SUD treatment provides a unique opportunity to validate our models in a real-world setting, enhancing the potential for these findings to be translated into practical, scalable monitoring and intervention tools.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY Alzheimer's disease (AD), and other neurodegenerative tauopathies, are defined by their pathologic accumulation of overexpressed, hyperphosphorylated, and oligomerized tau. Tau tangles result in proteotoxic stress through the endoplasmic reticulum (ER), cell death, and ultimately neurodegeneration. Understanding the molecular mechanisms that lead from tau aggregation to neuron loss is key to identify novel therapeutic targets. We have elucidated how the BCL-2 family member BOK induces apoptosis in response to ER stress stimuli. Specifically, we have found that BOK, which is predominantly bound to the inositol-3-phosphate (IP3R) calcium transporter in the ER, regulates the unfolded protein response (UPR) as well as the transfer of calcium from the ER to the mitochondria. Critically, BOK plays an important role in the formation of mitochondrial-ER contact sites (MERCs), also known as mitochondrial ER-associated membranes (MAMs). MAMs are central signaling hubs for the cell, mediating processes like calcium transfer, the UPR, mitochondrial shape and metabolic homeostasis. Neurodegenerative diseases have been associated with the abnormal quantity, formation and function of MAMs. In preliminary work we find that BOK regulates metabolic survival and cell death pathways in neurons. Our goal is to determine how the control of metabolic pathways through MAMs by BOK regulates neuronal cell death due to tau. Aim 1 will examine how BOK regulates tau-induced neuronal cell death through its regulation of ER to mitochondrial calcium transfer. Aim 2 will determine how BOK impacts autophagy through MAMs and its consequences for tauopathy. Aim 3 will define the ability of BOK to control lipid metabolism in tau-bearing neurons. Each of these aims focuses on metabolic pathways that signal through MAMs, that are known to be important for AD, and for which we have preliminary data implicating a role for BOK. This project will benefit from a multidisciplinary approach that includes neuronal genetic reprogramming, cutting-edge intravital microscopy, and advanced lipidomics. We will employ 2Phatal, two-photon chemical apoptotic targeted ablation, a novel technique we developed to induce and measure cell death in live mammalian brains without neighboring injury. These novel tools will enable us to address our conceptually innovative hypothesis that tauopathy-induced neuronal cell death is regulated by BOK's control of metabolic pathways that signal through MAMs. Discernment of the signaling networks that control the balance between metabolic homeostasis and cell death during tau- induced neurodegeneration is expected to provide targets for therapeutic development.

NIH Research Projects · FY 2026 · 2024-09

ABSTRACT Black and Hispanic men are at highest risk of comorbid conditions resulting from HIV. Cardiovascular disease has become the leading contributor to mortality among persons with HIV, as both conditions are often co-morbid. As a result, prominent HIV comorbid conditions include CVD, high blood pressure and type II diabetes mellitus. Compared with the general population, CVD risk is 1.5 to 2 times higher in people with HIV, and this risk increases with age. By the year 2030, an estimated 78% of persons with HIV will be 50 years old or older, and nearly 80% will have one or more chronic conditions. These overlapping health needs drive up the cost of care as total direct expenditures for HIV treatment in the US exceed those for persons without HIV by approximately $10.7 billion and cardiovascular and metabolic comorbidities further increase this financial burden. Increased risk of HIV-related comorbidities, such as heart disease, is driven by environmental and interpersonal factors that contribute to nicotine exposure, poor diet quality, low physical activity, insufficient sleep, high cholesterol levels, elevated blood pressure, high blood sugar, and increased body mass index. Even when HIV viral load is well-controlled, HIV-infection causes immune activation and chronic inflammation, which can cause a narrowing of blood vessels, and can result in high blood pressure, chest pain, and/or buildup of plaque in the heart, ultimately resulting in heart disease. The status quo as it pertains to traditional chronic illness prevention has been conventional patient teaching in the clinical setting. However, prevention efforts to reduce heart disease have not achieved population-level impact and have been less effective among persons with HIV. The LEARN Study was a pilot waitlist control trial testing a virtual environment for CVD and metabolic disease prevention education. Our LEARN findings suggested that participants are concerned about hypertension, type II diabetes, stroke, and cancer. Cancer risk reflected both the increased incidence of non–AIDS-defining malignancies among people with HIV and shared risk factors for cardiovascular comorbidities. We propose a follow-up study to these findings in LEARN 2 using innovative clinical and community collaboration, a multidisciplinary team, and a virtual environment designed to preemptively mitigate HIV‐related comorbidities with shared risk factors. Project objectives are to: 1) to utilize formative research to modify our intervention to address contextual factors that affect prevention of shared clinical risk factors for HIV‐comorbidities; 2) determine the efficacy of LEARN2, as prevention education for HIV-comorbidities; and 3) conduct a process evaluation of LEARN2 feasibility and acceptability, identifying which components are most successful in initiating change. This project represents a shift in the status quo and signifies a trailblazing effort that leverages a multidisciplinary team, virtual tools, and clinical and community collaborations to advance health optimization in populations experiencing health disparities, while informing research, clinical practice, and policy.

