Brigham And Women'S Hospital

NIH Research Projects · FY 2025 · 2021-01

ABSTRACT: The intersection of healthcare and biomedical research is at an inflection point with the convergence of the digital revolution, advances in imaging, nanotechnology, big data science, and precision or personalized medicine. There is a wealth of meaningful, but complex information that could be extracted from imaging data but is not optimally utilized for patient care. Cancer care exemplifies the current challenges which include early detection, accurate distinction of pre- neoplastic and neoplastic lesions, prediction of tumor aggressiveness, determining infiltrative tumor margins during surgical treatment, tracking tumor evolution/ metastasis pattern, recurrence, and potential acquired resistance to treatments over time. Major strides have been made in the personalization of cancer therapies such as immunotherapy, but the availability of specific, relevant, and timely medical data and information is of critical importance to realizing the full potential of precision medicine. Nowhere is this more acutely evident than during interventions in the operating and procedure rooms. Novel methods of image guidance, data integration, information extraction, and knowledge transfer are needed to enable clinicians to fully leverage the information available, especially before, during and after invasive procedures. We are excited to re-submit a proposal for a new P41 biomedical resource center (BTRC) called Advanced Technologies for NCIGT(AT-NCIGT) with 3 TRDs, 10 new collaborative and 10 new service projects, all of which aim to investigate develop and disseminate new technologies for image guided therapy (IGT). The 3 components are Imaging Cancer Heterogeneity for IGT, Deep Learning for IGT and Intraoperative devices for IGT. These new technologies alone and in combinations will allow for greater understanding of disease state, treatment guidance, integration/navigation and in-vivo monitoring of tissue responses and improve the precision of invasive procedures. Thus the overall goal of this proposal is to investigate, develop and disseminate novel technologies for extracting new tissue characteristics (technology research and development core TRD 1: Imaging cancer heterogeneity; analyze them and make them available through state-of-the-art algorithmic and data curation approaches (Deep Learning TRD 2); and enable precise tissue sampling surgical navigation and in-vivo tissue response through the results of novel Intraoperative devices (Intraoperative devices for IGT: TRD 3). In order to effectively disseminate all this new knowledge we have 10 new collaborative and 10 new service projects and will share these novel tools through our established mechanisms, from current BTRC- National Center for Image Guided Therapy (NCIGT), which continues to be dedicated to the innovating for IGT into interventional radiology, surgery, radiation oncology, and procedure-based medicine.

NIH Research Projects · FY 2025 · 2021-01

Multiple hypotheses have been put forward regarding cortical circuit dysfunction in autism, including: excitation to inhibition (E/I) imbalance, hyper- or hypo- connectivity profiles, abnormal processing along the cortical column, increased variability of sensory encoding, failure of “canonical” cortical computations, and others. Nevertheless, we currently lack a detailed mechanistic understanding of how cortical circuits malfunction during sensory processing in autism. This critical knowledge deficit needs to be corrected. Identifying common themes of neural circuit dysfunction in autism would yield new targets for intervention, potentially opening new windows for restoring function. Methyl-CpG-binding-protein-2 (MECP2) duplication syndrome is caused by duplication of the MECP2 gene, leading to progressive intellectual disability and autism in males with 100% penetrance. It is the “mirror image” of Rett syndrome, caused by loss of MECP2 function. Abnormal synaptic plasticity and E/I imbalance have been causally implicated in both MECP2-disorders and autism in general and are known to affect cortical function. Notably, we and others have shown that visual function is abnormal in MECP2-syndromes. Visual cortex, a prototypical “low level” sensory area, renders itself optimally for studying cortical sensory processing. Here, we mount a comprehensive effort to understand how sensory processing fails in MECP2-duplication syndrome, by studying the visual cortex. Recent advances will allow us for the first time to map densely, at single cell resolution, the functional properties and connectome of a cortical column, one of the fundamental modules of cortical computation, in the MECP2-duplication mouse model of autism (aim #1). This will be followed by a detailed electro-physiological connectivity analysis of the cortical circuit to probe underlying mechanisms (aim #2). Data obtained will be used in conjunction with deep learning techniques to create a sophisticated neuro-realistic model of the cortical circuit, which will allow a detailed, “in computo,” interrogation of the mechanism of dysfunction and how to ameliorate it (aim #3). Hypotheses formulated “in computo” can then be tested optogenetically, closing the loop. Expectations: 1) Obtain the first comprehensive picture of how early sensory processing fails in this model of autism. 2) Identify specific sub-network connectivity defects reflecting abnormal interneuronal connectivity and E/I balance, 3) Construct a neuro-realistic model of the cortical microcircuit, which can be used to uncover “in computo” the mechanism of dysfunction and to probe how one might intervene to repair it. Finally, we will 4) develop a systematic framework, within which to categorize cortical processing and dysfunction in autism. In the future, additional models of autism will be brought into this fold to be categorized and systematically studied.

