Brigham And Women'S Hospital

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY/ABSTRACT Obesity is associated with increased risk of at least 13 cancers. Of all cancers attributable to excess adiposity, colorectum and liver account for 55% of cancer among men and 48% among women, excluding reproductive cancers. Although most epidemiologic studies of obesity as a cancer risk factor evaluated body mass index (BMI), accumulating evidence for colorectal and liver cancers implicates viscerally located adiposity (and its closely related glycemic metabolic dysregulation) as the likely direct causal component. How visceral adiposity mechanistically predisposes its proximal organs to cancer is largely unknown. Inflammation undoubtedly plays a role in development and progression of malignancies, including colorectal and liver cancers; however, the large body of evidence for general inflammation processes and systemic markers like C-reactive protein (CRP) in relation to digestive cancers are underwhelming, possibly because most are non-specific to high-risk metabolically unhealthy obesity per se. Thus, distilling the inflammatory pathways and markers to identify those most reflective of the metabolically unhealthy obese state has immense potential to uncover key mechanisms and inform powerful broad-spectrum strategies for prevention. Techniques to obtain precise measures to characterize metabolically unhealthy obesity are often prohibitively costly and logistically infeasible in the context of large population-based studies. Therefore, we propose an innovative approach to address these gaps by (i) deriving novel proteomic-based inflammation signatures of metabolically unhealthy obesity (“Inflammotypes”) in cohorts with visceral adipose tissue quantified via dual-energy X-ray absorptiometry (DXA) and traits of glycemic metabolic function; then (ii) prospectively investigating these novel Inflammotypes in longitudinal cohorts with stored blood samples in relation to incident colorectal and liver cancer risk. We will characterize Inflammotypes via state-of-the-art Olink proteomic panel (384 inflammation-related proteins) to describe metabolically unhealthy obesity (i.e., higher visceral adiposity, with homeostatic model assessment for insulin resistance [HOMA-IR], hemoglobin A1c [HbA1c], or lipoprotein insulin resistance score [LPIR]). Machine learning analyses to identify the Inflammotypes will be replicated in an external cohort. We will then investigate the relationship between proteomic Inflammotypes with long-term risk of incident colorectal (1000 cases/1000 controls) and liver cancer (500 cases/500 controls), combining longitudinal cohorts with stored baseline bloods and long-term follow-up (median ranges 6.1-16.7 years). Based on compelling preliminary data, we hypothesize the combination of greater visceral adipose tissue and glycemic metabolic dysregulation are associated with abnormal profiles of circulating proteins, and that these novel Inflammotypes are independently predictive of long-term colorectal and liver cancer risks. These aims are closely aligned with the goals of the Metabolic Dysregulation and Cancer Risk Program, including enhancing identification of high-risk individuals, risk prediction, and elucidation of potential preventive and therapeutic targets.

NIH Research Projects · FY 2025 · 2022-09

ABSTRACT Insomnia, present among 15-25% of low-income adults and other overlapping socioeconomically disadvantaged groups such as racial/ethnic minorities, is frequently undertreated, impairs quality of life, and is associated with increased risk for depression, cardiovascular disease, and premature mortality. Our long-term goal is to test the dissemination and implementation of evidence-based treatments for insomnia for socioeconomically disadvantaged adults who face insomnia care inequities. Cognitive-behavioral therapy for insomnia (CBTI) is recommended as first-line treatment. However, CBTI’s real-world adoption is constrained by a limited number of specialty-trained clinicians, treatment time, costs, and language barriers. Brief behavioral treatment for insomnia (BBTI) was developed to expand CBTI’s reach by reducing the time burden (1.5 vs  6 hours) of treatment and clinician training while harnessing the broad workforce and embedded payment models of routine medical settings, such as primary care. Thus, BBTI offers a scalable solution for delivering CBTI’s core behavioral components to socioeconomically disadvantaged patients, who face the greatest barriers to accessing CBTI and have been underrepresented in insomnia research. This study is supported by evidence demonstrating BBTI’s short-term efficacy in improving insomnia outcomes. However, BBTI’s effects have not been adequately compared to CBTI. This application proposes to fill this gap by testing the non-inferiority of BBTI compared to CBTI on insomnia and insomnia-related outcomes in a low-income, diverse sample receiving care in community and academic-based primary clinics across a single site. During the one-year R61 start-up phase, we will conduct foundational work to ensure the R33 clinical trial phase is launched expeditiously and optimally structured to efficiently engage all partners and our target patient population and meet recruitment milestones. The R33 phase consists of a 52-week effectiveness-implementation trial enrolling 350 primary care patients with insomnia who are eligible to receive insurance through a medical assistance program (e.g., Medicaid), speak Spanish, or represent a racial or ethnic minority. We hypothesize that BBTI will be non-inferior to CBTI (defined by a non-inferiority margin of 4 points on the insomnia severity index) at 3-months. Secondary outcomes will include quality-of-life; depression; and diary-reported sleep duration and efficiency; hypnotic use; and adverse events. We will also explore the durability of effects at 6 and 12 months. We will use the Consolidated Framework for Implementation Research to explore patient- and clinic-level contextual factors influencing implementation to inform future strategies. By concurrently testing the effectiveness and investigating implementation factors, this proposal will lay the foundation for subsequent implementation trials testing the broad uptake of evidence-based behavioral insomnia treatments. Thus, the information gained for the proposed work would directly advance the treatment of insomnia for underserved groups along the translational continuum, strongly aligning with the goals of this RFA.

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY (Overall) Chronic pain affects >25 million Americans per year, with enormous impacts on both quality of life and productivity. Despite advances in our understanding of nociception in animal models, new and effective treatments for patients with chronic pain have been lacking. The poor translation between mouse and human pain targets has highlighted limitations of animal models of pain. Recent advances in single-cell genomics and physiology directly in human tissue position pain researchers to make important new advances with improved opportunities for clinical translation. The Harvard PRECISION Human Pain Center proposes to leverage state- of-the-art single-cell technologies to characterize human nociceptor subtypes and how their gene expression patterns vary across diverse populations (Project 1) as well as in chronic pain conditions that clearly localize to these cells – chronic phantom limb pain associated with painful neuromas (Project 2). The Projects will generate a wealth of data for the scientific community by closely integrating with 5 Cores tasked with 1) procuring high- quality human pain-related tissues following strict regulatory practices, 2) offering the latest single-cell gene multi-omic technologies, 3) performing advanced single-cell spatial transcriptomic analysis, 4) managing, integrating, and distributing all of the data, and 5) administrating and connecting to Center the other PRECISION Human Pain Network Centers. The data generated by our Center will contribute to this broader PRECISION Human Pain Network and to help identify and prioritizate of novel pain therapeutic targets for future investigation.