NSF Awards · FY 2024 · 2024-09

The living collections of zoos and aquariums (hereafter “zoos”) are a unique biological resource representing millions of animals across tens of thousands of species. Living collections in zoos hold broad scientific potential that cannot be replicated from traditional natural history collections. Modern zoos are transitioning from primarily entertainment venues to institutions of conservation, science, and education. Consequently, zoos are working to enhance their contribution to the advancement of biological sciences. Information from living animal collections can significantly improve our current knowledge of many vertebrate species. Further, Zoos hold extensive data on basic life history of many species, including data on lifespan and reproduction as well as information on pedigrees, growth, development, behavior, physiology, and immunology. The critical barrier for the advancement of basic science is that from live collections at zoos is that these data and specimens are not available to broader scientific communities – even for non-invasive research. Despite the obvious value of zoo collections for advancing biology, they remain an untapped resource for the larger scientific community. Given the similarities between zoos and museums as collection-based biological institutions, there is broad opportunity for zoos and natural history museum to collaborate more closely. This Research Coordination Network (RCN) will host ten workshops including professionals from zoos, natural history museums, and academia across the US to develop best practices for collaborations, sample sharing and data access, and to identify opportunities for scientific collaborations that are beyond the capacity of a single collection type. Biological collections are a crucial part of the global infrastructure for science. Preserved collections in natural history museums have long been recognized as a resource for science and STEM education while the living collections of zoos have not been widely appreciated for their intrinsic scientific value. Museum collections professionals typically have little understanding of the value, purpose, or potential of living collections in zoos. Collections-based collaborations between zoos and museums are rare, and while both zoos and museums hold vast datasets on their specimens, data is not interoperable between zoo and museum collection management systems. The rich data and biological materials collected over the lives of zoo specimens are of high value for basic and applied science, but are not accessible beyond zoos to the broader community of scientists. The RCN: ZooMu Network will build a lasting network of biological collections staff who are equipped to work between collection types, and will open broad new opportunities for biological collections research by linking living and preserved collections, databases, and professionals. Workshops will be held on the topics Physical Collections, Cyberinfrastructure, and Human Capacity. Four regional networks will address the issues pertinent to the institutions in specific regions of the country. By linking collections, staff, and data across collections types, this RCN will expand the national infrastructure for collections-based research. Zoo collections increasingly focus on rare and endangered species, and expanding research capacity into these living collections will open new possibilities for research with direct application for conservation science. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-09

