Yale University

NIH Research Projects · FY 2025 · 2024-07

Alzheimer’s disease (AD) is the leading cause of dementia in older adults. Early diagnosis of AD and AD-related dementias (ADRD) is crucial to both avoiding potentially harmful delays in medical care, and stratifying patients for treatment and research studies. AD pathogenesis is associated with several biomarkers, including brain deposition of amyloid-beta (Aß) plaques and hyperphosphorylated tau, classified by the A/T/N framework. The “A” and “T” represent measures of Aß and tau, respectively. The “N” encompasses biomarkers of neuronal injury and neurodegeneration, including neuronal activity. While reductions in neuronal activity are associated with rapid cognitive decline in ADRD including amnestic AD, neuronal activity has not been established as a sensitive biomarker for AD, possibly due to limitations on current neuroimaging techniques to detect such changes early in disease course. Although 18F-flourodeoxyglucose (FDG) functional positron emission tomography (fPET) measurements can directly quantify neuronal metabolism, the use of FDG-fPET has previously been discouraged by inadequate spatial resolution and sensitivity. Addressing this limitation, the Carson lab and our collaborators recently developed the NeuroEXPLORER (NX), a brain-dedicated PET imaging system with ultra-high sensitivity that is tenfold greater than the current state-of-the-art, the High Resolution Research Tomography (HRRT), with ultra-high resolution and continuous head-motion tracking. Leveraging the ultra-high performance (UHP) of the NX to measure visual-stimulation induced neuronal activity using FDG-fPET could permit reliable measurements of metabolism in small brain regions. Further, several studies have demonstrated olfactory dysfunction (OD) early along ADRD, and Parkinson’s disease progression. However, olfactory impairments specific to AD, that may permit its early detection or distinction from other diseases, have not yet been established. Thus, it is hypothesized that NX FDG-fPET will yield measurements of small differences in olfactory-stimulation induced neuronal activity between ADRD and cognitively normal subjects. Finally, it is hypothesized that NX FDG-fPET signals will be correlated, but temporally and spatially distinguishable from functional magnetic resonance imaging (fMRI). Aim 1 of this study will investigate the capability of the NX to measure dynamic changes in glucose metabolism in small brain nuclei. Aim 2 will investigate the application of a novel paradigm, olfactory-stimulation FDG-fPET, to investigating early neurodegeneration in ADRD. Both aims will compare NX FDG-fPET to fMRI. My research will set the groundwork for future studies evaluating metabolism and tau, using ultra-high sensitivity and resolution, as AD biomarkers, while validating and extending tasks currently reliant on fMRI. The rigorous research skills I will obtain throughout this study, in combination with my training plan and excellent mentorship will prepare me to become an independent physician-scientist.

NIH Research Projects · FY 2025 · 2024-07

Project Summary Privacy and security of personal information has become one of the major grand challenges in modern society, especially for healthcare studies. Re-identification risks and data breaches require new policies and regulations for data sharing across healthcare institutions and research laboratories. While policy cannot solve the problem on its own, advanced technologies that work hand in hand with policy are important to address the privacy/security concerns. Predictive analytics can support quality improvement, clinical research, and eventually impact patient health status. Extensive clinical variable information and voluminous data records from multiple institutions and laboratories are necessary to further improve the performance of modeling approaches and to identify medication-outcome associations for diseases. Nonetheless, the transfer of such sensitive data among institutions/laboratories can present serious privacy risks, which can jeopardize NIH’s mission. Aiming at mitigating the privacy problem while increasing predictive capability via cross-institutional modeling, prior studies proposed distributed methods to exchange only the predictive models, but not patient data. However, these methods still pose many challenges to the clinical cross-institutional learning problem, including the need for more comprehensive clinical variables and more patient records to achieve better prediction discrimination and build more generalizable models, the necessity for discovery/alleviation of data manipulation to increase the trustworthiness of the collaboratively trained models, and the requirement for more validation to ensure usability. In this proposal, we plan to develop SOCAL (Privacy-protecting Sharing Of Clinical data Across Laboratories), a distributed framework addressing these challenges by integrating vertical/horizontal modeling methods to include both more complete variables and more records, discovering/alleviating data manipulation incidents using models recorded on blockchain, and conducting controlled experiments and designing/testing a web portal with physician-researchers to increase the usability of the system. SOCAL will be evaluated on a Coronavirus Disease 2019 (COVID-19) dataset from five University of California (UC) Health medical centers. We expect the knowledge/capability of collaborative modeling can be improved, the trustworthiness of the learning process can be enhanced, and the framework will be ready for use. SOCAL is innovative because it will be a new integration methodology for vertical/horizontal modeling, a novel data manipulation resisting methods, and a hardened prototype for a practical blockchain application. We anticipate a powerful impact of the SOCAL framework to largely reduce the privacy concerns of predictive modeling tasks for various stakeholders, including healthcare providers, clinical researchers, and patients. Upon completion, SOCAL can accelerate the development of methods/technologies to increase willingness of institutions to participate in such a collaboration for improving the effectiveness of healthcare.

NIH Research Projects · FY 2026 · 2024-07

PROJECT SUMMARY/ABSTRACT: This proposal for a Mentored Clinical Scientist Research Career Development Award (K08) outlines a comprehensive training program for the career development of the applicant Dr. Prajwal Boddu as an independent physician scientist. The focus of scientific investigation is myelodysplastic syndrome (MDS), the most common cause of bone marrow failure in adults. Mutations in well-defined groups of genes (splicing factors, epigenetic regulators) underlie most MDS. SF3B1 mutations are most common among splicing factors, accounting for about 20% of MDS cases. Conventional models assign disruption of alternative splicing to be the primary cause of splicing factor mutant MDS, but many limitations to these studies have prompted alternate hypotheses. In this application, we consider an additional context in which splicing factors function – specifically, their role in the regulation of RNA transcription. Given the close interplay between RNA transcription and splicing, we explored how SF3B1 mutations affect transcription kinetics. Our studies show that SF3B1 mutations disrupt RNA Polymerase II (Pol II) transcription, leading to a profound reshaping of chromatin architecture, and yielding targetable epigenetic modifications. Consequently, we redefine SF3B1-mutant MDS functionally as an epigenetic disorder. Based on these preliminary results, this proposal will delve into the molecular mechanisms that link SF3B1 mutations to Pol II elongation defects and altered chromatin accessibility. The first aim will explore a novel hypothesis that mutant SF3B1 impairs early spliceosome assembly, affecting Pol II density at gene promoters, ultimately leading to chromatin closure and altered gene expression. The second aim will investigate the impact of these transcription defects on higher order chromatin (3D genome). Recent studies have pointed to the link between 3D genome reorganization and clonal evolution and aberrant gene expression patterns in many clonal processes. The third aim seeks to leverage data from an unbiased screen that shows reversal of transcription defects through inhibition of chromatin modulators such as those in the Sin3/HDAC complex. Using patient derived xenograft (PDX) models, we will explore therapeutic targeting of these chromatin modulators. The application seeks to expand the principal investigator’s training in RNA splicing, transcription biology, and epigenetics under the mentorship of Dr. Manoj Pillai, a physician scientist with expertise in RNA mechanisms and hematopoiesis, alongside co-mentor Dr. Karla Neugebauer, a pioneer in the field of co-transcriptional splicing. Additional expertise will be provided by an advisory committee comprising of Drs Andrew Xiao (epigenetics) and Amit Verma (patient-derived xenograft modeling and pre-clinical studies of MDS). Yale University provides exceptional opportunities for both training and career development for aspiring physician scientists such as Dr. Boddu. A carefully designed career development plan will include didactic coursework and career mentorship to complement the rigorous hands-on scientific training.