NIH Research Projects · FY 2025 · 2022-09

Project Summary New treatments are needed for bipolar disorder (BD). Transcranial magnetic stimulation (TMS) shows promise for BD, but the optimal treatment targets for mania, depression, and mood stabilization are unknown. Studying brain lesions that cause BD symptoms provides causal insights into neuroanatomy. These causal insights are critically important for target identification. Lesion network mapping (LNM) leverages the human connectome to map brain lesions onto brain networks rather than single brain regions, enhancing lesion localization and target identification. Pioneered by the Fox lab (Mentor), LNM shows promise for optimizing TMS targets for unipolar depression. Two recent Fox lab studies used LNM to examine the brain circuitry causally implicated in mania (n=56, two datasets) and depression (n=461, five datasets). However, there are two critical limitations of this prior work. First, mania and depression were analyzed as independent states rather than opposing poles of a valence spectrum in BD. This limitation will be addressed with a single model analysis of mania, depression, and control lesions. Second, these studies did not validate targets in patients with BD. This limitation will be addressed by validating lesion-derived targets in patients with BD using functional neuroimaging and behavioral testing. Aim 1 is to derive and validate TMS targets for mood valence. These valence-specific targets will be derived with LNM contrasts of mania vs. depression (and vice versa) in an a priori prefrontal cortex mask, and the results will be validated by correlating their whole-brain connectivity to task-based measures of valence bias in patients with BD. Aim 2 is to derive and validate a TMS target for mood stabilization. This valence-nonspecific target will be derived with LNM contrasts of mania plus depression vs. controls in an a priori ventrolateral prefrontal cortex mask, and the resulting target will be validated by correlating its whole-brain connectivity to a task-based measure of emotion regulation in patients with BD. This study aligns with the NIMH 2020 Strategic Plan objective of developing novel tools with which to characterize brain networks causally implicated in affective processes. A follow-up R01 or R61/33 grant examining whether TMS alters behavioral metrics, functional connectivity, and clinical outcomes in patients with BD aligns with NIMH’s experimental therapeutics approach. This grant was designed to provide the stepwise scientific training necessary to fulfill this plan, from LNM and biostatistics to translational research involving phenotyping and imaging of patients with BD. It also fits well with the long-term goal of becoming an independently funded physician-scientist who leads an Interventional Psychiatry research program primarily focused on deriving, validating, and testing circuit-based TMS targets. With this goal in focus, there is no better place to train than Brigham and Women’s Hospital, a Harvard Medical School affiliate offering world-class mentors, a robust TMS service in the Center for Brain Circuit Therapeutics, Harvard Catalyst Clinical/Translational Science Center, and Athinoula A. Martinos Center for Biomedical Imaging.

NIH Research Projects · FY 2024 · 2022-09

ABSTRACT Over 50 million Americans experience tinnitus. Persistent tinnitus can cause considerable suffering and disability, impairing sleep, cognition, mental health and daily function, and the economic burden due to disability, lost productivity and healthcare costs is substantial. However, little is known about the precipitants and pathways that lead to persistent tinnitus and treatment options are limited. Our long-term goal is to identify treatment targets and preventative strategies to reduce tinnitus burden and improve quality of life. Our overall objectives are to (i) identify novel metabolomic and multi-omic risk factors for the development of tinnitus among two large longitudinal cohorts of women (N>26,000); and (ii) collect tinnitus-related individual level data in two additional ongoing cohorts of younger and more diverse men and women (N>70,000). Our central hypotheses are that specific plasma metabolites are associated with risk of developing tinnitus and that genetic variants influence how environmental exposures contribute to the development of tinnitus. The rationale is that identifying risk factors for tinnitus will provide a strong scientific framework for improving tinnitus management, and expanding data collection to include younger individuals will create a comprehensive resource that will enable studies of genetic and environmental factors and will be invaluable in advancing future tinnitus research. The study objectives will be addressed in three specific aims: 1) Identify plasma metabolomic risk factors for developing persistent tinnitus; 2) Evaluate genomics and gene-environment interactions as risk factors for developing persistent tinnitus; and 3) Collect tinnitus information in two ongoing cohorts of younger individuals. We will leverage rich assets from four longitudinal cohort studies and findings from two large tinnitus genome-wide association studies (GWAS). In Aim 1, we will use logistic regression to identify novel metabolomic risk factors for developing tinnitus. In Aim 2a, we will conduct a GWAS and perform a meta- analysis with published tinnitus GWAS results from the UK Biobank. In Aim 2b, we will assess how genetic variations in enzymes responsible for caffeine and analgesic metabolism modulate associations between caffeine intake or analgesic use and tinnitus risk. In Aim 3, we will leverage regularly administered questionnaires in 2 well-characterized younger cohorts to collect detailed tinnitus information. This innovative proposal integrates omics with epidemiological data to identify new risk factors for tinnitus, improve understanding of tinnitus etiology and reveal metabolic pathways and candidate genes for future functional follow-up. The proposed research is significant because identifying risk factors and omics precursors may enable earlier neuroprotective interventions when treatments are more likely to be effective. As an early-stage investigator, this project will provide me with necessary preliminary data for a future R01 proposal to extend these large-scale multi-omics investigations of tinnitus, identify additional novel risk factors, and uncover new treatment targets in women and men across the lifespan, and advance my career to the next stage.

NIH Research Projects · FY 2025 · 2022-09

ABSTRACT Obstructive Sleep Apnea (OSA) is a common disorder with serious health consequences that often remains undertreated due to few therapeutic options beyond continuous positive airway pressure (CPAP). Alternative treatments are available, such as mandibular advancement devices (MADs) and hypoglossal nerve stimulation (HGNS). However, these treatments are not always effective, and the predictors of success are poorly understood or difficult to obtain. Furthermore, patients who fail these therapies are often left untreated and therefore susceptible to the clinical consequences of OSA. In the previous grant period, we developed methods for estimating the pathophysiological endotypes of OSA (pharyngeal collapsibility, loop gain, pharyngeal muscle compensation, and arousal threshold), as well as the primary site of airway collapse (palate, tongue, lateral walls, epiglottis), from the clinical polysomnogram (PSG). The objective of this grant is to apply these methods to 1) find predictors of MAD and HGNS response and 2) test endotype-specific pharmacotherapies in MAD and HGNS non-responders. Our hypothesis is that these endotypes/sites of collapse, as determined from the PSG, are important predictors of MAD and HGNS response. We also hypothesize that the addition of a drug targeting an abnormal endotype, e.g., high loop gain, can be used to more effectively treat MAD and HGNS non-responders. In the first two aims, the physiological endotypes and sites of collapse will be determined from the clinical PSG using the methods developed in the previous grant cycle. Patients will then undergo MAD (Aim 1) or HGNS (Aim 2) therapy. A follow-up PSG will be performed to evaluate the success of treatment. Using multivariable logistic regression, the significant physiological predictors of success will be determined. In Aim 3, the patients who fail MAD or HGNS in the previous aims, approximately one-third of individuals, will be treated with a drug targeting the most abnormal endotype (acetazolamide for high loop gain, atomoxetine-plus-oxybutynin for poor pharyngeal muscle compensation, or trazodone for low arousal threshold). Recent evidence suggests that these drugs can manipulate the endotypes. The drug will be administered concurrently with MAD or HGNS treatment (combination therapy). Aims 1 and 2 are expected to find the important physiological predictors of MAD and HGNS response, respectively, using novel metrics derived from the clinical PSG. Aim 3 is expected to provide proof-of-principle for a pharmacologic approach to treating MAD and HGNS failures, patients who otherwise have limited treatment options. Ultimately, these studies have the potential to improve patient selection for non-CPAP alternatives and broaden the treatment options for OSA.