NIH Research Projects · FY 2025 · 2021-01

Project Summary. The goal of this project is to develop, optimize, and evaluate an artificial intelligence (AI)- driven, medical imaging platform that utilizes computed tomography (CT) imaging to identify the presence of extranodal extension (ENE) in head and neck squamous cell carcinoma (HNSCC). HNSCC is a debilitating disease with significant patient-related morbidity related to the disease itself and its management, which is complex and consists of a combination of surgery, radiation, and chemotherapy. A key factor in determining proper HNSCC management is the presence of ENE, which occurs when tumor infiltrates through the capsule of an involved lymph node into the surrounding tissue. ENE is both an important prognostic factor and an indication for adjuvant treatment escalation with the addition of chemotherapy to radiation following surgery. This “trimodality therapy” is problematic, as it is associated with increased treatment-related morbidity and healthcare costs, but no improvement in disease control compared to upfront chemoradiation alone. The challenge is that ENE can only be definitively diagnosed pathologically after surgery, and pretreatment radiographic ENE identification has proven unreliable for even expert diagnosticians, leading to high rates of trimodality therapy and suboptimal treatment outcomes. In HNSCC management there is a critical need for improved pretreatment ENE identification to 1) select appropriate patients for surgery to avoid the excess morbidity and costs of trimodality therapy, 2) risk-stratify patients optimally, and 3) select appropriate patients for treatment de-escalation or intensification clinical trials. In recent years, Deep learning, a subtype of machine learning, under the umbrella of AI, has generated breakthroughs in computerized medical image analysis, at times outperforming human experts and discovering patterns hidden to the naked eye. While AI is poised to transform the fields of cancer imaging and personalized cancer care, there remain significant barriers to clinical implementation. The hypothesis of this project is that AI can be used to successfully identify HNSCC ENE on pretreatment imaging in retrospective and prospective patient cohorts and to develop a platform for lymph node auto-segmentation that will promote clinical utility of the platform. This hypothesis will be tested by rigorous optimization and evaluation of a deep learning ENE identification platform. Specifically, the platform will be validated for accuracy, sensitivity, specificity, and discriminatory performance on two heterogeneous retrospective datasets and two prospective cohorts derived from institutional and national Phase II clinical trials for HNSCC patients. The platform will then be directly compared with head and neck radiologists to determine if radiologist performance can be augmented with AI. In parallel, AI will be utilized to develop an auto-segmentation platform for tumor and lymph nodes, which will 1) improve the platform's clinical impact and 2) provide a valuable tool for treatment planning and future imaging-based research for HNSCC patients. 1

NIH Research Projects · FY 2025 · 2020-12

Project Summary/Abstract African-Americans and Hispanics of Puerto-Rican origin bear a disproportionate burden of asthma morbidity and mortality, despite decades of attention to asthma disparities. The advent of biologic therapies offers a promising route to narrow these disparities. However, despite the well documented disparities in asthma treatment and outcomes, little is known about the use of biologics in these minority groups. Furthermore, ethnic minorities have been grossly underrepresented in trials that form the evidence base of the efficacy of these drugs. The goal of this Postdoctoral Career Transition Award to Promote Diversity (K99/R00 MOSAIC) is to expedite the candidate's transition to an independent investigator who possesses unique expertise in the use of mixed methods in pharmacoepidemiology and disparities research. Through the application of rigorous qualitative methods and sophisticated non-experimental designs, the candidate will determine patients’ attitudes and beliefs about biologics and providers motivators for prescribing, and evaluate how these influence real-world utilization patterns and effectiveness of biologics, with focus on treatment effect heterogeneity by race/ethnicity. In the K99 phase of this award, the candidate will obtain focused training needed to accomplish these goals. In the R00 phase, the candidate will conduct a prospective cohort of patients with severe asthma and assess how time-varying patient factors and provider factors influence biologic initiation, adherence, and discontinuation. The aims are to 1) Describe biologic use and identify differences in use across racial/ethnic groups, 2) Compare the real-world effectiveness of these biologics on asthma-related outcomes; and determine effect modification by race/ethnicity, and 3) Identify patient- and provider factors that influence biologic use and adherence over time. Findings from this R00 study will form the basis for further research such as using mediation and decomposition analysis to partition any identified differences in biologic use or patient outcomes to the various sources of bias. This will be helpful as we identify interventions which are likely to be effective in eliminating disparities related to biologics use. These activities will also establish the candidate's portfolio for applying mixed methods to generate evidence on interventions to reduce disparities in minority patients with severe asthma.

NIH Research Projects · FY 2025 · 2020-12

Project Summary. Cellular hypoxia-reoxygenation or organ ischemia-reperfusion promotes intracellular redox stress, which can lead to cellular dysfunction and injury through the generation of reactive oxygen species (ROS). In prior work, we identified the role of L(S)-2-hydroxyglutarate (L2HG) as a unique metabolic derivative of α-ketoglutarate (2-oxoglutarate, or 2OG) that increases in hypoxia or ischemia. In the ongoing cycle of this award, we have shown that L2HG decreases glycolysis and increases pentose- phosphate pathway (PPP) activity as a unique mechanism for promoting redox protection in endothelial cells and in the myocardium. In this next proposed four-year cycle, we turn our attention to the relationship between L2HG and branched-chain ketoacids (BCKAs), metabolic derivatives of branched- chain amino acids (BCAAs), and their role in redox protection in the heart. Upon examination of the metabolome in hypoxic cardiovascular cells, we observed that BCKAs are significantly increased compared with normoxic cells, and that this increase in the BCKA pool is also an important determinant of redox protection. Abundant preliminary data provided in this application demonstrate that the redox protection afforded by BCKAs is mediated by Hif-1α stabilization, and comes about by a unique mechanism: an increase in BCKAs leads to an increase in BCAAs, which is associated with an increase in 2OG generation from glutamate via reamination of BCKAs. The increase in 2OG in the reductive environment of hypoxia leads to an increase in L2HG, with accompanying redox-protective metabolic reprogramming. Thus, the central hypothesis of this proposal is that an hypoxia-induced accumulation of BCKAs in endothelial cells (ECs) and cardiomyocytes (CM) increases L2HG, which together promote redox protection. To test this hypothesis, we propose three specific aims: 1) we will determine the effects of hypoxia on BCAA and BCKA metabolism in ECs and CMs; 2) we will identify the molecular and metabolic determinants linking BCKA metabolism with L2HG generation, and their consequences for Hif stabilization in ECs and CMs; and 3) we will study the effects of the BCKA-L2HG metabolic axis in hypoxia or ischemia on redox protection and function in ECs, CMs, and the myocardium. The results of these studies should provide useful insight into the complex interplay of metabolic intermediates that govern redox potential and redox protection in the myocardium, and its potential consequences for ischemia-mediated cardiovascular diseases.