NIH Research Projects · FY 2025 · 2024-06

Abstract: My laboratory is interested in studying signaling mechanisms for the regulation of neutrophil biology. Neutrophils are a type of polymorphonuclear leukocytes and are well recognized as one of the major players during inflammation. Although neutrophils are required for normal immune responses, they are also responsible for many inflammation-related diseases as the effector molecules released by neutrophils are toxic to host tissues. Mature neutrophils are known for their short lifespan (half-life is generally believed less than a day), and their lifespan may be expanded in inflammatory and disease conditions. Thus, the control of neutrophil development and lifespan can be a key step in regulating neutrophil-related functions in normal physiology as well as disease conditions. However, not much is known about the mechanisms underlying neutrophil development and lifespan regulation. While transcription factors like Cebpe are known to play a role in neutrophil development, investigations into these mechanisms have been limited to individual studies. Therefore, a comprehensive genetic screen would provide comprehensive knowledge of neutrophil development. In addition, although various death mechanisms, particularly apoptosis, play roles in neutrophil death, their blockades only had moderate effects, suggesting unknown mechanisms may exist. Thus, we hypothesize that there might be novel mechanisms for the regulation of neutrophil lifespan. Primary neutrophils have a very short lifespan and are unable to expand perpetually in vitro. Together with their being refractory to transfection or viral transduction, neutrophils have never been used in any large-scale genetic screen in mice. The HoxB8-ER fusion protein has been used to immortalize mouse hematopoietic progenitor cells (HoxB8-HPCs), which can differentiate into neutrophils both in vitro and in vivo. The HoxB8-HPC-derived neutrophils were functionally similar to freshly isolated mouse neutrophils. Because HoxB8-HPCs can be unlimited expanded and transduced with lentivirus, they are amenable to genetic screens. In our preliminary studies, we have established Hoxb8-HPCs from a Cas9 knock-in mouse line. These cells can be transduced with lentivirus with sufficient efficiency to meet our screening goals. We also did a pilot in vivo screen using one of the sub-libraries, which demonstrated the feasibility of our screen strategy and method. Therefore, in this exploratory R21 proposal, we propose to perform the first CRISPR-Cas9-based screens for key regulators that control neutrophil differentiation from HoxB8-HPCs and lifespan of differentiated neutrophils in mice. Our proposed work will not only establish a valuable research tool but also yield insights into neutrophil biology that cannot be predicted from existing knowledge. Importantly, the tool we are developing and validating here can be readily adapted for screens with many other possible readouts.

NIH Research Projects · FY 2025 · 2024-06

Respiratory viruses have wide-ranging impacts on public health. Impactful viruses include SARS-CoV-2, which caused over 1.1 million deaths in the U.S. since 2020, influenza, which typically causes tens of thousands of deaths and hundreds of thousands of hospitalizations each winter, and rhinovirus, which is a major cause of disease exacerbations in common chronic lung diseases such as asthma and COPD. The interferon (IFN) response is a critical defense mechanism that protects against these and other respiratory viruses, but excessive IFN responses can impair tissue repair and drive immunopathology. Canonical Type I (IFNs a, b) and Type III IFNs (IFNl1-3), are regulated by induction: they are constitutively off but are rapidly and transiently induced in response to viral infection. This project focuses on a non-canonical Type I interferon, IFN epsilon (IFNe), and its distinct regulation and role in coordinating mucosal interferon responses in the human respiratory tract. IFNe is known to play a role in mucosal defense in the female reproductive tract (FRT), but a role in the respiratory tract has not previously been described. This project will address this knowledge gap. Our data indicate that IFNe is constitutively expressed by human airway epithelial cells and can stimulate antiviral responses in these cells, albeit much less potently than canonical Type I or Type III IFNs. Previous work and our data also suggest that constitutive IFNe expression is modulated by inflammation. We hypothesize that IFNe functions to enhance baseline antiviral defenses in the respiratory epithelium, particularly in the setting of recent damage, thus fine-tuning antiviral responses to be “just enough” to counter infection while minimizing the need for inducible IFNs and the risk of excessive immune activation upon viral infection. If this model is correct, IFNe could be the basis of novel strategies to enhance mucosal antiviral defenses while minimizing the risk of immunopathology from the more potent canonical IFNs. Testing this model supports our long-term goal, to inform the development of host-directed therapies that reduce the public health impact of respiratory viruses. The goal of this project is to establish the presence of IFNe in the human respiratory tract and understand its relationship to canonical IFNs in regulating and fine-tuning IFN responses. Aim 1 will define the cell-type specific expression of IFNe in the differentiated human respiratory epithelium and regulators of expression, using both the tissue-like air-liquid interface culture model and primary human airway mucosal tissue. We will also define nasopharyngeal (NP) IFNe protein levels in human subjects using NP swabs collected for SARS-CoV-2 screening at Yale New Haven Hospital. Aim 2 will employ the ALI culture model to define the function of IFNe in the respiratory epithelium alone, in combination with canonical IFNs, and in dynamic setting of viral infection, testing the impact on high-impact human respiratory viruses including SARS-CoV-2, influenza A, and rhinovirus. Public health impact: This work will provide insights into the regulation of the interferon response, a key host defense against respiratory viruses, and will inform new strategies to prevent viral respiratory infections.

NIH Research Projects · FY 2025 · 2024-06

PROJECT SUMMARY Xylazine has become an increasingly common adulterant that is often unknown to the user. The combination of xylazine with fentanyl is particularly prominent with xylazine now recognized as an escalating factor in fentanyl overdose deaths. How xylazine potentiates fentanyl toxicity including the basic dose/response, however, remains unclear. Both fentanyl and xylazine produce respiratory depression and it is generally accepted that co- administration increases potency for both, thereby enhancing the potential for profound hypoventilation that if left untreated can lead to hypoxic organ damage and death. Less well appreciated is that unlike fentanyl, intravenous xylazine has significant direct adverse cardiovascular effects that can lead to substantial reductions in blood pressure and cardiac output (whole body blood flow). Implications of this in the context of co-administration are two-fold. First, while the brain and other vital organs exhibit intrinsic autoregulatory responses to maintain blood perfusion and oxygen delivery over a range of blood pressure and blood flow, this autoregulation has limits when the blood pressure is very low and/or metabolic disturbances such as acidosis are superimposed. Recently published data indicate that, at least for the brain, xylazine also blocks some aspects of cerebral autoregulation that are not significantly altered by fentanyl alone. Second, since oxygen delivery to tissues is the product of both the oxygen content of arterial blood and blood flow, xylazine may enhance fentanyl toxicity by not only potentiating respiratory depression to produce hypoxemia but also by reducing organ perfusion. Additionally, in that fentanyl is metabolized in the liver and clearance is largely dependent upon hepatic blood flow, it is possible that xylazine-induced reductions in cardiac output may also enhance fentanyl toxicity by impairing its clearance. Currently, there are no controlled robust data specifically defining how the dose/respiratory response for fentanyl is altered by xylazine (or vice versa), how xylazine may enhance fentanyl toxicity by further impairing oxygen delivery, or whether xylazine alters fentanyl clearance. The proposed studies will address these fundamental knowledge gaps using anesthetized swine extensively monitored to provide assessment of a wide range of respiratory, cardiovascular, and metabolic endpoints as well as biochemical makers of end-organ damage. Importantly, since the doses associated with clinical toxicity manifest as respiratory depression are unknow, we will first define within the experimental model of this exploratory study the dose/respiratory depression response relationship for fentanyl and xylazine individually and use these data to guide subsequent co-administration studies.