NIH Research Projects · FY 2025 · 2022-09

Abstract In this 5-year R01 project entitled “Harmonizing data acquisition, reconstruction, and analysis for reproducible, cross-vendor, open-source MRI,” we address the significant barriers to scientific progress due to the large inter- scanner variability (often more than 10-20%) present in multi-site MRI data which substantially diminishes the power of neuroimaging studies to detect subtle pathologies in neuropsychiatric disorders. Inter-scanner biases are a result of differences in implementation of closed-source product sequences (e.g., gradient and radiofrequency pulse shapes and timing), the choice of reconstruction algorithms, as well as variations inherent to the scanner hardware (e.g., gradient strength). Another major challenge is the significant barrier to develop new sequences for each vendor separately. This inhibits the translation of new MRI technologies to research laboratories, as vendor-specific sequence development environments are closed-source, proprietary, and suffer from a steep learning curve. In this project, we address these challenges by proposing an “end-to-end” harmonization framework. We propose to develop and disseminate a single open-source vendor-neutral MRI pulse sequence development environment containing both standard MRI protocols (e.g., T1-weighted, T2-weighted, and diffusion MRI) and cutting-edge quantitative acquisitions (T1, T2, T2*, and quantitative susceptibility maps (QSM)), a unified image reconstruction framework, and novel algorithms for post-acquisition data harmonization to enable multi-site reproducible research and mitigate inter-scanner variability and bias. Our quantitative MRI acquisitions will be efficient (5 min as opposed to more than 15 min) and also comprise of fast, distortion-free diffusion MRI sequences. The performance of standard contrast-weighted protocols and the accuracy of novel quantitative imaging sequences will be rigorously validated on phantoms and in-vivo data acquired from all major vendors (Siemens, Philips, GE). Further, we will develop and validate novel data harmonization algorithms that will remove any remaining scanner-induced discrepancies in the data due to hardware differences. One of the goals of this project is to reduce inter-scanner variability to the level of those observed within-scanner. The technical developments proposed in this grant will dramatically increase reproducibility across sites and allow for seamless execution of multi-site neuroimaging studies. Thus, the increased statistical power of multi-site studies will facilitate detection of subtle changes in neuropsychiatric disorders. Our open-source first-of-its-kind platform will also accelerate cross-vendor sequence development and enable immediate translation of new sequences into research studies (which currently takes several years).

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY Type 1 Diabetes (T1D) is an autoimmune disease affecting over 1.6 million people in the United States, and more than 5 million Americans are expected to be diagnosed with T1D by 2050. Clinical T1D is preceded by an occult period of autoimmune beta cell loss and dysfunction. Disease prediction can be performed for clinical trial purposes, with a combination of islet autoantibodies, genetic markers, and metabolic markers. However, the predictive ability in the short term, particularly early in the disease or as an early marker of response to therapy, is often inadequate. This results in needing longer and more extensive clinical trials for T1D interventions. Islet- derived exosomes (or small extracellular vesicles produced by pancreatic beta cells or nearby cells within the peri-islet environment) may reveal beta cell dysfunction and islet inflammation and are believed as promising biomarkers for early detection and monitoring of T1D, but little has been explored yet. Thus, there is an urgent and unmet need to identify and characterize islet-derived exosomes for the early detection of T1D, particularly during the asymptomatic phase. Our overall objective is to create an integrated exosome isolation and analysis system for the high throughput screening and identification of islet-derived exosomal markers with the rapid purification and specific detection of islet-derived exosomes in T1D. The rationale for the proposed work is to screen for pancreatic islet-specific exosomal markers and further develop an Exosome Technology with Optoelectronics Lab-on-chip (EXTOL) system for rapid and specific capturing and analyzing islet-derived exosomes in T1D. Then, we will validate the EXTOL system and screened exosomal markers using clinical samples from T1D patients and appropriate controls. The ultimate product of this study is to provide a new platform to screen, identify, and analyze exosomal markers for rapid and specific detection of asymptomatic T1D.

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY Early detection of Alzheimer’s disease and related dementias (ADRD) from electronic health records (EHRs) can facilitate participant enrollment in clinical trials and early intervention once clinically available. Subjective cognitive decline (SCD) can be an early manifestation of ADRD. Previous research in early detection of ADRD has focused on observational study cohorts, generally small in size and often with stringent medical exclusion criteria. Investigation of larger and more representative samples is needed to develop a full understanding of the underlying conditions, procedures, and/or interventions that can contribute to cognitive decline or accelerate progression to dementia in the population at large. The overall goal of this proposed research is to leverage large-scale EHR data and advanced informatics technology to develop case-finding methods for SCD and to advance the understanding of its risk factors and dementia outcomes in older adults. Preliminary data suggest that clinical notes and machine learning (ML) algorithms can be helpful to capture patients with early cognitive decline. However, identifying which patients with SCD are more likely to develop dementia is extremely challenging. During the K99 phase, the first aim will be to develop an informatics approach to identify a pre-dementia cohort (patients with evidence of a cognitive concern but no dementia). The second aim will identify the social and clinical characteristics of this cohort in the EHR, along with antecedent risk factors, and predictors for a dementia outcome. The two hypotheses are that 1) clinical conditions (eg, neuropsychiatric disorders, cardiovascular diseases, renal disease, respiratory infections, sleep disorders) and medications that deleteriously affect cognition will contribute to the initial appearance of cognitive decline; and 2) longitudinal, multimodal EHR data can be leveraged in ML models to stratify patients with high risk of dementia. To accomplish these goals, the applicant will leverage existing strengths in case identification, risk factor analyses, and prognostic modeling and gain additional knowledge and skills in three critical areas of training: (1) cognitive decline and ADRD, (2) clinical epidemiology, and (3) statistical methods. With the development of these skills, the applicant will be well positioned in the R00 phase to conduct the final aim: to study the antecedent risk factors and outcomes of SCD in a presumed SCD cohort (patients with both a subjective cognitive concern and normal performance on objective cognitive measures). Similar approaches to those used in the second aim will be employed to study the presumed SCD cohort. A highly innovative component of this project is the use of advanced artificial intelligence and large-scale EHR data for presumed SCD cohort identification, risk factor analyses, and early detection of dementia. The proposed study will provide some of the first insights into the characteristics and risk factors of SCD in the EHR, and predictors for dementia outcomes in SCD. For the applicant, this program will support a rapid transition to independence through a short period of intensive training and mentorship, which will seamlessly intertwine with the aims of the proposed project.