NIH Research Projects · FY 2025 · 2020-12

PROJECT SUMMARY Effective emotion regulation (ER) requires the ability to flexibly and dynamically respond to affectively-valenced stimuli in the service of goal-directed behaviors. Patients with major mood disorders, including bipolar disorder (BD) and major depressive disorder (MDD) are characterized by brain-based abnormalities in affective processing and cognitive deficits that make it difficult for them to regulate their emotions. Disruptions in ER are thought to play a role in risk for onset of illness, a relapsing course, and incomplete remission. Aging may amplify poor outcomes in older adults with depression, as reflected in a more severe course and treatment resistance. In contrast, in healthy adults, ER improves across the lifespan with a shift from attending to negative to attending to positive stimuli in attention, learning and memory. Consistent with RDoC, we will leverage multiple units of analysis (circuit, performance, self-report) in a transdiagnostic sample enriched for a range of ER-related network functions, implicit attentional biases, and ER strategies. We will enroll 200 adults (ages 41-80) with an affectively-stable mood disorder (100 BD, 100 MDD), and 100 demographically-matched healthy controls, allowing us to capture the range from extreme positive to extreme negative emotional experience. We will assess performance-based affective biases, cognitive control, and resting-state functional connectivity (FC), to define age-related changes in ER circuitry. We will assay habitual use of ER strategies, social functioning, and well-being to determine how brain-based processes affect these functionally- and clinically-relevant outcomes. Impact. The goals of this project are directly aligned with the NIMH Strategic Plan to develop new ways of characterizing and treating mental illness that are predicated on understanding brain-based mechanisms. Beyond the heuristic value of understanding the specific mechanisms and developmental trajectory of ER in mid and late life, results can be used to inform the development of novel interventions (e.g., neurostimulation, cognitive interventions) designed to “rescue” the specific network dysfunctions that give rise to maladaptive ER in depressive disorders.

NIH Research Projects · FY 2025 · 2020-12

Human malignant melanoma is an aggressive cancer with high propensity for metastatic dissemination. Despite recent advances in melanoma therapy, most patients with metastatic disease do not experience durable benefit from current treatment options. Indeed, existing targeted and cancer immunotherapeutic modalities do not directly inhibit tumor metastasis, which accounts for most cancer-related deaths. Accordingly, the development of new agents that specifically target pro-metastatic pathways intrinsic to melanoma cells could greatly improve treatment outcomes and reduce off-target toxicities. The trafficking processes observed in disseminating metastatic cancers resemble, at least in part, the leukocyte homing paradigm, a sequential multistep adhesive cascade involving cell tethering and rolling on microvascular endothelium, followed by integrin-mediated arrest and transendothelial migration into secondary tissues. Leukocyte homing is dependent on specialized integrin heterodimers and their cognate ligands on endothelial cells. To date, however, expression of these distinct leukocytic homing integrin subsets has not been described in melanoma. Our preliminary studies demonstrate, for the first time, aberrant expression of integrin heterodimers, conventionally thought to be restricted to leukocytes, by melanoma cell subsets with high metastatic capacity. In patient primary melanomas, cancer cell-intrinsic integrin positivity correlated with sentinel lymph node metastases. Melanoma-specific inhibition of these integrin heterodimers suppressed endothelial adhesion and significantly blocked growth and metastasis formation in preclinical mouse models of human melanoma. These paradigm- shifting findings identify leukocytic homing integrins as novel mediators of tumor cell dissemination. While hematopoietic integrin targeting approaches, including humanized antibodies, have already been developed for the treatment of patients with inflammatory and autoimmune leukocyte trafficking disorders, they have never been examined in the context of cancer. In this proposal, we newly investigate the therapeutic utility of these validated and readily available integrin inhibitors in blocking metastatic dissemination in preclinical melanoma models. Our specific aims are to 1) dissect mechanisms of melanoma cell-intrinsic homing integrin induction and functional activation, and define integrin glycosylation states and heterodimer composition in patient tumor biospecimens at various stages of progression, and 2) examine the therapeutic efficacy of CRISPR/Cas-9-mediated leukocytic integrin knockout or clinical-grade integrin inhibitors originally formulated for the treatment of immune trafficking disorders, in preclinical melanoma models. We have assembled a team of experts in the melanoma metastasis, leukocyte homing, gene editing, dermatopathology, and glycobiology fields, to bring to fruition the translationally relevant aims of this proposal. Results from our studies could establish melanoma cell-expressed leukocytic integrins and their glycostructural determinants as novel therapeutic targets for selective inhibition of metastatic dissemination.