NIH Research Projects · FY 2026 · 2024-06

Project Summary Opioid medications are highly prescribed for pain management. However, these drugs have considerable abuse liability. As users increase their opioid intake, they build tolerance against their therapeutic effects. Despite well- described molecular and cellular mechanisms, tolerance can be reversed when the drug is taken in another context, a phenomenon known as associative analgesic tolerance. Since associative analgesic tolerance can lead to escalation of use, it increases the risk of opioid use disorder and fatal overdose. Uncovering neuronal mechanisms underlying associative analgesic tolerance will inform the development of new treatment options to mitigate pain while decreasing opioid use and overdoses. Using a novel behavioral training paradigm in mice, I identified brain regions activated by tolerance. The anterior cingulate cortex (ACC) plays a crucial role in contextual learning, nociception, and opioid analgesia, which are aspects of associative tolerance. My preliminary data indicate that associative tolerance induces the formation of a tolerance-active neuronal ensemble in the ACC (ACCtol-active). Preliminary studies using fiber photometry and chemogenetic approaches suggest that ACC activity tracks tolerance state and is necessary for associative tolerance expression. These data indicate that the ACC may be an orchestrator of associative tolerance. The ACC projects directly to the spinal cord (SC), and activation of this projection increases nociception. I hypothesize that ACCtol-active neurons produce associative tolerance by integrating context and drug signals to increase SC excitability in the presence of opioids. In the K99 phase, I will determine the role of the ACCtol-active ensemble in associative tolerance using a combination of transgenic tools for ensemble tagging, fiber photometry, and optogenetics. I anticipate that ACCtol-active activity will be upregulated during tolerance and that the bi-directional modulation of this ensemble will induce or prevent tolerance. In the R00 phase, I will use viral-mediated tracing and chemogenetic approaches to determine if ACCtol-active forms functional connections onto the SC and if modulating this pathway can alter associative tolerance. These experiments will help define the role of specific ACC ensembles and the ACC to SC circuit in associative analgesic tolerance. In addition to significant scientific advances in understanding the neural substrates driving contextual control of analgesic tolerance, this K99 proposal will provide me with training and mentorship to increase my technical and academic skills, building a foundation for my career as an independent investigator with my research laboratory. During the training phase, I will acquire extensive training in optical techniques, corticospinal circuit manipulations in vivo, and career development. This training, combined with my expertise in behavioral pharmacology and addiction models, will equip me to transition to independence as an Assistant Professor. During the R00 phase, I will apply these techniques to defining corticospinal circuits involved in associative tolerance. The training and support from this proposal will provide the scientific and mentorship tools needed for me to establish a successful, independent academic laboratory.

NIH Research Projects · FY 2026 · 2024-06

PROJECT SUMMARY Despite effective antiretroviral therapy (ART), HIV resides in infected cells as integrated proviruses and persists lifelong. While ART suppresses plasma viral load to clinically undetectable levels, ART does not kill the existing HIV-infected cells. HIV-induced chronic immune activation accelerates aging, increases risks of premature cardiovascular diseases, and increases cancer risks. It was believed that HIV latently infected cells, as opposed to transcriptionally active HIV-infected cells, are the major barrier to cure. Transcriptionally active HIV-infected cells should presumably die of viral cytopathic effects or immune clearance and therefore were not the major focus of research. However, recent studies revealed that transcriptionally active HIV-infected cells can survive viral cytopathic effect, escape immune clearance, persist, and proliferate despite suppressive ART. This is because although ART inhibits viral enzyme function, ART does not inhibit HIV LTR promoter activity. Despite suppressive ART, HIV LTR promoter fires bursts of viral protein expression in people living with HIV under suppressive ART and induce immune activation. Our central hypothesis is that transcriptionally active HIV- infected CD4+ T cells drive chronic immune activation in tissues. Our goal is to examine HIV-induced immune activation at the single-cell level. Identifying HIV-infected cells for mechanistic understanding is extremely challenging because of the rarity and heterogeneity of HIV-infected cells. First, only 1 in a million CD4+ T cells harbor infectious HIV provirus, while around 1000 per million CD4+ T cells harbor defective HIV provirus. The remaining 99.9% of CD4+ T cells are uninfected. Therefore, bulk transcriptomic approaches measure the 99.9% of uninfected cells and do not reflect the cellular states of HIV-infected cells. Second, CD4+ T cells are extremely heterogeneous because of distinct T cell differentiation (such as naïve, central memory, and effector memory), polarization (such as Th1, Th1, Th17, TFH, Treg), immune programs (such as activation, exhaustion, and cytokine responses). Therefore, single-cell multi-omic profiling is needed to identify the rare and heterogeneous HIV-infected cells. Third, there is no cellular markers that can specifically distinguish HIV-infected cells from uninfected cells. Therefore, understanding HIV persistence in vivo has been a major barrier in the field. To resolve the rarity and heterogeneity of HIV reservoir, our approach is to use single-cell multiomic approaches to profile the rare HIV-infected cells at the single cell level and examine the heterogeneous infected cells. We pioneered singlecell multi-omic profiling to advance our understanding of HIV reservoir. Using single-cell ECCITEseq, we used HIV RNA expression as a surrogate to identify transcriptionally active HIV-infected cells and their single- cell transcriptome landscape. Using single-cell DOGMAseq, we identified latent (HIV DNA+ RNA–) and transcriptionally active (HIV RNA+) HIV-infected cells and their epigenetic regulators, transcriptional landscape, and surface protein expression. In Aim 1, we will examine the immune activation programs in HIV-infected cells. In Aim 2, we will examine whether HIV infection induces immune activation in uninfected immune cells.

NIH Research Projects · FY 2025 · 2024-06

PROJECT SUMMARY It has now been two decades since the clinical high risk for psychosis (CHR) criteria were first formulated in service of the goal of preventing psychotic disorders, one of the most urgent unmet clinical needs in behavioral health if not in all of medicine. As with most psychiatric patients, CHR patients benefit from psychotherapies but are also often left with important treatment needs not fully addressed. Despite the critical public health need, drug development for CHR is viewed in many quarters as risky. The Foundation for the National Institutes of Health and the National Institute of Mental Health along with other public and private partners established the Psychosis Risk Outcomes Network (ProNET) and the Accelerating Medicines Partnership® Schizophrenia Observational Study (AMP® SCZ) in 2020 to develop tools to parse the heterogeneity of the CHR syndrome and de-risk the drug development that could lead to improvement of symptoms and functioning in CHR patients and ultimately to the prevention of schizophrenia. The current project, the Psychosis Risk Outcomes Compound Assessment Network (ProCAN), follows up on this successful previous initiative and will establish infrastructure to determine, in partnership with the Clinical Trials Data Processing Analysis and Coordination Center (CT-DPACC), whether the biological, digital, cognitive, and clinical outcome measures developed in AMP SCZ are viable as drug development tools (DDTs) for use in Phase 2 clinical trials in participants at clinical high risk for psychosis (CHR). One or two Phase 2-ready compounds will be studied, each selected by the AMP SCZ Compound Selection Committee. Aim 1 will evaluate the potential of selected compound(s) to detect a signal in CHR participants on one or more biological, digital, cognitive, or clinical outcome measures developed in the AMP SCZ Observational Study within a 16 week time frame. We propose two trials, each with 15 sites, each with three arms and 65 participants per arm (total per trial N=195), and each with the Network RFA specified maximum 16 week follow-up. Compound safety will also be evaluated. Aim 2 will determine whether biomarkers developed in the AMP SCZ Observational Study and/or novel biomarkers can act as pharmacodynamic readouts of drug response and/or provide insights into proposed mechanisms or pathways underlying CHR for psychosis. We propose biomarker timepoints at baseline and 8 and 16 weeks. If outcome or biomarker signals are detected, findings will pave the way for further development of phase-specific and safe new interventions to benefit CHR patients and their families and communities.