NIH Research Projects · FY 2024 · 2022-09

This Administrative Supplement targeting complementary and integrative health (CIH) practitioners seeks support to enhance the research capabilities of Dr. Wren Burton, MPH, DC. The proposed award targets a critical phase in Dr. Burton’s career trajectory, aiming to facilitate her transition to an independent clinician-researcher and to be competitive for a future NIH career development award to advance her independence. Dr. Burton’s research interests focus on multimodal chiropractic care (MCC) for older adults with chronic pain, aligning with NCCIH priorities. This award will support Dr. Burton’s time to serve as a study team member for our NCCIH-funded R34 trial, which will afford her with essential hands-on training in clinical trial conduct. The parent award evaluates combined MCC and Tai Chi for chronic nonspecific neck pain (CNNP). Phase I established treatment regimens through a Delphi process, while Phase II will investigate feasibility and participant experiences while optimizing data collection processes. Dr. Burton’s participation in this trial offers a unique opportunity to hone her skills in clinical trial design, IRB protocols, participant recruitment, outcomes assessment, safety monitoring, and data management, while addressing a topic central to her research interests. In addition to primary hands-on learning in the parent award, she will engage in three related and complementary training activities with her mentorship team. These include 1) completing data analyses and publishing multiple peer-reviewed articles related to an observational study of CNNP and gait health (same study population as parent award), 2) contributing to the design and initial conduct of an adjunct neuroimaging pilot study employing the same combined MCC and Tai Chi interventions for CNNP as the parent award, and 3) drafting a competitive K23 application. The proposed activities will substantially extend Dr. Burton’s hands-on experience in clinical trial conduct, enrich her data management/analysis skills, strengthen her writing of peer reviewed manuscripts and grants, and introduce her to the fundamental neuroimaging research. This training will significantly contribute to the development of Dr. Burton as an independent clinician researcher and further enhance the CIH research community.

NIH Research Projects · FY 2025 · 2022-09

Summary The blood-brain barrier prevents most drugs from reaching the central nervous system and is one of the biggest problems in developing new effective therapies for patients with brain tumors, neurodegenerative diseases, and other disorders. The use of ultrasound in combination with injected microbubble agents has emerged as a prom- ising method to temporarily disrupt the barrier. After over a decade of preclinical studies in animals, multiple commercial systems have been developed and clinical trials have begun. Early experience with these trials have shown several problems that were predicted by the preclinical work. The clinical treatments use lower doses of microbubbles, have to overcome the variable attenuation of the human skull, and are often in white matter. As a result, treatments have been suboptimal. The purpose of this proposal is to provide a roadmap to clinical success for ultrasound-mediated blood-brain barrier opening. We will develop new treatment planning methods that ac- count for the human skull, electronic steering of the focused ultrasound beam, and variations in microbubble concentrations in different tissue structures. These methods will be employed to improve safety and control of the procedure. Next, we will investigate whether we can improve our ability to control the procedure in white matter targets and evaluate the safety of repeated blood-brain barrier disruption in white matter targets. Finally, using what we have learned, we will investigate whether we can deliver sufficient drugs to treat a highly infiltrating tumor model. If successful, this work could have a significant impact on future use of this exciting technology.

NIH Research Projects · FY 2025 · 2022-09

Infection due to Hepatitis C virus (HCV) is a current global health burden and it is estimated that globally more than 58 million people have chronic HCV, with about 1.5 million new infections occurring per year. If left untreated, HCV infection can lead to cirrhosis and hepatocellular carcinoma. Despite significant recent advances in the development of highly effective and affordable HCV treatment, one of the major challenges in HCV infection management is rapid and early diagnosis of active HCV infection, particularly in resource-limited settings. Worldwide, only 21% of HCV-infected people are diagnosed. The two-step HCV testing process of HCV antibody testing followed by confirmatory HCV RNA testing is expensive, time-consuming, and suboptimal, which has led to significant drop-out of HCV-infected individuals from the cascade of HCV management before receiving care. The HCV antibody testing cannot be used for detecting active infection due to its inability to distinguish between resolved HCV (R-HCV) and viremic HCV (V-HCV). The currently available HCV RNA testing assays, including the POC HCV RNA assays, are still lab-based and expensive and may not be available in most resource-limited settings. Low-cost, rapid, sensitive, and specific POC HCV antigen testing is an attractive alternative approach that holds great promise for one-step HCV screening and diagnosis. There is currently no commercially available and FDA-approved POC HCV Ag testing device. The already developed HCV Ag assays are lab-based, relatively expensive, and more importantly not sensitive/specific enough, particularly when tested with samples with clinically relevant low viral loads (<1000 IU/mL), which has limited their clinical utilities. The Abbott Architect HCVcAg assay had a sensitivity of 64.7%–81.9% when tested with HCV serum samples with <10⁴ IU/mL viral loads and 0.0%–19.7% when tested with HCV serum samples with <1000 IU/mL viral loads. Therefore, to increase access to HCV care in under-resourced populations, there is an urgent need for inexpensive, rapid, sensitive, and specific POC HCV Ag diagnostic testing. The main goal of this interdisciplinary project is developing a smartphone-based diagnostic system for rapid (<30 minutes) and sensitive (LoD of 200 IU/mL to 1000 IU/mL) HCV detection using fingerprick volume (<100 µL) of a whole blood sample placed on an inexpensive (<$2 material cost), disposable, and mass-producible microfluidic-based cartridge. We will validate the proposed device with HCV-infected patient blood samples.