Project Summary Over 280,000 people die from advanced heart failure each year in the United States. This population experiences burdensome symptoms, frequent hospitalizations, and delayed transitions to hospice care. Clinical practice guidelines recommend the use of palliative care for people with advanced heart failure to address their many palliative needs. However, fewer than 20% receive specialist palliative care, highlighting its markedly limited reach among this population. Little is known about the palliative care and cardiology program composition (i.e., structures) or operational characteristics (i.e., processes) that increase the reach of specialist palliative care or improve care near the end of life. As a result, medical centers nationally struggle to implement specialist palliative care for people with advanced heart failure and implementation varies widely. Our proposal will address these critical knowledge gaps. Our long-term goal is to increase the reach of specialist palliative care and improve the quality of end-of-life care among people with advanced heart failure. As a step towards this goal, the objective of this proposal is to identify the key modifiable structures and processes of specialist palliative care delivery that result in high-reach and three end-of-life care outcomes highly valued by people with advanced heart failure: days at home in the last three months of life, hospice enrollment ≥ 7 days before death and family-reported end-of-life care quality. To accomplish our objectives, we will conduct a rigorous multisite, mixed methods study within the Department of Veterans Affairs (VA). The VA is the largest healthcare system in the United States comprised of 146 nationwide medical centers. Moreover, it is the only healthcare system with an integrated electronic health record that includes detailed variables on structures and processes of specialist palliative care, cardiology programs and practices, and surveys of bereaved family members. We will combine VA data with data from the Centers for Medicare and Medicaid to comprehensively examine care near the end of life within and outside of the VA. We will evaluate associations between specialist palliative care and cardiology program structures and processes and the reach of specialist palliative care (Aim 1), and the three outcomes of end-of-life care quality (Aim 2). Next, we will conduct interviews with specialist palliative care and cardiology clinicians and analyze policy documents and consultation templates to identify strategies employed by medical centers that have successfully implemented specialist palliative care for people with advanced heart failure and compare them to those medical centers that have not (Aim 3). Finally, we will integrate quantitative and qualitative data to identify comprehensive strategies that facilitate the implementation of specialist palliative care for this population. This proposal directly aligns with NOT-HL-20- 737, by identifying practical strategies that can effectively overcome barriers and support sustained delivery of specialist palliative care. Findings from our project will provide valuable insights that can be utilized by palliative care and cardiology programs across the country, ultimately improving patient care.

NIH Research Projects · FY 2025 · 2024-09

Project Summary/ Abstract The researcher's central career goal is to become an independent researcher investigating disorders of consciousness (DoC), with a specific emphasis on using non-invasive neurostimulation to restore accurate conscious perception. Despite ongoing research efforts, gaps persist in the understanding of consciousness, and recent findings suggest promising avenues for neurostimulation therapies. Aim 1 of the dissertation research project involves utilizing functional magnetic resonance imaging (fMRI) to map brain networks associated with auditory perception without explicit reporting. The thesis work establishes a paradigm and machine learning model that eliminates the need for explicit reporting, mitigating confounding signals related to reporting. Preliminary data indicate success in inducing threshold-level perception, identifying eye metrics specific to auditory conscious perception, and a successful machine learning model to predict auditory perception based on eye tracking. Aim 1.2 will identify the neuronal activity associated with this more purified measure of perception. Auditory conscious perception is hypothesized to involve three major brain networks independent of task report: 1. Detection/arousal/salience networks, 2. Task-positive attention networks, and 3. Default mode network. This work will improve our capacity to identify auditory perception in those who may not be able to report their experiences and holds promise to help identify targets for neuromodulation to improve disorders of consciousness. Aim 2, the postdoctoral research direction, advances neuromodulation strategies for DoC. Current approaches like transcranial direct current stimulation (tDCS) and deep brain stimulation (DBS) have limitations, and the researcher proposes exploring transcranial, low-intensity, low-frequency focused ultrasound (tFUS) as a potential solution. tFUS offers spatially precise neuromodulation of deep brain structures without surgery, demonstrating safety and neuroactivity in animal models and healthy human volunteers. The plan is to contribute to the broader field of neuromodulation research by advancing understanding of tFUS's modulatory effects on neural networks associated with consciousness. Essential skills to be acquired include a comprehensive understanding and practical skills related to tFUS technology and gaining clinical insight into DoC and working with clinical populations. The training in both aims will significantly enhance the researcher's proficiency in neuroimaging, machine learning, and neuromodulation approaches, laying a solid foundation for future academic pursuits.