NIH Research Projects · FY 2025 · 2020-12

Comparisons of genetic mutations found in primary tumors and their corresponding metastatic lesions have so far failed to define genetic mutations that lead to metastasis. This raises a notion that it is the epigenetic mechanisms, working together with cancer type-specific oncogenic and/or cell type-specific lineage programs, that may drive metastatic progression. In breast cancer, how epigenetic abnormalities drive metastatic progression remains largely elusive. A better understanding of this may lead to novel strategies to block breast cancer metastasis. LSD1 (KDM1A) is the first identified histone demethylase. In human cancers, genetic abnormalities of LSD1 mainly include deletions and mutations. Such deletions/mutations have also been found in metastatic breast cancer, raising a possibility that LSD1 is a breast cancer metastasis suppressor. Indeed, in preliminary studies, we found induced loss of LSD1 in luminal mammary tumor cells or LSD1 inhibitor treatment in the MMTV-PyMT mouse model led to a dramatic increase in lung metastasis. Mechanistically, in luminal breast cells, we found LSD1 interacts with GATA3, a key luminal-specific transcription factor, to control their common programs related to cell-cell adhesion and cell cycle. LSD1 positively regulates GATA3 expression and represses that of TRIM37, a common target of both LSD1 and GATA3, which encodes a histone H2A ubiquitin ligase involved in gene repression. Importantly, TRIM37 may contribute to increased invasion and migration of luminal breast cancer cells with LSD1-loss via repression of several cell adhesion genes (e.g., CDH1, VCL, CTNNA1). Such expression changes were also observed in murine PyMT tumor cells with LSD1-loss. Together, these data suggest that LSD1 may suppress breast cancer metastasis via regulation of its target genes (e.g., TRIM37) in luminal cells in a demethylase activity- dependent manner. Intriguingly, PyMT tumor cells with LSD1 ablation also exhibited a profound change in immune-related genes, suggesting that LSD1 may also suppress breast cancer metastasis by a cell-extrinsic, immune-related mechanism. To test these, we will continue to establish mouse intraductal injection (MIND) transplantation models for PyMT tumor cells and human estrogen receptor+ breast cancer cell lines as our in vivo system. In Aim 1, we will perform CRISPR-based screens to map functional domain(s) of LSD1 responsible for its metastasis suppression vs. proliferation/survival-supporting roles, and test if LSD1 mutations found in patients impair its metastasis suppression function via disruption of the demethylase activity. In Aim 2, we will determine roles of LSD1 targets (e.g., TRIM37 and its partner EZH2, and others) of luminal cells at different steps of the metastatic cascade in various MIND models. In Aim 3, we will determine the immune mechanism mediating increased PyMT metastasis associated with LSD1 ablation, in particular, NK cells and MHC-I molecules, as LSD1-loss in PyMT tumor cells led to a profound upregulation of various classic and non-classic MHC-Is, which serve as ligands for inhibitory receptors in NK cells.

NIH Research Projects · FY 2024 · 2020-09

PROJECT ABSTRACT/SUMMARY Alzheimer’s disease (AD) affects 5.5 million Americans and recent studies suggest that AD pathogenesis can be affected by the gut microbiota. We submit an extensively revised proposal in which we have identified three major mechanisms by which gut microbes may regulate AD: (i) APP processing and tau phosphorylation, (ii) modulating microglia, and (iii) activating peripheral immunity. We found that Bacteroides was linked to high levels of Aβ and Allobaculum was linked to low levels of Aβ, and we also identified metagenomic functions associated with Aβ. To find novel microbial mediators we will perform metabolomics. Administering Allobaculum reverses age-related changes in inflammatory expression in the cortex of WT mice and reversed markers of the microglia neurodegenerative disease phenotype (MGnD). In new preliminary data, we found that administering Bacteroides fragilis increased Aβ plaques and depleting Bacteroidetes with metronidazole decreased Aβ plaques. Both manipulations altered APP processing gene expression, including APP phosphorylation, trafficking from the golgi, and degradation by insulin degrading enzyme, which is a new potential microbially- driven mechanism that we will investigate in Aim 1. Of note, Bacteroides is increased in aging and AD in humans. Both microglia and peripheral monocytes play an important role in AD. In new preliminary data, we now show that colonizing mice with microbiota from AD patients increases Trem2 expression on microglia, which is a regulator of the MGnD phenotype, and that it decreases the expression of CCR2 on peripheral monocytes. CCR2+ monocytes traffic to the brain and are critical for the clearance of Aβ. Thus, we provide evidence that the AD microbiota can contribute to dysfunction in immune signaling pathways known to impact AD. We also show that administering specific bacteria or antibiotics modulates peripheral and central innate immunity. AIM 1: Which microbial factors alter AD pathogenesis in Aβ and tau animal models? We will determine whether (i) specific bacteria, (ii) individual antibiotics, and (iii) microbiota from AD subjects affect Aβ and tau pathology and cognitive decline. We will investigate whether this is linked with altered APP processing, regulation of Aβ degradation enzymes, activation of pro-amyloidogenic pathways, or with altering Tau phosphorylation. We will use 16S rRNA and shotgun metagenomic sequencing to identify bacteria and functions linked with AD pathology, and identify metabolites altered in models of AD. AIM 2: How does the microbiota modulate innate immunity in Aβ and tau animal models? We will investigate how microbiota interventions alter microglial migration and Aβ phagocytosis, and whether the microbiota modulate the switch between homeostatic and neurodegenerative microglia. We will test whether the microbiota alter monocyte migration to the brain and subsequent Aβ phagocytosis. We will establish whether microbial cell wall components, live microbes, and/or their secreted metabolites drive changes in innate immunity that affect AD.