NIH Research Projects · FY 2025 · 2024-06

Modified Project Summary/Abstract Section Daily and intermittent/2-1-1 pre-exposure prophylaxis (PrEP) options are promising to end the HIV epidemic among participants in the Philippines where the HIV case infections recently doubled (1560 cases in 2022 vs. 714 in 2019) within a short timeline in this population. Understanding end-user input and preferences of PrEP via behavioral economic approaches like conjoint study designs are vital to maximizing its effectiveness such as feasibility, acceptability, and sustainability across its care continuum. However, to our team's knowledge, no conjoint design studies have been applied to examine participants' end-user preferences for PrEP, including the co-use of hormone therapy. Moreover, the socio-ecological facilitators and challenges pertinent to influencing PrEP uptake across the personal, social, economic, and structural levels are underexamined among this population. As such, along with this study's Stakeholder and Scientist Advisory Board, this proposal aims to inform and test a future behavioral economic-based intervention to support PrEP engagement among participants in the Philippines, with the following aims: (1) To qualitatively explore and identify all preferred and accepted attributes and features of PrEP needed to inform a full-profile PrEP program choice-based conjoint survey study via in-depth interviews with 30 participants and 15 key informants (i.e., HIV specialists, primary care providers, PrEP programmers/policymakers), and (2) To quantitatively test and determine optimal combinations of attributes predictive of participants' acceptability and preferences about PrEP modalities via full-profile choice-based conjoint study design with 300 participants in the Philippines to enhance implementation outcomes (e.g., acceptability, feasibility) of future intervention, and examine socio-ecological factors that may influence the chosen optimized PrEP program preferences. Findings will provide pilot data insights to test the identified optimized PrEP program profile(s) via a future larger scale (R01) behavioral economic-structural strengthening intervention for participants in the Philippines to increase PrEP uptake and reduce HIV incidence in the Philippines.

NIH Research Projects · FY 2026 · 2024-06

PROJECT SUMMARY Deuterium metabolic imaging (DMI) is a novel, MR-based method to map metabolism non-invasively in vivo. DMI maps of glucose metabolism in patients with high grade brain tumors illustrate the detection of aberrant metabolism (`Warburg effect') with high contrast, thereby showing a strong clinical potential to supplement existing anatomical MRI with unique metabolic information. DMI is not the first MR-based metabolic imaging modality, but stands on the shoulders of 1H, 13C, 31P and hyperpolarized 13C MR spectroscopic imaging (MRSI). Unfortunately, none of these methods have reached their full clinical potential due to a variety of reasons including technical complexity and lack of robustness and/or sensitivity. DMI is unique in that it is extremely robust due to the simple MR acquisition methods, while providing good sensitivity and information content, making it an ideal technique for broad dissemination in the clinical arena. Yet, adding DMI scans to a standard, clinical MRI protocol is challenging because the relatively long scan time of DMI that can result in decreased patient compliance and increased scanning costs. Fortunately, MRI and DMI are based on different, well- separated resonance frequencies, opening the possibility to acquire DMI in parallel with MRI without increasing the scan time. This is achieved by implementing DMI acquisitions during the short delays present in most MRI methods to generate appropriate anatomical image contrast. Here we pursue the technological innovations necessary to achieve high-quality and time-efficient parallel acquisition of MRI and DMI on a clinical MR scanner. This overall goal will be achieved through three Aims, focused on hardware and software development followed by in vivo evaluation. Aim 1 is focused on the development of a 1H/2H RF coil suitable for parallel MRI-DMI on human brain in a clinical research setting. Primary design criteria are brain coverage and sensitivity for 1H and 2H, in addition to acceleration potential for 1H. Aim 2 addresses the development and implementation of parallel MRI-DMI methods on a clinical 3 T Siemens platform. The selected MRI methods will resemble a standard, clinical brain MR examination protocol and include FLAIR, T1-weighted MP-RAGE, diffusion-weighted imaging (DWI) and susceptibility-weighted imaging (SWI). Aim 3 is centered on a comparison between standard and parallel MRI-DMI acquisitions on healthy volunteers to test the general design philosophy that parallel MRI and DMI sensitivity, resolution and image contrast are unperturbed. Studies on patients with brain tumors are performed to demonstrate the robustness of parallel MRI-DMI under real-world conditions. Upon successful completion, this project will deliver the hardware and software necessary to achieve robust, parallel acquisition of high-quality MRI and DMI at 3 T. Integration of DMI into existing neuro MRI methods will result in a comprehensive imaging protocol that provides both standard anatomical and unique metabolic information of the brain without increased total scan time. These technical developments will be key for many clinical sites to gain access to DMI and drive its further development and validation via use in larger, diverse patient populations.

NIH Research Projects · FY 2026 · 2024-06

PROJECT SUMMARY (ABSTRACT) Combined oral contraceptive pills (COCPs), containing both an estrogen and a progestin, remain the most commonly used hormonal contraceptive method in the US, and overall, one of the most commonly prescribed medications among all women. Despite its high prevalence of use, little is known about the pharmacogenomics of COCPs, which are the relationships between genetic variations and interindividual variability in drug efficacy, metabolism, and safety. Pharmacogenomic investigations have led to the development of actionable clinical guidelines for over 40 drug-gene pairs, the majority of which involve drugs far less frequently prescribed than COCPs. Given the utility of COCPs and similar steroid hormone-containing medications throughout a woman's lifespan, it is imperative that we gain a better understanding of how individual genetic variation affects the wide interindividual response to these drugs. However, a major hurdle faced in conducting pharmacogenomic research with these medications is the lack of useful phenotypic data in existing biobanks. National genetic consortia are primarily made up of men or postmenopausal women, thus necessitating the creation of new biobanks that focus on reproductive-age women and collect data on phenotypes specific to steroid hormone medications. We aim to build a novel biobank of 700 COCP users to both validate previously identified genetic relationships among contraceptive implant users and to identify novel areas of the human genome associated with steroid hormone metabolism, contraceptive mechanisms, and side effects. We will collect pharmacokinetic outcomes from COCP users to evaluate the influence of CYP3A7*1C carrier status, which has been associated with increased metabolism of other exogenous and endogenous steroid hormones. We will enroll a subset of 150 COCP users into a matched case-control study to determine how CYP3A7*1C carrier status affects ovulation inhibition using pharmacodynamic measurements of hypothalamic-pituitary-ovarian axis suppression and dominant ovarian follicle creation. All participants will also complete questionnaires to assess their side effect profiles after a single cycle of COCP use and undergo serial measurements of clinically relevant biomarkers. Participants will then be given the opportunity to complete repeat questionnaires and biomarker measurements after 3, 6, and 13 cycles of continued COCP use. This prospective collection of side effect and biomarker data will allow for analyses of clinically pertinent phenotypes, such as early COCP discontinuation and enhanced estrogenecity. We will utilize genome-wide sequencing for all participants so that we can conduct exploratory genome-wide analyses in addition to our planned targeted approaches. This study will create the first biobank of COCP users specifically designed with collecting phenotypic data most pertinent for the eventual creation of precision and personalized medicine clinical tools. These clinical tools will one day allow women considering steroid hormone medications to assess their individual risk for medication failure and adverse side effects, thus leading to better informed care and increased patient satisfaction.