NIH Research Projects · FY 2025 · 2024-09

ABSTRACT Among the 5.5 million older people (>50 years) with HIV (OPWH), 80% live in low- and middle-income countries (LMIC). Ukraine, an emblematic LMIC in Eastern Europe and Central Asia (EECA), is the only world region with increasing HIV incidence and mortality. Among the 240,000 PWH in Ukraine, OPWH account for 15% of people with newly diagnosed HIV annually but OPWH are significantly less likely to initiate ART and be retained in care, compared to younger people with HIV. Consequently, mortality among OPWH is significantly higher than the age-matched general population. Key barriers to ART engagement for OPWH include stigma, social isolation and multimorbidity including depression. Our previous work demonstrates that OPWH in Ukraine crave giving and receiving peer support, are interested in mHealth options to increase social engagement and belonging within a community, and have capacity for smartphone use. PositiveLinks is an established mHealth platform demonstrated to effectively improve virologic outcomes in people living with HIV in the United States and in Russia, another higher-income country where it has been successfully piloted. This app delivers appointment reminders, daily queries (“check-ins”) of mood, stress and medication adherence, tailored educational resources, and the opportunity to interact with other users on a secure, anonymous community message board (CMB). We propose to adapt PositiveLinks for use in OPWH, for the Ukrainian LMIC context, and to incorporate into the mHealth platform a culturally appropriate depression screening with subsequent brief intervention and referral (SBIRT) to clinical evaluation. In the R21 phase, we will perform focus groups discussions with OPWH and key informant interviews with clinicians and clinic administrators to identify components to retain in the adaptation that are important for OPWH to meaningfully engage in HIV care. We will perform alpha and beta testing of PositiveLinks Ukraine to evaluate usability and functionality by OPWH to ensure that the R21 deliverable is a tailored, fully interactive app supported by local stakeholders. In the R33 phase, we will perform an individually randomized controlled trial among 240 OPWH, who are newly diagnosed or on ART without viral suppression, randomized 1:1 to the PositiveLinks Ukraine intervention versus treatment as usual, to evaluate a) feasibility using a validated framework, b) multilevel acceptability (OPWH, clinicians, clinic administrators, and policy makers), and c) efficacy examining viral load suppression at 12 months and secondarily ART initiation, retention at 12 months, VL suppression at 6 months, and time to ART initiation. These findings will provide key data necessary to design and conduct further mHealth implementation research within HIV care in Ukraine. Through this work, we will also stimulate capacity in mHealth through the development of a Consortium for mHealth Innovation and Intervention.

NIH Research Projects · FY 2026 · 2024-09

Project Summary/Abstract Candidate: I aspire to become an independent clinician-investigator working at the intersection of cardiovascular disease and aging, focused on the impact of cardiovascular treatments on cognition, function, and global quality of life in older adults. My clinical expertise as an interventional cardiologist combined with my research training through my Master’s in Health Sciences and Clinical Research have positioned me to accomplish this goal. I have a track record of success and independent funding for my aging research through a GEMSSTAR award, two Pepper Center grants, and a PCORI Healthy Aging award. Mentors and Environment: This project will be supported by a world-class mentorship team, including Dr. Thomas Gill (Geriatrics), a global leader in randomized trials in older adults and Director of the Yale Program on Aging (PoA) and Claude D. Pepper Older Americans Independence Center (OAIC), as well as co-mentors Dr. Eric Velazquez (Cardiology), an internationally recognized cardiovascular trialist and Chief of the Yale Heart & Vascular Center, and Dr. Jeff Williamson (Geriatrics, Alzheimer’s Disease and Related Dementias (ADRD)), an expert in brain health and physical function in older adults and PI of the SPRINT MIND and PREVENTABLE trials. My advisory team includes experts in biostatistics, analytical sciences, randomized trial design, the study of ADRD and the heart-brain continuum. We have constructed a comprehensive career development plan that will leverage the infrastructure of the Yale PoA/OAIC, the Yale Alzheimer’s Disease Research Center (ADRC), the Duke-UNC ADRC, national educational resources for ADRD-related research, and leadership training. The combined support of the Yale School of Medicine PoA/OAIC, ADRC, and sections of Geriatrics & Cardiology, and my external collaborators, will catalyze my successful career development and completion of the proposed research plan. Mentored Research Project: Older adults with cardiovascular disease frequently cite maintenance of cognitive function as their top health priority. Recent randomized trials have begun to investigate whether commonly used cardiovascular treatments can modify the risk of developing cognitive impairment or dementia. Stable ischemic heart disease is one of the most commonly treated conditions impacting older adults, with beta-blockers & calcium channel blockers considered the two first-line anti-anginal treatments. To date, these agents have not been adequately tested in older populations and their long-term effect on cognitive outcomes is unknown. We will leverage existing longitudinal data from the SPRINT MIND trial as well as prospective randomized trial data from the PCORI-sponsored LIVEBETTER trial to rigorously evaluate the effect of these two commonly used medication classes on cognitive status over time, mild cognitive impairment, and the incidence of dementia among older adults.