NIH Research Projects · FY 2025 · 2020-09

Abstract Viral reservoir cells are an extremely small but highly durable population of HIV-1-infected CD4 T cells that persist despite treatment with highly-effective antiretroviral therapy and are responsible for viral rebound once treatment is interrupted. Understanding and characterizing the physiology of these cells will likely be critical for any effort to successfully target these cells but has turned out to be extremely difficult, due to their low fractional abundance and considerable heterogeneity in blood and tissues. Moreover, there is growing evidence suggesting that viral reservoir CD4 T cells are dynamically evolving over time, and subject to selection mechanisms that favor the long-term persistence of some reservoir cells, while eliminating others. Here, we plan to take advantage of recent progress in molecular single-cell and imaging analysis techniques and propose to comprehensively profile the longitudinal evolution of viral reservoir cells in blood and tissues. We hypothesize that continuous suppressive antiretroviral therapy selects for intact proviruses with features of deeper latency, likely as a result of immune selection mechanisms that preferentially eliminate proviruses more susceptible to reactivation signals, while proviruses in deeper latency persist. These studies will be conducted using samples of a unique, prospectively followed cohort of HIV-1-patients who were identified in acute infection and started antiretroviral treatment immediately after diagnosis. In Specific Aim 1, we will use novel next-generation sequencing technologies to longitudinally profile the chromosomal position of intact and defective proviruses from blood and tissues, and evaluate their microanatomical location in lymphoid tissues. Subsequently, we will characterize the epigenetic chromatin environment within chromosomal proximity to intact proviruses from blood and tissues, using a platform of next-generation sequencing assays to evaluate chromatin accessibility, inhibitory or activating histone modifications and DNA methylation (Specific Aim 2). In Specific Aim 3, we will perform novel, functional single-cell assays to simultaneously analyze the proviral sequence, the corresponding integration sites and HIV-1 RNA expression profile of single virally infected cells from blood and tissues; this assay will allow us to individually characterize the viral gene expression pattern of single infected cells encoding for intact and defective proviruses, and enable testing the hypothesis that continuous antiretroviral therapy is associated with progressive accumulation of proviruses with deeper levels of latency and lower responsiveness to viral reactivation stimuli. Together, these studies have the potential to provide significant advances in understanding the complexity and longitudinal evolution of viral reservoir cells and may allow to identify susceptibilities and vulnerabilities of residual HIV-1-infected cells that could be therapeutically targeted.

NIH Research Projects · FY 2024 · 2020-09

Summary     Glioblastoma  (GBM,  or  astrocytoma  grade  IV)  brain  tumor  remains  one  of  the  most  lethal  forms  of  human  cancer  and  a  major  unmet  need  in  current  oncology.  GBM  is  a  highly  heterogeneous  and  multifactorial  disease  characterized  by  the  wide  landscape  of  mutations  and  signaling  alterations.  Thus,  most  of  the  developing experimental therapies will likely only help a fraction of patients. We have discovered microRNA-­ 10b  (miR-­10b),  a  regulatory  molecule  whose  transcriptional  activation  emerges  as  a  unique  mechanism  shared by almost all gliomas, including both high-­grade and low-­grade, despite their heterogeneity. miR-­10b  regulates  neoplastic  transformation  of  normal  glial  cells  and  the  growth  of  malignant  gliomas.  Moreover,  it  appears essential for the viability of heterogeneous glioma cells and glioma-­initiating stem cells (GSC). Since  miR-­10b is highly expressed in practically all malignant gliomas, and its inhibition affects all glioma subtypes,  miR-­10b targeting represents a common therapeutic strategy for GBM. Despite the high levels and the critical  role  of  miR-­10b  in  GBM,  how  the  expression  of  this  molecule,  which  is  silenced  in  the  normal  brain,  gets  activated  in  gliomagenesis  is  unknown.  Based  on  our  preliminary  data,  we  hypothesize  that  various  aberrations accumulating in the brain may converge on epigenetic alterations and reorganization of the three-­ dimensional structure of the miR-­10b locus, resulting in its transcriptional activation. Such structural changes,  primarily mediated by the CCCTC-­binding factor (CTCF) and regulatory long non-­coding RNA transcripts, will  result in the exposure of miR-­10b promoter to a corresponding enhancer, and thus miR-­10b expression. In  this R01 project, we will test our hypothesis, investigate the epigenetic mechanism underlying the activation  of miR-­10b locus in glioma, and establish the miR-­10b-­locus centered model of gliomagenesis. Specific Aim  1  will,  therefore,  provide  the  high-­resolution  analysis  of  the  epigenetic  landscape  and  three-­dimensional  chromatin  conformation  of  miR-­10b  locus  in  normal  neuroglial  and  glioma  cells  and  tissues,  and  at  the  different stages of neoplastic transformation. It will also assess how generalizable such regulation is in glioma  on a genomic scale. Specific Aim 2 will investigate functions of major regulatory DNA and RNA elements in  the  locus,  including  the  promoter-­associated  and  enhancer-­associated  RNAs,  using  a  combination  of  biochemical, gene editing, and imaging-­based approaches. Specific Aim 3 will model the process of the locus  activation and neoplastic transformation of astrocytes and neuroprogenitors using cell and animal models of  glioma. Discovery of the mechanism(s) converging on miR-­10b expression in the brain cortex will shed light  on the origin and etiology of malignant glioma. It may also suggest new strategies for switching it off and new  molecular targets for therapeutic applications.