NIH Research Projects · FY 2025 · 2022-09

ABSTRACT This K23 proposal describes a five-year research and training plan to facilitate Dr. Katherine Bell’s transition into an independent physician-scientist in the field of neonatal nutrition. Dr. Bell is a neonatologist with a strong foundation in patient-oriented research. Nutrient deficits occurring during the neonatal intensive care unit (NICU) hospitalization impair preterm infants’ growth and maturation during a critical period for development of the body and brain, adversely impacting long-term neurodevelopmental outcomes. The essential micronutrient zinc is crucial for infant growth and brain development, but the optimal zinc intake for preterm infants is unknown and current fortification strategies may be insufficient. Accurate assessment of nutritional status in preterm infants is facilitated by distinguishing lean mass—which reflects organ growth and maturation—from fat. The goal of this proposal is to determine the association between zinc intake in the NICU and lean mass accrual (as a marker of nutritional status) and to evaluate the clinical impact of variabilities in zinc intake on concurrent brain development and later neurodevelopmental outcomes. The hypothesis that greater zinc intake results in greater lean mass accrual, improved brain growth and maturation, and improved neurodevelopment will be tested through 3 specific aims: 1) Determine the association of zinc intake in the NICU with lean mass at term equivalent age. 2) Determine the association between zinc intake in the NICU and brain growth and maturation. 3) Determine the impact of neonatal zinc intake on neurodevelopmental outcomes at 2 years. This research is significant for the field of neonatal nutrition, as knowledge gained from this study will help determine optimal zinc intake for preterm infants and inform the design of nutritional strategies to ensure adequate micronutrient provision to all preterm infants. Dr. Bell’s mentoring team—Dr. Belfort (primary mentor) and Dr. Duggan (co-mentor)—provide complementary expertise in preterm infant nutrition and micronutrient requirements in children, respectively. Dr. Bell will also receive mentorship from distinguished scientists with expertise in key areas related to this work, including micronutrient biochemistry, breastmilk composition, neurodevelopmental assessment in childhood, and the developmental origins of disease. The training opportunities and resources at Brigham and Women’s Hospital, Tufts Friedman School of Nutrition Science, and Harvard Medical School are an ideal environment for the candidate’s career development. The candidate’s institution is strongly committed to her success. Dr. Bell’s detailed career development plan includes mentored research, didactic coursework including a formal degree in nutrition science, seminars, and presentations at scientific meetings. She presents a timeline for completion of the research aims and preparation of a future R01 application. The knowledge and training gained from this K23 award will enable Dr. Bell to develop the skills and expertise required to launch an independent research career focused on designing micronutrient interventions to optimize growth and long-term health outcomes for preterm infants.

NIH Research Projects · FY 2025 · 2022-09

Project Summary / Abstract Successful HIV treatment programs in Botswana and elsewhere in southern Africa have led to dramatic reductions in mortality from tuberculosis, cryptococcosis, and other non-cancer AIDS deaths. However, cancer deaths have not decreased, and cervical cancer now is the leading cause of death for women living with HIV in the region. Cervical cancer is preventable with early detection and treatment of precancerous lesions but challenges of limited access to initial screening, poor performance of initial screening technologies, high prevalence of cervical precancers, and persistent or relapsed dysplasia following therapy impair the impact of programs for women living with HIV. Working to develop strategies to these challenges, we will establish the Botswana CASCADE Clinical Trials Site at BHP that will participate in and contribute to the following high- impact areas of research: 1) Enhancing cervical precancer screening uptake through patient and context relevant approaches, including HPV self-sampling, non-clinical screening venues, and screening during antenatal care; 2) Strategies and novel technologies to improve management of positive HPV initial screening maximize prevention of invasive cancer while minimizing patient risk and consumption of health system resources; 3) Improving precancer treatment access, treatment completion, and outcomes; and 4) Optimizing treatment approaches to cervical precancers including comparative trials of ablation techniques, intervals of repeat evaluation, and vaccines or other immunologic therapies. The Botswana CASCADE Clinical Trials Site will contribute to conducting high-quality clinical research studies, provide context-relevant input on developing trial concepts, understand disparity in access by geography, economic factors, and language/ethnicity, and continue to develop local research capacity through mentoring and training.

NIH Research Projects · FY 2026 · 2022-09

The most common bacterial infections during pregnancy include urinary tract infections, cellulitis and skin abscesses, upper and lower respiratory tract infections, and sexually transmitted diseases. Management of bacterial infections in pregnant women requires early antimicrobial treatment to prevent adverse maternal and pregnancy outcomes. As such, antibiotics are among the most commonly used medications in pregnancy – approximately six out of ten publicly insured and four out of ten commercially insured pregnant women fill at least one antibiotic prescription during pregnancy. To select the optimal antibiotic from the range of available options for specific infections, it is therefore crucial to understand the comparative safety of in utero exposure to specific antibiotics. Unfortunately, rigorous and comprehensive safety data to inform the risk-benefit trade-off are sparse and evidence is conflicting. The primary concern among potential risks associated with antibiotic use in pregnancy are congenital malformations, which are a leading cause of neonatal morbidity and mortality, and frequently cause lifelong disability. Additionally, some studies have pointed to an increased risk of spontaneous abortions and neonatal jaundice associated with some commonly used classes of antibiotics. Given that 45% of pregnancies in the US are unintended, understanding the comparative safety of antibiotics in early pregnancy may also inform the selection of antibiotics in women of reproductive age. The objective of the proposed studies is therefore to evaluate the comparative safety of antibiotics commonly used for the treatment of bacterial infections during pregnancy. To accomplish this, we will employ large pregnancy cohorts of publicly and privately insured pregnant women (N ≈ 4.5 million). For each of the most common bacterial infections, we will assess the comparative safety of available commonly used antibiotic treatment options and utilize the rich information in our data sources to control for potential confounding variables. The large study size will enable quantification of effects for the pre-specified outcomes (i.e., malformations overall, specific malformation types, spontaneous abortion, and neonatal jaundice) with great precision. In addition, to ensure a comprehensive evaluation of the comparative safety, we will utilize a novel signal detection method developed by members of our team, TreeScan, for simultaneous evaluation of a broad range of potential maternal, fetal and neonatal adverse outcomes. By harnessing the power of existing real-world data, this study will inform strategies for tailoring antibiotic treatment to optimize pregnancy outcomes in this vulnerable population. As such, the proposed study aligns well with the main goal of PAR-20-300. By defining the safest treatment options for women of reproductive age with bacterial infections, the findings of this study will have direct and immediate clinical impact.

NIH Research Projects · FY 2025 · 2022-09

Abstract Tuberous sclerosis complex (TSC) is an autosomal dominant disorder caused by germline loss-of-function mutations in TSC1 or TSC2. Renal disease, which includes cysts, angiomyolipomas, and renal cell carcinoma, is a major source of morbidity and mortality for both children and adults with TSC. mTORC1 inhibitors have partial, cytostatic effects on TSC-associated tumors, so continuous and potentially lifelong therapy is required, often beginning in early childhood. The death of two children from serious infection in a recent trial of mTORC1 inhibition for TSC highlights the unmet need for novel therapies that eliminate TSC-associated tumor cells. The TSC1/TSC2 protein complex inhibits mTORC1. Multiple components of the TSC signaling network can localize to the lysosomal membrane, including mTOR, Rheb, TSC1, and TSC2. Lysosomes are highly dynamic organelles with both degradative and signaling functions. We have found that nuclear levels of the transcription factor TFEB, a master regulator of lysosomal biogenesis, are elevated in TSC1-deficient and TSC2-deficient cells, in a mouse model of TSC renal disease, and in human TSC tumors. This is unexpected, because mTORC1 phosphorylates TFEB and TFE3, leading to their cytoplasmic sequestration. We have also found that TFEB is required for the proliferation of TSC2-deficient cells, in vitro and in vivo. These and other preliminary data lead to our central hypothesis that hyperactivation of TFEB and TFE3 leads to a lysosome-dependent increase in cell proliferation in TSC. This hypothesis will be tested in three Aims: Aim 1. To identify the mechanisms of nuclear localization of TFEB and TFE3 in TSC2-deficient cells. Aim 2. To identify compounds that induce TFEB and TFE3 to move to the cytoplasm in TSC2-deficient cells. Aim 3. To determine the in vivo impact of TFEB and TFE3 on cell proliferation and renal cystogenesis in TSC. We expect this project to have scientific and preclinical impact by elucidating the roles of TFEB and lysosomal biogenesis in TSC-associated renal disease, with the potential for clinical translation to prevent and/or eliminate TSC-associated renal tumors.