NIH Research Projects · FY 2025 · 2024-06

About two million persons are diagnosed with cancer every year in the US. The Effective clinical management of cancer patients including the use of oral therapies can improve outcomes and reduce costs. However, adherence rates to oral therapies in cancer treatment have been reported to be 20%, depending on the drug.2 Poor Patient-provider communication (PCC) is one of the barriers to adherence to oral chemotherapies in addition to adverse drug events and lack of knowledge about adherence. Timely and effective PPC with high levels of empathy shown by providers to address patients’ emotional concerns, wants, and needs can enhance patients’ trust in healthcare providers, and their clinical outcomes such as adherence and emergency services utilization. New digital health platforms such as secure messaging (SM) through patient portals can provide an effective and timely channel of Electronic Patient-Provider Communication (EPPC). Patients with and without cancer are increasingly using secure messaging to communicate their needs. As of May 2019, out of 1M patients that visited Yale New-Haven Health System (YNHHS), about 436,000 patients used the patient portal resulting in more than 2.7M messages. With the identification and quantification of EPPC in SM contents, we can measure associations and impact on patient-centered outcomes. However, existing studies to identify EPPC patterns in large scale SM data are limited as they focused only on patients’ messages and minimally included providers’ messages. Some studies are not scalable as they manually coded EPPC patterns for a small set of SM. We will fill this gap using natural language processing and machine learning approaches that will utilize big SM data. In our previous work we mapped expressions in SM into EPPC codes of communication using the Roter Interaction Analysis System (RIAS); a method to code medical interactions and developed the Electronic Patient- Provider Communication miner (EPPCminer) tool. It can detect three EPPC codes: information seeking and giving, socio-emotional behavior. In this study, we will (1) refine EPPCminer to more effectively extract more granular EPPC codes of information seeking (e.g., medication-, lab-, imaging-related), information giving of social determinants of health (e.g., transportation, economic concerns, food), socio-emotional behavior, partnership building, and shared decision-making. We will refine EPPCminer using SM from YNHHS and Cleveland Clinic and evaluate generalizability using Veterans Administration (VA) data. partnership building, and shared decision-making. We will also assess and score quality of bi-directional communication by examining providers’ responses to patients’ requests in SM. (2) We will apply EPPCminer to SM of a cohort of patients with different types of metastatic. We will then extract and characterize EPPC codes from 1 year worth of prospective patients’ and providers’ SM and examine their associations with scores of patient-reported communication assessments. (3) We will assess the impact of EPPC codes on patients’ outcomes: adherence using pharmacy data and patient-reported adherence data, emergency room (ER) visits, and hospitalizations.

NIH Research Projects · FY 2025 · 2024-06

Project Summary The reactions of carbon-containing gas molecules (e.g., CO2 and CO) with metalloenzymes are vital biochemical processes. They are responsible for energy generation/storage and synthesis of biomass in many organisms. Additionally, the use and regulation of CO2 in our atmosphere has significant societal implications. In anaerobic microbes, the most prevalent enzymatic pathways for CO2 reduction and CO oxidation utilize nickel/iron-containing Carbon Monoxide Dehydrogenases (CODHes). Through spectroscopic and crystallographic studies of CODH, the active site of the enzyme was found to be an inorganic NiFe4S4 cluster, termed the C-cluster. Based on these experimental data, proposals for its mechanism have been formulated. However, discrepancies in (and different interpretations of) the experimental data have led to numerous structural/mechanistic hypotheses. Many important questions remain regarding the structure, function, and mechanism of the C-cluster. Synthetic bioinorganic modeling provides a valuable opportunity to learn about the electronic structure and reactivity of metalloenzymes. The well-defined environments in these models are far simpler to characterize spectroscopically and can be systematically varied to build structure–function relationships for fundamental insight into bioinorganic chemistry. Several synthetic models of the C-cluster have been developed and studied, including some with NiFe3S4 cores. However, none of these synthetic C-clusters had Ni in a biomimetic environment with three donor ligands, and none contained the important “unique” iron site outside the cubane core. Further, the influence of the second coordination sphere has not been investigated in C-cluster models. In this proposal, we seek to synthesize and study models of the C-cluster that contain biomimetic structural motifs hypothesized to be imperative for reactivity. The coordination environment around Ni will be systematically varied to elucidate the structure–function relationships of the metal centers and donors that comprise the C- cluster. These structural characteristics will be correlated with the reactivity of the cluster models toward CO and CO2, enabling us to study key proton and electron transfer events in a well-defined system. We will also study the validity of the various mechanistic hypotheses by synthesizing reactive intermediates of interest, including Ni hydrides. Most importantly, we will perform in-depth spectroscopic experiments on these model systems to shed light on the electronic structure and magnetic coupling of the reactive metal centers within the C-cluster. Bioinorganic spectroscopy will also be used to understand the redox events that occur during reaction with the gas molecules. In all cases, the reactivity and spectroscopic signatures will be compared with that of the C- cluster itself. These studies will help to elucidate the electronic structure and mechanism of the CODH C-cluster and will contribute to the ongoing development of biomimetic catalysts for CO oxidation and CO2 reduction.

NIH Research Projects · FY 2026 · 2024-06

Summary Mitogen-activated protein kinase (MAPK) cascades are core pathways mediating cellular responses to a wide variety of extracellular and intrinsic cues. In the past several years, we have made progress in understanding how connections are made in MAPK signaling networks, and we have exploited this knowledge to identify new MAPK substrates and regulators. We plan to extend these studies along two major lines of research. In the first, we will continue to investigate a role for non-catalytic “docking” interactions in mediating specificity and signaling output by MAPKs. We have developed yeast-based screening platforms to define sequence motifs selectively interacting with a conserved docking groove in the MAPK catalytic domain. We have so far applied these methods to a set of MAPKs including representatives of three major subfamilies (ERK, p38 and JNK). We plan to investigate novel MAPK substrates uncovered through these screens, with a focus on crosstalk between JNK and small GTPase signaling pathways. We further propose to expand our studies to include the remaining understudied MAPK groups, for which few substrates are known. To understand how selectivity is enforced in MAPK signaling systems, we will perform structural studies of MAPKs in complex with key regulators interacting with the docking groove and other ill-defined interfaces. Our second line of inquiry follows upon our recent discovery of the protein phosphatase 6 (PP6) complex as a MEK phosphatase that negatively regulates oncogenic ERK signaling. Despite being conserved throughout eukaryotes and essential to life in mammals, we know very little about the basic architecture and regulation of the complex. We will investigate the basis for PP6 complex assembly, and we will define how interactions with the catalytic and associated regulatory subunits confer substrate specificity. Finally, we will explore a role for PP6 in mediating a negative feedback loop in the ERK signaling pathway. Collectively, our proposed studies over the next five years will provide important new insight into the function of core signaling pathways relevant to normal physiology and human disease.