NIH Research Projects · FY 2024 · 2020-09

PROJECT SUMMARY This is a resubmission by Kei Ouchi, MD, MPH, MS for the Paul B. Beeson Emerging Leaders Career Development Award in Aging (K76). Dr. Ouchi is committed to lead the field of emergency medicine to integrate the principles of geriatrics and palliative medicine. Dr. Ouchi is an emergency physician and home hospital physician (provides inpatient-level care at patient’s home10) in the Department of Emergency Medicine, Brigham and Women’s Hospital/Harvard Medical School. Dr. Ouchi’s research focuses on the development of ED GOAL, a 6-minute motivational interview conducted in the emergency department (ED), which engages patients to address advance care planning (ACP) conversations with their outpatient clinicians and avoids a time- consuming, sensitive conversation in the time-pressured ED environment. With funding from the NIA GEMSSTAR R03 and Emergency Medicine Foundation, Dr. Ouchi developed ED GOAL and demonstrated its acceptability and feasibility in seriously ill older adults in the ED. ED GOAL may also increase patients’ self- reported ACP engagement and ACP documentation after leaving the ED. The GEMSSTAR project identified that, in this setting where resources are limited, ED GOAL requires refinements to maximize its potential efficacy. This study will refine ED GOAL to maximize its potential efficacy and scalability, and determine the preliminary efficacy of the refined ED GOAL to increase ACP engagement one month after leaving the ED. The proposed 5-year training plan accelerates Dr. Ouchi’s career development as an independent physician-scientist through training in: 1) cognitive impairment assessment and engagement of caregivers in ACP research (ED GOALCG); 2) adaptation of ED GOAL/ ED GOALCG by specially-trained nurses; 3) conducting a clinical trial of ED GOAL/ ED GOALCG administered by specially-trained nurses; and 4) implementation science in preparation for a future pragmatic clinical trial of ED GOAL/ ED GOALCG. James Tulsky, MD, an internationally recognized researcher and leader in palliative medicine will serve as the primary mentor. Dr. Ouchi is co-mentored by: 1) Mara Schonberg, MD, MPH, a leader in health services research among older adults; and 2) Edward Boyer, MD, PhD, a K24-funded emergency medicine researcher with expertise in behavioral interventions. The culmination of this career development award will ensure that Dr. Ouchi gains the advanced research skills and knowledge that he needs to conduct a large, pragmatic trial of ED GOAL. The ultimate goal is to establish ED GOAL as a national standard of care to help all seriously ill older adults to receive ACP conversations at the most critical times of their lives. Dr. Ouchi aims to expand the scope of ED-based care from acute, disease- oriented care (e.g., gunshot wounds) to include patient-centered care (e.g., value-based, end-of-life care) for seriously ill older adults by integrating geriatrics and palliative medicine principles.

NIH Research Projects · FY 2024 · 2020-09

PROJECT ABSTRACT Obesity is a rapidly expanding epidemic that is arguably the leading cause of cardiovascular disease. Obese individuals have increased autonomous aldosterone production resulting in excessive activation of the mineralocorticoid receptor that increases the risk for myocardial fibrosis and ischemia, hypertension, and stroke. Since mineralocorticoid receptor antagonists are widely available and safe medications, autonomous aldosterone production represents a modifiable mechanism to prevent cardiovascular disease in obesity. We hypothesize that mineralocorticoid receptor antagonists can improve myocardial perfusion and fibrosis in obese individuals. We propose a mechanistic clinical trial that involves deep phenotyping of aldosterone physiology and cardiac MRI imaging to evaluate this hypothesis. Participants with high-risk obesity, defined as obesity with untreated hypertension and/or one or more features of the metabolic syndrome, will be enrolled. Participants will undergo a deep-phenotyping protocol to characterize aldosterone physiology, and cardiac MRI to measure myocardial perfusion reserve (to assess coronary microvascular function) and extracellular volume fraction (to assess myocardial fibrosis), before double-blinded randomization to eplerenone (a mineralocorticoid receptor antagonist and potassium-sparing diuretic) or chlorthalidone (a conventional blood pressure medication and potassium-wasting diuretic) along with potassium chloride for one year. During this year, blood pressure and potassium will be maintained in a target range to ensure outcomes are independent of these variables. Cardiac MRI-derived outcomes will be measured again after one year of the randomized intervention. It is anticipated that eplerenone therapy will improve measures of coronary microvascular function and fibrosis, independent of blood pressure, when compared to chlorthalidone with potassium. This mechanistic study is designed to investigate a targeted treatment for the prevention of cardiovascular disease in high-risk obesity using innovative hormonal phenotyping and sophisticated imaging outcomes. If our hypothesis is correct, this study may justify the early use of mineralocorticoid receptor antagonists in patients with obesity to prevent or delay the onset of cardiovascular disease, and establish a foundation for future trials to evaluate incident clinical cardiovascular outcomes.