NIH Research Projects · FY 2025 · 2022-09

Abstract Gene expression programs are dynamically regulated by the accessibility of chromatin for transcription factor (TF) binding, but how TFs recognize specific regulatory regions occluded by nucleosomes remains unclear. Certain TFs, termed pioneer factors, can recognize their target sites within nucleosomes, leading to the opening of chromatin. By priming cis-regulatory elements for subsequent transcriptional regulatory activity, pioneers serve as gatekeepers to cellular differentiation. Although pioneers can bind nucleosomal sites, they bind only a subset of their potential recognition sites in the genome that typically varies across cell types, thus indicating their interplay with sequence, epigenetic or other cellular features. Despite the importance of pioneer factors, what restricts pioneer binding is poorly understood. Little is known about how the sequence context of their sites in nucleosomes, the presence of histone variants or post-translational modifications (PTMs) of histones, or interactions with cofactors or chromatin readers that recognize those PTMs might influence pioneer binding to nucleosomes. No high-throughput technologies have been developed to survey the impact of these many parameters on TF pioneer binding. In this project, we will develop novel, high-throughput biochemical assays to investigate how nucleosomal sequence context, histone variants or histone PTMs influence pioneer binding of human TFs to nucleosomes. We will also investigate the interplay of pioneers, cofactors, and chromatin readers in pioneer binding. Results from these biochemical assays will be validated in vitro and used in analysis of in vivo genomic data in human cells to understand how these various features contribute to TF pioneer binding in cells. As pioneer factors play crucial roles at the top of regulatory hierarchies, these results will aid in understanding how gene regulation of cell states is encoded in the genome and the mechanisms by which it is read out.

NIH Research Projects · FY 2025 · 2022-09

Functional status—a summary of a patient’s physical, emotional, and social wellbeing—is a key index of disease risk, treatment outcome, quality of life, and overall healthcare usage across a wide range of clinical settings and patient populations. Especially in older patients with chronic pain, accurate functional assessments are critical for detecting age-related treatment side effects, disability, and decline. In older patients, pain is a leading, difficult-to-treat cause of disability that interferes with function and independence; however, many older patients lack access to or are unable to participate in traditional models of care. The lack of frequent, remotely available assessments of functional status is a clear barrier to improved patient care. Digital devices promise to remotely capture real-time, real-world patient function and to inform clinical decisions in objective ways that are not now possible. Our team has shown that ubiquitous smartphones capture facets of functional status, but it is not known how separate measures might combine to form a concerted digital biomarker profile. Similarly, although 80% of Americans in their fifties and sixties own and use smartphones, the existing clinical ecosystem only uses these devices to coordinate face-to-face visits by teleconference. To impact and expand access to clinical care, a digital biomarker profile must demonstrate clinical utility (through scientific study) and usefulness (through engineered service design). We have created the Pain Intervention and Digital Research (Pain-IDR) program, a research clinic designed to foster digital integration with clinical care. Overall, we present a unique opportunity for transformative work, providing a real-world clinical setting to develop and test workflows that maximize the utility of digital devices in two parallel aims: first, we will use patients’ own smartphones to define High-frequency Ecological Recordings of Mobility, Emotion, and Sociability (the HERMES phenotype). Second, we will partner with industry experts to engineer a clinical service design that implements the HERMES platform into the Pain-IDR workflow and will pilot decision support models in real-time, real-world patients. To meet these research goals, I require formal training in longitudinal digital biomarker development, clinical program administration, and entrepreneurship. The primary mentoring team (Drs. Silbersweig, Insel, and Onnela) has extensive expertise in biomarker development, program administration, and entrepreneurship. Other key collaborators provide specific expertise in digital phenotyping (Dr. Baker) and health policy (Dr. Ahern), while consultants offer mentoring in program administration (Dr. Grossman), industry externships (Dr. Basu, Ms. Mazzone), and commercial digital health platform development (Mr. Barber and Mr. Whelan). Five years from now, we expect to deliver the HERMES phenotype as a candidate digital biomarker of functional status and, in parallel, the HERMES platform as viable toolset that integrates digital measures to support clinical decisions, to be further developed in future SBIR-supported projects.

NIH Research Projects · FY 2025 · 2022-09

Volatile anesthetics, such as isoflurane, produce all stages of general anesthesia including unconsciousness, amnesia, analgesia and muscle relaxation. Despite their ubiquity, the fundamental mechanisms of action of these drugs remains unknown. Elucidating the mechanisms by which clinical anesthesia is produced is the foundational unanswered research question in the specialty of anesthesiology. The routine use of volatile anesthetics is not without clinical risk. Multiple exposures to anesthetics in infancy leads to possible behavioral problems in later life, and persistent post-operative cognitive dysfunction is seen in the elderly after anesthesia. Historically, research in this field has proceeded along two tracks: either molecular analysis looking for specific receptors for the volatile anesthetics (an approach that has largely foundered due to diffuse interactions with many receptors whose effects do not combine appropriately), or the gross measurement of neuronal activity in entire regions of the brain using EEG and fMRI (which are fundamentally limited by resolution). Clearly, there is an enormous gap in length resolution between synaptic-scale and EEG-scale. We hypothesized that the onset of anesthesia, and hence the loss of consciousness, is due to disruption in the communication between neurons at the level of small neuronal networks that lie well below the resolution limit of EEG and fMRI. We study the effect of anesthetic agents on intercommunication within intact, living neural networks, with single neuron resolution. We use C. elegans, the creature with the simplest, most tractable neuronal architecture in which anesthesia is known to be inducible. Using light-sheet microscopy, a combination of fixed and calcium- sensitive fluorophores expressed under neuronal promoters, and our customized supercomputing toolchain for image analysis and signal extraction, we track and capture the activity of essentially the entire nervous system and examine its behavior under varying levels of anesthetic exposure normalized to comparable levels used in human surgery. Using two-photon imaging, we are able to perform similar experiments in the mouse and extract activity from selected regions of the somatosensory cortex in both awake and anesthetized states. We will use a system of differential expression of fixed neuronal fluorophores in C. elegans to allow the precise identification of individual neurons under light-sheet imaging. In combination with the C. elegans connectome, we will determine the neuronal pathways that underlie anesthetized vs conscious states, how anesthetics alter chemical and electrical synaptic connections to induce these states, the changes in neuronal connectivity that permit the anesthetized state to resolve back into consciousness, and hence delineate the mechanisms of clinical post-operative cognitive dysfunction in the old and neurodevelopmental impairment in the young. We will extend our imaging and analysis techniques into vertebrate zebrafish, building a phylogenetic bridge in the action of anesthetics from simple creatures to humans. We will demonstrate that these changes in neuronal activity are consistent with the gross statistical hallmarks of anesthesia seen in the EEG in humans.