NIH Research Projects · FY 2026 · 2024-06

Project Summary Primary cilia serve as cellular sensors for rapid detection of environmental changes. These microtubule- based antennae are expressed on almost all eukaryotic cells across unicellular and multicellular systems and encompass wide roles in development and homeostasis. In recent years, primary cilia have come into the limelight in diabetes and metabolism research, as previously unappreciated functions have been attributed to these organelles on endocrine cells. Recent human genetic and GWAS studies show that cilia have clinically important roles in metabolic diseases including obesity and diabetes. In the pancreatic islet, we observe that loss of cilia disrupts β-cell endocrine functions including glucose-stimulated Ca2+ signaling and insulin secretion. Mice lacking cilia on β-cells develop glucose intolerance and diet-induced diabetes. These findings suggest that primary cilia mediate glucose responsiveness in normal β-cells, but the molecular drivers of ciliary glucose- sensing and signaling are unknown. In addition, proteome and metabolome profiling have been done in other mammalian cilia but not in pancreatic islet β-cells, posing a knowledge gap regarding cilia-dependent regulatory mechanisms in β-cell glucose metabolism and secretory function. Our preliminary studies identify glycolytic signaling machinery in β-cell cilia, both by proteomics and with a palette of newly developed biosensors that monitor the dynamics of ciliary signaling. We further demonstrate that glycolytic fluxes differ between primary cilia and cytosol in β-cells. Based on these findings, we hypothesize that compartmentalized glucose metabolism in β-cell cilia generates signals that regulate ciliary and cellular function. To test this hypothesis, we will combine genetic loss-of-function models with state-of-the-art proteomic and metabolic profiling tools, microscopy, electrophysiological recordings, and islet function tests to delineate the mechanisms by which cilia effect glucose-dependent β-cell functional changes. Aim 1 will leverage strong functional imaging, proteomic, and metabolomics expertise and promising pilot data to delineate the signaling network by which primary cilia relay glycolytic information and to comprehensively identify ciliary signaling pathways relevant to β- cell function. Aim 2 will determine the mechanisms by which cilia regulate β-cell electrophysiological properties and intracellular metabolic crosstalk leading to insulin secretion. A detailed understanding of these regulations by primary cilia could support the development of novel therapies to modulate β-cell function in diabetes.

NIH Research Projects · FY 2026 · 2024-06

PROJECT SUMMARY Cannabis consumption during pregnancy and lactation has reached 7-15% in pregnant women and nursing mothers in recent years, and will likely rise due to widespread legalization. Increased availability of cannabis has led to the public perception that it is a safe natural remedy for pregnancy-related ailments and postpartum mood disorders. Yet, growing clinical and preclinical data suggest prenatal and perinatal cannabis exposure is associated with long-term neurodevelopmental consequences in children, including sensorimotor, emotional, and cognitive deficits, as well as increased risk for illicit drug use in adolescence and adulthood. The neural mechanisms and sensitive periods underlying these long-term effects are still poorly understood, making it challenging to provide accurate medical advice for risk assessment of cannabis use in mothers. To address this challenge, our overall goal is to identify the developmental processes and circuit-specific mechanisms underlying the effects of early-life cannabinoid exposure on the emergence of cognitive behaviors. We will focus on the medial prefrontal cortex (mPFC) due to its high levels of cannabinoid receptor expression during development, and its critical role in cognitive processing. We will assess the circuit and network effects of early- life exposure to the two most widely used and frequently combined cannabinoids, 9-tetrahydrocannabinol (THC) and cannabidiol (CBD), in mouse pups across development. We will test the central hypothesis that early-life cannabinoid exposure disrupts mPFC maturation by interfering with network synchronization during a critical developmental window, resulting in abnormal neuronal activation during cognitive behaviors in adolescence and adulthood. We will leverage our novel longitudinal 2-photon imaging technique in developing mice to assess the impact of THC, CBD, and THC+CBD exposure through three aims. In Aim 1, we will reveal the spatial and temporal patterns of in vivo network activity and eCB dynamics across development and determine critical windows during which altered eCB signaling affects these network dynamics. In Aim 2, we will assess how early-life THC, CBD, or THC+CBD exposure impacts eCB and calcium dynamics during development using longitudinal 2-photon imaging. We will also examine the effects of cannabinoid exposure on synaptic connectivity and the balance between excitation and inhibition in the mPFC. In Aim 3, we will assess the impact of early-life cannabinoid exposure on the neural correlates of cognitive behaviors in the mPFC across adolescence and adulthood. We will also systematically assess the behavioral outcomes after early-life cannabinoid exposure longitudinally across neonatal, adolescence and early adulthood. Together, outcomes of this project will identify neural mechanisms underlying later-life behavioral deficits as a result of early-life cannabinoid exposure. As such, this project is expected to have a significant translational impact on clinical efforts to provide guidelines on cannabis use in mothers and timely interventions for affected children.

NIH Research Projects · FY 2026 · 2024-06

PROJECT SUMMARY Predicting the outcome of a treatment given the pre-operative patient status, i.e., individualized treatment effect (ITE) inference, is of great clinical importance for precise treatment planning. For example, the ITE w.r.t. survival time estimation of glioblastoma (GBM) patients undergoing different treatments enables assessing these possible multi-treatments by answering the question: ”would this patient have lived longer (and by how much), had an alternative treatment been applied?” Improving beyond subjective experience-driven therapy, the widespread accumulation of big medical data offers unprecedented opportunities for the data-driven deep learning (DL) algorithms to learn the underlying causal relations between multimodal depict patient imaging and clinical data, multi-treatments, and corresponding ITE. The practical ITE prediction requires a DL framework, which is largely unavailable at present. The current methods have limitations, including only utilizing the partial and incomplete status depiction, not applicable to multi-treatment on the outcome, and neglecting the ordinal ITE labels. In addition, the lack of reliability information and interpretability in the conventional DL model also hinders its large-scale clinical implementation. We propose to use our previous successful DL model to take both multimodal status and multi-treatments for accurate ITE inference for both factual and counterfactual cases with either continuous or ordinal labels. We will further establish a deep self-training scheme for reliable and interpretable ITE inference with quantified uncertainty and visualized DL-focused pathology region. The overall goal of this project is to develop an accurate, reliable, and interpretable pipeline for ITE inference by leveraging our advanced DL technique, which can be widely generalizable. This concept could significantly advance individualized treatment planning. The overall hypothesis is that the proposed solution can offer a unique opportunity to characterize causal relations among multimodal status depictions, multi-treatments, and corresponding ITEs with the novel DL model, which is not provided by current direct models. In addition, enabling the reliability quantification and interpretation of the underlying patterns of DL decisions could open a new window for ITE outcome utilization and treatment- specific pathology patterns investigation, thus leading to a multitude of new applications. The specific aims of this exploratory proposal are (1) to develop a multimodal multi-treatment DL framework for accurate ITE inference, (2) to establish a deep self-training scheme for reliable and interpretable ITE inference with calibrated uncertainty and visualized 4D (3D+modal) gradient activation. We will apply the proposed DL-based ITE inference framework to the clinical GBM survival dataset with different resections and test it based on various figure-of-merits. Successful completion of the project will provide a clinically applicable DL technique for better assessment and prediction of outcomes with individualized treatment. Using this overall strategy, which is only just now beginning to be explored, DL will play a major role in advising the best interventions.