NIH Research Projects · FY 2024 · 2020-09

Blood-brain barrier (BBB) dysfunction has been shown to play a causal role in both early- and late-onset Alzheimer's disease (EOAD, LOAD). While much has been learned about the molecular mechanisms of BBB function and dysfunction in AD from mouse model systems, many important unanswered questions remain regarding how AD-associated mutations and genetic variants affect human BBB integrity and function. Improved human experimental systems are required to complement existing animal models. Pioneering studies by co-PI Ingber have produced microfluidic 3D organ-on-chip models, including a BBB-on-a-chip (BBB- Chip), increasingly representative of human in vivo physiology. We have adapted this system to create isogenic iPSC-derived BBB-Chip models of normal human subjects and of subjects with EOAD and LOAD. The Young-Pearse lab has generated a collection of iPSC lines that capture the diverse set of genetic risk factors for AD including: EOAD mutation of APP and corrected controls, DS and DS with removal of copies of high impact chr21 genes, an isogenic APOE series including APOE 2/2, 3/3, 4/4 and KO, and a collection of lines that we've generated from over 50 individuals in the ROS/MAP cohorts that represent the clinical and pathological spectrum of LOAD. Here, we propose to combine the BBB-Chip model with the iPSC line collection to examine the impact of early- and late-onset genetic variants on BBB function, and to define the molecular pathways impacted by these variants. In the first aim, we address the hypothesis that neurons expressing EOAD mutations secrete Aβ species that negatively affect BBB integrity through toxic effects on brain microvasculature endothelial cells (BMVECs). We will use human BBB in vitro models to examine Aβ- dependent and independent impacts of trisomy 21 and fAD mutation on BBB integrity and function via a) measurements of transendothelial electrical resistance (TEER), b) permeability assays, and c) immunocytochemistry and morphological analyses of BBB cells. In addition, we will identify the molecular pathways affected in EOAD in BMVECs, pericytes and astrocytes via RNA sequencing and unbiased proteomics. In aim 2, we determine the functional impact of altered composition of Aβ aggregates on clearance of pathologic Aβ across the BBB. To this end, we will use a variety of well defined synthetic Aβ species as well as human neuron-derived and brain-derived Aβ to systematically define how Aβ composition and aggregation state affects: 1) uptake and transcytosis of Aβ across the BBB and 2) integrity of the BBB and health of the pericytes, astrocytes and BMVECs composing the BBB. Finally, in the third aim we address the hypothesis that the LOAD risk genes SORL1 and CLU work in concert with APOE to mediate Aβ clearance by the BBB. In this aim, we will determine the functional consequences of variants of APOE, CLU and SORL1 on BBB integrity and Aβ clearance. Finally, we will determine the molecular consequences of modulation of APOE, CLU and SORL1 in BMVECs, pericytes and astrocytes in our human BBB experimental system.

NIH Research Projects · FY 2026 · 2020-09

The “clinical high risk” (CHR) for psychosis syndrome is an antecedent period characterized by attenuated psychotic symptoms marked by subtle deviations from normal development in thinking, motivation, affect, behavior, and a decline in functioning. Early intervention in this CHR population is critical to prevent psychosis onset as well as other adverse outcomes. However, the presentation of symptoms and subsequent course is highly variable, and there is a paucity of biomarkers to guide treatment development. Thus, to improve predictive, clinically relevant models, several issues need to be addressed: 1) focusing on outcomes beyond psychosis; 2) consider the heterogeneity in samples and outcomes; and 3) integrating data sets with a broad array of variables using innovative algorithms to overcome variability across studies. To address these challenges, the proposed “Psychosis Risk Evaluation Data Integration and Computational Technologies: Data Processing, Analysis, and Coordination Center” (PREDICT-DPACC) brings together a multidisciplinary team of highly experienced researchers with proven capabilities in all aspects of large-scale studies, CHR studies, as well as computational expertise. The ultimate goal is to identify new CHR biomarkers, and CHR subtypes that will enhance future clinical trials. To do so, the PREDICT-DPACC will 1) aggregate extant CHR related data sets from legacy datasets; 2) provide collaborative management, direction, data processing and coordination for new U01 multisite network(s); and 3) develop and apply advanced algorithms to identify biomarkers that predict outcomes, and to stratify CHR into subtypes based on outcome trajectories, first from the extant data and then refined and applied to the new data. The PREDICT-DPACC team has the broad, comprehensive, and robust infrastructure that is sufficiently flexible to accommodate the inclusion of multiple data types and to optimally address the needs of the CHR U01 network(s). Carefully selected extant data will be rapidly obtained, processed, and uploaded to the NIMH Data Archive (NDA). Proposed analysis methods are powerful and robust, leveraging the expertise and experience of computer scientist developers, and experienced clinical researchers. The U01 network(s) will be coordinated by a team that is experienced in managing large studies, familiar with the needs of such studies, flexible, and is knowledgeable in all aspects of CHR studies, including measures, outcomes, biomarkers, and cohorts. Upon meeting the goals of this U24, and the supported U01 network(s), the expected outcomes of the PREDICT-DPACC will be new predictive biomarkers for CHR outcomes, new definitions of CHR subtypes that are clinically useful, and new curated and comprehensive CHR datasets (extant and new) as well as processing tools and prediction algorithms that are shared with the research community through the NIMH Data Archive. The U.S. population is impacted by CHR and the information garnered will advance our understanding of the trajectory and clinical outcomes in this population and enable intervention at the earliest stage of schizophrenia.