NIH Research Projects · FY 2024 · 2024-09

ABSTRACT Every year in the United States, over 35,000 newborns suffer from neurologic injury at the time of birth due to hypoxia. Despite widespread use of cardiac external fetal monitoring (EFM) for the last 60 years, the rate of fetal neurologic injury has not decreased, highlighting the urgent need for better assessment methods in labor. Currently, clinicians still rely on cardiac EFM, which reflects a downstream effect of initial neurologic damage due to interruptions in fetal oxygenation resulting in subsequent heart rate changes. Relying on downstream effects can be inaccurate and result in both false positive and false negative diagnoses. Evaluating fetal brain activity via fetal electroencephalography (fEEG) has been shown to be a promising method as it shows abrupt signal changes up to ten minutes before cardiac EFM changes measured in fetuses with acidemia. These ten minutes in delivering a fetus can be the difference between lifelong cerebral palsy and a developmentally normal child. However, vaginal fetal EEG (V-fEEG), the only currently available method, is invasive, requiring vaginal electrodes attached to the fetal scalp. Consequently, it has been abandoned as a monitoring method. Non- computerized abdominal fetal EEG, which is non-invasive, has been proposed, but is uninterpretable due to extensive signal artifact from non-EEG signals from the abdomen due to maternal and fetal movement, muscle activity, and maternal and fetal electrocardiogram signal. Our work overcomes this challenge by harnessing advances in artificial intelligence to identify and filter out non-fetal EEG signals, allowing fetal neurologic activity to be accurately and non-invasively measured. We have developed an algorithm that has been refined and applied to patients that shows classical fetal EEG response to auditory stimuli, or evoked brain stem potentials. Using this algorithm, fetal EEG signals can be separated cleanly from maternal and other fetal noise. Our hypothesis is that our method of computerized abdominal fetal EEG (cAb-fEEG) can rapidly and accurately reconstruct fetal neurologic activity and is equivalent to invasive V-fEEG monitoring. To test this hypothesis, we will first compare our method of cAb-fEEG to direct V-fEEG in a group of 46 patients to quantify reconstruction error (regression residuals) between the signals. Second, neurology clinical experts in EEG interpretation will evaluate the neurological features of both cAb-fEEG and V-fEEG. To achieve these aims, we have assembled and will lead a team of experts in EEG research, electrical and computational engineering, clinical neurology, obstetrics, and pediatrics. We expect the results of this study will formally provide a strong base for cAb-fEEG and lay the foundation for future clinical studies to evaluate cAb-fEEG as a monitoring method to improve perinatal outcomes. The results of this research will provide a non-invasive and novel method to directly measure fetal neurologic activity and have the potential to decrease the rates of preventable brain injury at birth.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Alzheimer's disease (AD) is an age-related neurodegenerative disease characterized by progressive cognitive decline and dementia. It accounts for approximately two-thirds of all dementia cases, and its pathogenesis may predate its clinical manifestations by decades. With ~44 million patients worldwide, AD is placing an everincreasing burden on long-term well-being, healthcare costs, and family life. Despite more than fifty years of research, no cures exist, and the standard of treatment remains unsatisfactory; available therapies only partially alleviate select clinical symptoms. Decades of genetic research have demonstrated the high heritability of AD, and identified dozens of genetic variants that are associated with AD, but it has not been straightforward to connect these to disease mechanisms. Disentangling the impact of the normal aging process on disease risk and progression is not straightforward and has hampered efforts to develop effective treatment or prevention strategies for AD. In the R21 phase of this proposal, we will leverage and integrate large-scale epigenomic and transcriptomic datasets from multiple consortia and projects to develop a cell-type specific regulatory network model for normal brain aging and AD brain aging (Aim 1), while we simultaneously generate the first empirical dataset to resolve AD risk regulatory loci with differential activity in donor-matched "young" and "old" human neurons and microglia (Aim 2). Reciprocal use of computational and experimental models will benchmark the extent to which we can recapitulate the hallmarks of AD brain aging in silica and in vitro (.R21 Milestone). In the R33 phase of this proposal we will model the epigenetic regulation of gene expression changes in brain aging and AD progression (Aim 3) and conduct an unbiased examination of the role of human brain cell aging in AD risk, validating age-dependent regulatory activity and resolving convergent downstream impacts of ADassociated variants and drivers of aging (Aim 4). Our objective is to couple emerging computational and experimental approaches to refine in silica and in vitro experimental models of aging, towards resolving how aging processes initiate and/or increase genetic risk for AD (R33 milestone). Overall, we test the hypothesis that aging-related processes and AD-associated risk variants independently alter chromatin accessibility and gene expression, acting in a combinatorial manner to drive aberrant cell type-specific function in AD. We propose to predict and measure the molecular and functional effects of aging on neural and glia function. Our hope is that this work may identify novel therapeutic points of intervention, in order to prevent or slow disease course in individuals with AD.