NIH Research Projects · FY 2025 · 2022-09

SUMMARY Coupling, or communication between the bone-resorbing osteoclasts and bone-forming osteoblasts during bone remodeling, is a key step in the bone remodeling cycle. While compelling evidence shows that bone loss and fragility with age and osteoporosis result from corrupted coupling, the precise mechanism of osteoclast- osteoblast communication remains unclear. Thus, although stimulating coupling is a theoretically attractive therapeutic target, current treatments for osteoporosis, a common disorder affecting 54 million of the elderly in the US alone, are limited to either inhibiting osteoclastic bone resorption or stimulating osteoblastic bone formation. Our long-term goal is to determine the mechanism of osteoclast-osteoblast communication critical for coupling of bone formation to resorption during physiological bone remodeling, using rare osteopetrotic diseases as a tool. Rare bone diseases provide important insights into typical bone physiology and knowledge gained from these diseases has already led to new therapies for osteoporosis. In this proposal, we utilize samples from patients with autosomal dominant osteopetrosis type II (ADOII), a rare inheritable osteopetrosis characterized by high bone mass and skeletal fragility and complement human studies with mouse models. ADOII results from heterozygous mutations in the CLCN7 gene, which encodes the ClC-7 Cl-/H+ exchanger essential for osteoclastic bone-resorption. While the lack of osteoclastic resorption clearly contributes to bone phenotype, bone formation is also inappropriately high. In preliminary data investigating the bone structural unit (BSU) composition of ADOII bones, we found bone formation is primarily remodeling based, with excess bone formation called overflow remodeling. Osteoclasts are abundant and scalloped cement lines suggest an intermittent pit-like resorption mode, which in combination with overflow remodeling results in a characteristic puzzle-like bone structure. We hypothesize that the anabolically active but poorly resorptive osteoclasts in ADOII overexpress anabolic coupling factors, inappropriately stimulating bone formation to overfill the resorbed cavities and leading to disorganized puzzle-like bone and fragility. We will test this hypothesis by combining in vivo and in vitro studies of ADOII patients and mouse models, multimodal and multiscale imaging, biomechanics and spatial/single-nuclei transcriptomics. Specifically, we will: 1) test if the high bone mass and fragility in human and mouse ADOII is osteoclast-mediated; and 2) investigate the mechanism of inappropriately high bone formation in ADOII by single nuclei transcriptomic analysis of physically adjacent osteoclasts and osteoblasts. The proposed studies take advantage of the unique resource of extant iliac crest bone biopsy specimens from 15 ADOII patients from a Danish family carrying the CLCN7 (G215R) mutation and age and sex matched controls, and two mouse models of ADOII, including the analogous Clcn7G213R/+ mutation. Through the lens of ADOII, these studies will provide unique insights into osteoclast-osteoblast communication.

NIH Research Projects · FY 2025 · 2022-09

Project Summary/Abstract Despite recent progress in cancer therapy, the brain tumor glioblastoma (GBM) remains an extremely challenging disease and new therapies are much needed. One of the biggest obstacles to effective treatment of GBM is the presence of the blood-brain barrier (BBB), which prevents the passage of most drugs into the brain. The highly invasive nature of GBM means there are always cells that remain after surgery in otherwise normal brain tissue, and these cells are protected behind the BBB, preventing many therapeutics from reaching them. To address this, we have formed a collaboration between Cho’s pre-clinical GBM therapeutics group at BWH (PI), and Pentelute’s peptide chemistry group at MIT (Co-I) to develop a new therapeutics to 1) specifically target GBM cells, and 2) cross the BBB. Our collaboration has identified a novel peptide, called BTP-7 that can specifically target GBM cells and penetrate the BBB, serving as a promising agent to deliver potent anti-cancer drugs to the tumor. The Pt(IV) drug has widespread clinical use for cancer treatment, but it is unable to cross the BBB, leading to low brain uptake and limiting its effectiveness for treating GBM. Here, we propose to attach Pt(IV) to BTP-7 (Pt(IV)-BTP-7), with the aim to increase Pt(IV) drug delivery to intracranial GBM tumors. Our specific aims (SA) are as follows: SA 1. Analyze Pt(IV)-BTP-7 specificity to dg-Bcan and potential to cross the BBB in vitro. SA 2. Investigate the biodistribution (BD), pharmacokinetics (PK) and pharmacodynamics (PD) of Pt(IV)-BTP-7 in GBM bearing mice. SA 3. Evaluate the efficacy of Pt(IV)-BTP-7 drug in orthotopic GBM mouse models. Our research findings could lead to the development of a highly efficacious therapeutic to benefit GBM patients.

NIH Research Projects · FY 2025 · 2022-09

Project Summary Pulmonary thromboembolism remains a significant cause of morbidity and mortality in the western world. While many of the initial symptoms in acute pulmonary embolism (PE) resolves with appropriate treatment, there is increasing awareness of chronic impact of the disease ranging from development of chronic thromboembolic pulmonary hypertension (CTEPH) to persisting dyspnea and exercise impairment. Many patients initially diagnosed with PE may already have chronic disease and inappropriate treatment for acute disease in these cases may be harmful and delay referral to specialized centers with experience in treating chronic disease. On the other hand many patients with acute PE go on to develop chronic disease despite current treatment options and follow-up to insure resolution remains a challenge particularly without the ability to predict who will develop chronic disease. Furthermore, prognostication and selection of treatments can be difficult, particularly in submassive acute PE and CTEPH, particularly with newly emerging treatment choices. Quantitative methods are needed to help define disease trajectories early in presentation, help guide prognostication and treatment and improve our understanding of the pathophysiology of this condition. Computed Tomography (CT) imaging is the cornerstone of evaluation of pulmonary thromboembolism. In acute PE, it is the often the first imaging modality available for assessing treatment options. As the patient recovers, it is used to detect chronic or reoccurring clot guide interventions in chronic disease. Advances in CT imaging quality, image processing (including application of deep learning), coupled with increasing computation power make possible the extraction of a large number of novel features from CT imaging. In this proposal we seek to combine our team’s experience in CT image quantification with multi-center longitudinal data to develop CT imaging features that can identify and predict disease chronicity, its impact on the pulmonary circulation and its response to treatment. In Aim 1 we utilize longitudinal data from three academic hospitals (Brigham and Women’s Hospital, Massachusetts General Hospital, Northwestern University) to assess CT features at presentation that predict the presence or development of chronic disease. In Aim 2, we study both the presentation and follow-up image to build quantitative models of the impact of acute and chronic disease on the pulmonary circulation in order to help with prognostication and improve non-invasive methods of predicting the relevance of persistent disease to the clinical state of patients. In aim 3 we use a combination of longitudinal imaging in CTEPH patients having undergone surgery and patients with pulmonary arterial hypertension to identify patients that would have the most optimal surgical outcomes. We believe that the combination of the features and models developed in these complementary aims will advance our ability to use clinically available CT imaging to improve phenotyping, prognostication and treatment decisions and improve our understanding of the longitudinal progression of pulmonary thromboembolic disease.