NIH Research Projects · FY 2026 · 2024-06

PROJECT SUMMARY Alterations in the control of lipid homeostasis can lead to cardiometabolic diseases, including atherosclerosis, the most common cause of mortality in Western societies. Our previous studies have demonstrated the importance of miRNAs in regulating high-density lipoprotein (HDL)-C and LDL-C. Work from our group and others identified miR-33a/b as key regulators of cellular cholesterol efflux and uptake, HDL biogenesis and fatty acid metabolism. Notably, we have recently discovered that miR-33 and the nuclear receptor liver X receptor (LXR) regulates the expression of transmembrane protein 86a (TMEM86a), which is a lysoplasmalogenase that regulates plasmalogen (phospholipid) metabolism. This finding is highly relevant given the key role of these phospholipids as reservoir of polyunsaturated fatty acids, which are the precursors of bioactive lipids that control inflammation resolution. Plasmalogen/lysoplasmalogen content in cells can also regulate membrane fluidity, which may contribute to cytokine-mediated inflammatory responses, efferocytotic capacity, ER stress, lipid peroxidation, and cellular cholesterol efflux in macrophages. Notably, TMEM86a is highly expressed in human and mouse atherosclerotic lesions, suggesting a relevant role for this enzyme in regulating macrophage immunometabolic response during atherosclerosis. Together, these novel findings strongly suggest that LXR/miR-33/TMEM86a signalling pathway might contribute to the chronic vascular inflammation observed in atherosclerotic lesions. To investigate the functional relevance of TMEM86a in regulating macrophage phospholipid metabolism during the progression of atherosclerosis, we have recently generated a mouse model that lack the expression of TMEM86a in macrophages. Using these mice and cutting-edge techniques (genomics and metabolomics), we will elucidate the contribution of LXR/miR-33/TMEM86a pathway in atherogenesis.

NIH Research Projects · FY 2026 · 2024-06

Multi-PI: Titus J. Boggon and David A. Calderwood TITLE: Signaling mechanisms of the cerebral cavernous malformations protein complex ABSTRACT Loss of function mutations in the genes encoding KRIT1 (CCM1), CCM2 (OSM), or CCM3 (PDCD10) cause Cerebral Cavernous Malformations (CCM). The presentation of this disease includes dilated leaky blood vessels, especially in the neurovasculature, resulting in stroke, focal neurological defects, seizures and vascular abnormalities. Each of the multi-domain CCM proteins functions as a molecular scaffold and importantly, CCM2 recruits the MAP kinase kinase kinase, MEKK3, to the multi-protein CCM signaling complex. Recruitment of MEKK3 to the CCM complex is thought to result in suppression of MEKK3 activation of the MEK5-ERK5 pathway and a reduction in KLF2/4 levels. In CCM disease this suppression is lost. Despite extensive research on CCM proteins and their intersection with MEKK3 major gaps in understanding remain, including 1) the fundamental organization of the CCM complex and how this impacts its activity, and 2) the mechanisms by which the CCM complex controls the MEKK3 MAP kinase signaling cascade. In this highly-collaborative, multi-PI proposal the Boggon and Calderwood laboratories will address these outstanding important gaps in knowledge. We will do this in two Aims. In Aim 1, building on extensive preliminary data, we propose a revision of canonical models of the CCM complex and will assess CCM complex stoichiometry as a determinant of signal transduction. In Aim 2, we will discover how CCM proteins act as determinants of MEKK3 signaling outcomes. Our structure-directed functional studies will reveal the normal formation of and define the basis for targeted CCM complex modulation of MEKK3-MEK5-ERK5 signaling.

NIH Research Projects · FY 2026 · 2024-06

PROJECT SUMMARY/ABSTRACT The three-dimensional (3D) genome folding organization within the nucleus of cells plays a key role in epigenomic regulation in both normal physiology and disease. Sequencing-based 3D genomics technologies – such as high-throughput chromosome conformation capture (Hi-C) – have reported systematically altered genome organization in cancer cells. Yet, these studies relied on population averaging of cells and indirect inference of genome organization based on chromatin contacts. As a result, how the genome is folded in true 3D in individual cancer cells in vivo, how this folding organization evolves and is regulated during cancer progression from normal to preinvasive to invasive tumor cells within the native tissue environment, and how alterations in genome organization drive tumorigenesis remain elusive. To address these gaps in knowledge, we applied an image-based 3D genomics method that we pioneered termed chromatin tracing to a faithful Kras- driven mouse model (K-MADM-Trp53) of lung adenocarcinoma (LUAD) and developed the first in situ single-cell 3D genome atlas of any cancer. We observed stereotypical 3D genome alterations during cancer development, including a striking structural bottleneck in preinvasive adenomas prior to progression to LUAD, indicating a stringent selection on the 3D genome early in tumorigenesis. We further found that 3D genome organization correlates with distinct histologic cancer states in single cells and shifts in this organization reveal potential drivers of LUAD progression. In this proposal, we aim to test the hypothesis that changes in the 3D organization of the cancer genome drive tumorigenesis. The studies in Aim 1 utilize a sophisticated multiplexed in vivo CRISPR knockout screen to establish the functional importance of 3D genome-regulated candidate driver genes in LUAD progression and confirm that similar alterations occur in human LUAD biospecimens. The proposed work in Aim 2 uses genetic and pharmacologic manipulation and epigenetic profiling methods (ChIP, CUT&RUN, chromatin tracing) in LUAD cells and mouse models to define how the chromatin-modifying enzyme Rnf2 regulates the cancer 3D genome through a non-canonical function in promoting an active chromatin state. Finally, the experiments in Aim 3 leverage analogous autochthonous mouse models of EGFR-driven LUAD and Kras-driven pancreatic ductal adenocarcinoma to determine how oncogenic driver (Kras vs. EGFR) and tissue of origin (lung vs. pancreas) impact the 3D genome and resultant effects on tumor biology. Together, these experiments will establish how alterations in the 3D genome – as assessed by in situ chromatin tracing – drive context-dependent cancer development, the underlying mechanisms that promote their pro-tumorigenic effects, and their capacity to serve as novel predictive biomarkers for cancer therapy.

NIH Research Projects · FY 2025 · 2024-06

ABSTRACT Alzheimer’s disease (AD) is a major global health crisis, In USA alone 6 million people are diagnosed with AD, and without any breakthrough this number will be doubled in the next 3 decades. While new treatments (e.g. Lecanemab) can extend the self-sustaining life to 5-6 months, effective AD treatment still does not exist, partially because of the lack of comprehensive understanding of the origin and AD development. Cognitive dysfunction has been linked to altered brain function and structure. Recent brain imaging studies of AD patients suggest abnormal brain activity and connectivity, hypometabolism, and loss of cerebral autoregulation, implying sequelae of dysfunctional events occurring within the neurogliovascular unit. The hypometabolism hypothesis of AD is that decrease in glucose metabolism causes insulin resistance which consequently alters amyloid precursor protein processing, causes oxidative stress which lead to mitochondrial dysfunction, and changes the neuronal and glial signal transduction. Technological barriers have limited the possibility of disentangling when exactly neuronal and/or astrocytic dysfunctional events occur in relation to hypometabolism, exhausted cerebral autoregulation, and vascular damage. To unravel the sequelae of neuronal and astrocytic dysfunctions in relation to cerebral metabolism and cerebrovascular health, we propose a novel fusion of optical-MRI to study AD longitudinally. We will conduct multi-modal optical-MRI experiments in mice during AD pathogenesis, specifically with innovative advances that allow significantly higher sensitivity of Ca2+ imaging and with a newly developed multi-wavelength optical system to measure reflectometric hemoglobin signals. Conventional fMRI will track altered functional connectivity and cerebrovascular reactivity, calibrated fMRI will measure flow-metabolism uncoupling, and 3D time-of-flight (TOF) angiography will map damaged macrovessels. Using the reflectometric signals to measure blood volume, and 2D fluorescence imaging to map neuronal (red) and astrocytic (green) activity, and angiography of microvessels (i.e., <40µm) using our green fluorescently tagged magnetic protein nanoparticles (f-MPNPs) which also enables high sensitivity macrovessel (i.e., >40µm) mapping by MRI. Our specific aims are to behaviorally monitor the development of AD to determine the onset of AD, but in conjunction with mapping deficits of neuronal/astrocytic dysfunction in relation to hypometabolism and reduced CBF regulation in AD brain, and microlevel to macrolevel impairments of cerebral vasculature in AD brain in a series of longitudinal experiments. Measures of functional activity and connectivity, cerebrovascular reactivity, metabolism, and vascular health in AD brain will reveal insights of when and where these dysfunctions occur and how distributed they are, information which could guide and track targeted treatments of AD patients. In summary, this is an extremely significant scientific goal because it can reveal neuronal, astrocytic, and vascular interactions underlying AD metabolism.