NIH Research Projects · FY 2024 · 2024-09

People experiencing homelessness have a disproportionate burden of mental illness and mortality than those who are not homeless. The environment in congregate shelter accommodation may significantly contribute to this health burden, particularly regarding mental health. Housing insecurity significantly increases risk of presenting to the emergency department in behavioral crises. In recent years, many cities implemented programs diverting congregate shelter residents, most commonly to hotel accommodation. There is some evidence that the shift to non-congregate living may have had a positive impact on people’s mental health. Connecticut localities are planning new policies designed to build on lessons learned from that period, providing non-congregate options through healthcare-community partnership organizations to people who are unhoused. Understanding the mental health effects of non-congregate shelter options is essential to inform these developing policy reforms and innovations. This project will use a Community Based Participatory Research transformative approach, with a multistage convergent parallel mixed methods design, to measure the impact of healthcare-housing community partnerships that support non-congregate living interventions on mental health. We will conduct the study in Connecticut, where a state-wide implementation of non-congregate shelter policies from 2020-2022 presents a unique opportunity to examine the relationship between housing interventions and mental health outcomes. This context presents an unprecedented opportunity to study the relationship between shelter interventions and mental health outcomes. We will aim to study the impact of both the above-mentioned shelter policies and developing and ongoing housing initiatives on mental health crises by: 1) Qualitatively exploring mechanisms between non-congregate housing policies and mental illness including a landscape analysis to characterize processes through which shelter and healthcare providers partner to address housing needs, building on strong existing relationships with stakeholders and people experiencing homelessness; 2) Characterizing the effect of Connecticut’s hotel-based temporary shelter program on mental health crises among patients experiencing homelessness who were diverted from congregate shelters to hotel rooms during between 2020 and 2022 compared to a control site in Alabama using data from electronic medical records to perform a difference-in- differences identification strategy; and 3) Prospectively evaluating, using mixed methods, the impact of current housing policies that offer non-congregate living options on mental health, including non-congregate spaces in existing shelters, and newer potential policies such as tiny house villages. Findings from this study have the potential to inform policies and procedures of healthcare-housing community partnerships and improve mental health among those experiencing homelessness.