NIH Research Projects · FY 2024 · 2022-09

PROJECT SUMMARY / ABSTRACT The vast majority of pediatric and adult cardiac surgery procedures worldwide involve the use of cardiopulmonary bypass with a dedicated and highly customized perfusion system. Cardiac surgery procedures are complex and entail safety-critical activities, requiring continuous coordination between four subteams: perfusion, surgical, nursing and anesthesia. This environment demands outstanding technical and non-technical skills (e.g. teamwork, communication and situational awareness). Over the past few decades, technological advancements have improved the safety and efficiency of the perfusion system, however, despite substantial progress, recent studies continue to report a high incidence of preventable intraoperative adverse events among cardiac surgery patients. The perfusion system, in particular, relies heavily on the expertise and skills of the perfusionist, and there is currently no computational intelligent system to support perfusionists' optimal decision-making during the critical phase of cardiopulmonary bypass. In this proposal, we seek to develop a data-driven approach to learn from expert perfusionists how to achieve optimal outcomes for cardiac surgery patients. Rather than attempt to engineer a solution, we propose to develop a computer-based apprentice that can learn from high-quality demonstrations of perfusionist actions to infer gold-standard patient care. Our goal is to develop and evaluate a Robot-Assisted Perfusion System (RAPS) that can be integrated into the cardiac surgery workflow as a non-human teammate. The RAPS will support the perfusion team in a way that perfusionists still will keep control of the perfusion system (i.e. human- in-the-loop), but cognitively supported and guided by the RAPS.

NIH Research Projects · FY 2025 · 2022-09

Alzheimer's disease is the most common neurodegenerative disorder and is characterized clinically by cognitive dysfunction. Classic neuropathological features of the disease include the formation of extracellular amyloid plaques, intraneuronal deposition of abnormally phosphorylated and aggregated tau protein into neurofibrillary tangles, and gliosis. Glial pathology has generally been considered a secondary, or reactive, change. However, recent advances in understanding normal and pathological glial biology have instead suggested that glia may play an active role in neurological disorders, including Alzheimer’s disease. Here we take a genetic approach to define proteins and pathways mediating the influence of glia on Alzheimer’s-associated neurodegeneration. Taking advantage of the advanced molecular and genetic tools, short lifespan, and conserved glial biology in Drosophila we will identify glial proteins and pathways that can influence tau neurotoxicity in aging adult brains. In proof of principle studies, we have validated a novel system for studying non-cell autonomous neurodegeneration in tauopathy and show that our assay system works in the context of unbiased screening. In addition, based on the observation that many genes implicated in Alzheimer’s disease through genome wide genetic association studies (GWAS) are expressed predominantly or substantially in glial cells, we will test the effect of upregulating and downregulating these GWAS-derived gene candidates in fly glia on tau-induced neurotoxicity. To additionally connect our genetic model experiments with the authentic human disease, we will use state-of-the-art informatics tools to integrate functional genetic data with Alzheimer’s disease transcriptomics and proteomics. Since our systems analysis will be performed on a glial subtype-specific basis our studies can not only outline glial networks modulating the toxicity of tau to neurons, but also provide functional insight into newly defined glial subtypes. Our studies will develop fundamental insights into glia cell biology in health and disease and will expand the array of cellular and molecular targets relevant for therapy development in Alzheimer’s disease and related neurodegenerative disorders.

NIH Research Projects · FY 2025 · 2022-08

Miscarriage - defined as pregnancy loss prior to 20 weeks of gestation - is the most common pregnancy complication, affecting 10-20% of clinically recognized pregnancies. While advances have been made in noninvasive prenatal diagnosis of chromosomal abnormalities leading to pregnancy loss, the pathophysiology and environmental causes of chromosomally normal losses – the bulk of miscarriages occurring after the 6th gestation week – remain largely unexplained. We hypothesize that microRNAs serve as a physiologic “glue” for common pathways predicting loss of chromosomally normal pregnancies. MicroRNAs are non-coding RNAs that negatively regulate gene expression by inducing translational inhibition or mRNA degradation. Because of their remarkable stability in the circulation and their ability to report on or regulate cellular and tissue phenotypes in distal anatomic sites, they present an attractive novel target for mechanistic and diagnostic biomarker research. miRNA expression is controlled by a variety of exposures not yet deciphered in pregnant women. In our global transcriptomics pilot, we discovered circulating miRNAs that are differentially expressed in typical pregnancy compared to pre-conception and to pregnancy in women who later miscarry. This application responds to a strategic priority identified by NICHD. We leverage the rich dataset of demographic, socio-economic and maternal health data and the biospecimen archive of three large early pregnancy cohorts (>8000 enrolled participants) and align them with technological resources offered under GLP practice by four participating laboratories. Drawing on the largest sample of miscarriages ever examined in relation to prospectively obtained biological data (250 chromosomally normal miscarriages) and building on the technological resources offered under GLP practice by four participating laboratories, we will: Aim 1: Identify prodromal molecular signatures of miscarriage, in pre-miscarriage maternal blood, free of common chromosomal defects: 1.1 identify miRNAs and miRNA-targeted pathways dysregulated in such miscarriages and 1.2 test associations with gestational age at miscarriage;1.3 determine whether hypothesis-driven biomarkers of deficient endometrial function, inflammation, oxidative stress, hormonal imbalance, and coagulopathy/hemostatic injury are associated with such miscarriages; and 1.4. whether they mediate an association between miRNA and miscarriage. Aim 2: Apply omics in maternal urine to identify environmental exposures associated with miscarriages free of common chromosomal defects; and Aim 3: Explore whether miRNA antecedents mediate an association between miscarriage and elements of the maternal exposome, including chemicals, and socioeconomic and health- related stressors. The proposed research will generate high-dimensional data for the research community and open the door to novel predictive models of the adverse effects of chemical exposures in pregnant women. The study is innovative in its focus on understanding mechanisms and environmental exposures associated with miscarriage and may identify molecular predictors and modifiable risk factors of early pregnancy complications.