NIH Research Projects · FY 2026 · 2024-06

Traditional physiologic paradigms focus on 2 fluid compartments, intracellular volume (ICV) and extracellular volume (ECV), in addition to renal sodium (Na) handling to explain Na and water homeostasis. A potential 3rd compartment, where Na is stored without an osmotic effect on ICV or ECV, has recently been popularized. However, this candidate 3rd compartment does not invalidate traditional physiology; it remains true that Na loading will predictably influence ICV/ECV and the kidney will excrete the overwhelming majority of loaded Na. Since only a small fraction of the variance in Na handling can be attributable to the candidate 3rd compartment, measurement error (or measurement omission) of traditional physiologic parameters can be of similar or greater magnitude to the 3rd compartment signal. Likely as a result, essentially the same salt loading rodent experiment has been published multiple times often with different results/conclusions. Notwithstanding the difficulty in studying this question, if a 3rd compartment does meaningfully contribute to Na/water homeostasis, revolutionary biologic and therapeutic insights could be gained by understanding it. However, before we can understand a 3rd compartment, we first need to definitively prove it exists. We propose a comprehensive set of porcine and human studies that will definitively answer 3 primary questions 1) Can a stoichiometrically relevant amount of NaCl be acutely stored or released without water? 2) Is this storage location primarily intracellular or extracellular? 3) Does this physiology apply to humans? Specifically, Aim 1 will establish if significant acutely mobilizable non-ECV sodium storage occurs. We will administer large amounts of NaCl (without significant water) to nephrectomized otherwise normal pigs and measure the change in total ECV osms compared to equal osmolar mannitol, which is known to distribute into ECV and not a 3rd compartment. We will also remove large amounts of Na (without significant water) via peritoneal dialysis with a sodium-free dialysate solution and determine the change in ECV sodium as well. Aim 2 will determine if the non-ECV sodium storage location is primarily intracellular or extracellular. In the above porcine models, we will measure 22Na storage in the skin (primarily acellular) and erythrocytes/skeletal muscle cells (primarily cellular) between the NaCl group and a mannitol control. Aim 3 will determine if significant mobilizable non-ECV sodium storage occurs in humans. We will conduct an ultra- rigorous inpatient balance study with randomized crossover design of 10 patients treated with 5 days of sodium free 5% dextrose (titrated to remove ~150 mmol/day Na without water) added to their standard PD prescription versus a blinded control 1.5% dextrose commercially available PD solution (both minimal Na and water removal). We hypothesize that 5 days of ~150 mmol/day Na removal will result in a large negative sodium balance without significant change in ECV/TBW. Upon completion of this proposal we will have definitively established if water free sodium storage occurs to a physiologically relevant degree.

NIH Research Projects · FY 2026 · 2024-05

Abstract The development of central nervous system (CNS) drugs requires imaging tools that can quantify drug efficacy and target engagement as well as the effects of drug concentration on these quantitative assessment measures. Positron emission tomography (PET) imaging has become standard practice for quantitative assessment, thanks to its ability to image tracers that bind to target receptors of drugs. Receptor occupancy (RO) studies, which consist in a pair of PET scans, baseline and post-drug injection, can be used to quantify, as a function of drug concentration, the blocking effect of a drug. The concentration yielding half-maximum blocking effect, called EC50, is determined by first estimating receptor occupancy for each pair of scans, then fitting a logistic model to the occupancy vs. concentration curve. The conventional method to estimate RO and EC50 consists in reconstructing the dynamic PET data for each pair of scans, perform kinetic fitting, typically in high binding regions, to estimate the binding potential and calculate RO, before performing the logistic fit across concentrations to obtain EC50. The resulting estimates have low precision due to the noise in dynamic PET images and the lack of proper noise modeling. Moreover, estimating single RO and EC50 values discards potentially valuable information on the spatial distribution of RO and EC50. We propose an estimation framework that jointly estimates spatial RO maps for each pair of scans and a global EC50 map using an end-to-end model from the PET measurements to the estimated EC50. The estimation framework relies on advanced optimization strategies to decompose the joint estimation process into manageable subproblems, such as image reconstruction, parametric fitting, image denoising and logistic fitting. The method is expected to improve the estimation of RO and EC50 over conventional methods, while offering additional spatial information. The targeted improvement in estimation would allow to reduce the sample size required in drug trials to achieve the same statistical power as conventional approaches (or conversely, increase the statistical power for a fixed sample size). The method will be validated in numerical simulations and applied to in vivo animal studies.

NIH Research Projects · FY 2026 · 2024-05

PROJECT SUMMARY/ABSTRACT Suicide is a leading contributor to global mortality and rates have remained steady, or increased, in low- resourced settings. South Asia has the highest suicide rate in the world and despite different cultural risk profiles for suicide, little research has explored strategies for health systems to address its growing suicide burden. Given rising suicide rates and growing dissemination of mental health training programs for primary care health workers to treat common mental disorders (the WHO mental health gap action programme, mhGAP), there is critical and urgent need to incorporate implementation strategies for suicide detection, management and follow up within these programs. Community health workers remain an untapped resource to provide suicide prevention support in settings where it is needed most, particularly within overburdened health facilities. Using co-design principals and RE-AIM with primary health workers and a community advisory board, this project will assess barriers to implementing mhGAP suicide modules, then adapt and pilot test a package of strategies to optimize implementation within a decentralized primary care system in Nepal. We anticipate the primary care suicide prevention package (P-SuPP) will include more systematized screening with decision tool aids, the systematic integration of CHW task-shifted safety planning and contact follow-up, supportive supervision, and enhanced digital monitoring systems. The proposed research will in Aim 1 conduct a formative evaluation of current mhGAP suicide practices among clinicians and then co-develop and refine implementation protocols (including workflows, health worker training, and support standards) for integrating suicide detection and follow-up management (P-SuPP) to meet the needs of primary health providers. Aim 2 will complete a pilot feasibility hybrid type 2 randomized controlled trial (RCT) of P-SuPP versus standard mhGAP. We will use mixed-methods to assess trial feasibility and acceptability of implementing and sustaining P-SuPP. We will explore patient-level preliminary effectiveness outcomes including suicidality, depression, and uptake of follow-up care. We will also explore preliminary pilot RCT implementation outcomes including Reach, Adoption, Implementation, and Maintenance of P-SuPP at 6 months for a future fully powered trial. This R34 lays the groundwork for a future R01 to scale a package for suicide prevention strategies that can be integrated into government primary care facilities, particularly targeting individuals living in low-resourced settings. As the model is designed to be easily adapted and integrated, we anticipate the findings will be valuable for all researchers looking to improve population health and mental health services in disadvantaged settings.