NIH Research Projects · FY 2024 · 2020-09

ABSTRACT In this K01 application, I will design and conduct a pilot study of a novel behavioral intervention to improve obstructive sleep apnea (OSA) evaluation and treatment among transportation workers. I will also explore whether improved adherence to recommended OSA evaluation and treatment is mediated by OSA self- efficacy. The proposed study will use qualitative and quantitative methods to design a tailored text messaging intervention with the aim of increasing OSA self-efficacy, leading to recommended OSA evaluation and treatment among transportation workers. Candidate: The proposed K01 will provide me with critical training in the development and evaluation of novel behavioral interventions. Training in (1) OSA research, (2) designing novel intervention packages, (3) clinical trials design to test behavioral interventions, (4) collecting and analyzing ecological momentary assessment data, and (5) designing and evaluating adaptive interventions, and (6) career development will bridge my prior training in health communication (doctoral training, Cornell University) and behavioral sleep medicine research (postdoctoral training, NYU School of Medicine). This training in underdeveloped areas of my background will allow me to reach my career goal, which is to transition to become a leading health communication researcher specializing in novel intervention approaches to improve sleep disorders awareness, evaluation, and treatment. In consultation with my Primary Mentor, Dr. Girardin Jean-Louis, I have assembled a comprehensive training plan, including coursework and apprentice- ship like training, which will be delivered and monitored by a cadre of outstanding scientists who will serve as scientific and career mentors . Environment: The superb educational and training environment at the NYU School of Medicine will provide me with the optimal training experience to become a federally funded, independent researcher designing interventions to improve adherence to sleep disorders evaluation and long- term treatment adherence. Research: The goal of this K01 application is to identify OSA barriers and facilitators, develop tailored health messages, and conduct a pilot study assessing their feasibility for improving adherence to recommended OSA evaluation and treatment among transportation workers. I will design an adaptive intervention to nudge and navigate transportation workers along their individual position on a spectrum of readiness to change. Messages will be delivered via text messaging in a mobile health (mHealth) approach. Messages will be designed to increase self-efficacy (i.e., belief in one’s ability to perform a recommended behavior such as adhering to recommended OSA evaluation and treatment) in accordance with Social Cognitive Theory. Future Directions: Results from this K01 will provide the necessary preliminary data for my first R01 submission to evaluate the effectiveness of the proposed intervention for improving OSA evaluation and treatment among transportation workers.

NIH Research Projects · FY 2024 · 2020-09

PROJECT SUMMARY/ABSTRACT This proposal requests support for a five-year program of training and research to better understand how distinct brain circuits can be mapped and selectively stimulated with transcranial magnetic stimulation (TMS) to treat different symptoms of major depression. In the proposed training plan, I will build upon my previous psychiatric and computational experience to perform a multidisciplinary project at Beth Israel Deaconess Medical Center. My career development plan includes training in brain circuit mapping, neuromodulation, biostatistics/data science, psychiatric phenotyping, clinical trials, and general translational research. TMS is an effective treatment for major depression which is capable of modulating specific brain circuits. However, efficacy varies greatly across patients and the mechanisms are not well-understood. Recent work from our lab shows that the efficacy of TMS can be improved by stimulating specific targets based on their connectivity profile. Additionally, different TMS targets can modulate different brain networks which may be involved in different symptoms of depression. The brain circuit connected to each stimulation site can be mapped by using functional connectivity MRI (fcMRI), either at the group level or the individual level. A general estimated map of stimulation site connectivity can be generated from the human connectome, a normative wiring diagram of the human brain based on fcMRI of a thousand healthy controls. A more precise map of connectivity can be generated based on subject-specific fcMRI data. This proposal aims to personalize TMS targets based on symptoms, emotional task performance, and brain connectivity. In my preliminary data, this approach yielded distinct circuits responsible for improvement in “dysphoric” versus “anxiosomatic” symptom clusters. However, these results are limited by retrospective nature, reliance on subjective symptom scales, and reliance on group-based connectivity. In this proposal, I will address these limitations by confirming our results in a prospective randomized trial, incorporating task-based behavioral metrics, and incorporating subject-specific connectivity. More broadly, this research aims to develop a model for mapping specific circuits associated with distinct symptom clusters that can be modulated with therapeutic brain stimulation. This will lay the foundation for personalized approaches to transdiagnostic neuromodulation in clinical psychiatry.

NIH Research Projects · FY 2024 · 2020-09

PROJECT SUMMARY/ABSTRACT Allogeneic stem cell transplantation is a potentially curative treatment for some hematologic malignancies, and it often requires a 3-4-week hospitalization. Notwithstanding the promising nature, the transplantation process and recovery is intensive and fraught with potential life-threatening complications during acute and long-term recovery. Hence, allogeneic transplant recipients have a high burden of psychological distress, and quality of life (QOL) deficits are common. Most efforts to achieve optimal psychological well-being in this population have targeted the reduction of distress symptoms (e.g., depression and anxiety). However, positive psychological well-being (e.g., optimism, positive affect) can buffer against this distress and has been prospectively associated with improved QOL, physical functioning, and survival in allogeneic transplant patients. Positive psychological interventions (PPIs), which utilize systematic activities (e.g., recalling positive life events, using personal strengths) to promote psychological well-being, have consistently and durably enhanced psychological health and QOL in medical settings, but have never been used in allogeneic transplant patients. Given the need for new programs to promote well-being and recovery after allogeneic transplantation, the proposed project will develop and test a novel PPI in allogeneic transplant recipients, PATH (Positive psychology for Allogeneic Transplantation of Hematopoietic stem cells), to fill this unmet need. Principal Investigator Dr. Amonoo will develop the PATH intervention via a review of the literature and application of a theoretical framework and test its acceptability (via quantitative participant ratings and qualitative feedback at exit interviews) in a one-arm proof- of-concept trial (N=10; Aim 1). Next, Dr. Amonoo will test the feasibility (primary outcome) and preliminary efficacy of the PATH intervention (refined using Aim 1) on psychological, functional, and behavioral outcomes in a pilot randomized controlled trial with 70 allogeneic transplant recipients (Aim 2). Finally, in Aim 3, Dr. Amonoo will use individual semi-structured interviews with Aim 2 pilot trial participants and 20 oncology clinicians to explore the facilitators and barriers to implementing PATH in clinical settings. This project will facilitate training essential to Dr. Amonoo’s research career goals: intervention development, clinical trial design and execution, advanced biostatistics, and implementation science. Dr. Amonoo has assembled dedicated mentors who are renowned researchers with complementary expertise: PPI trials in medical populations (primary mentor: Jeff Huffman, MD), supportive oncology interventions (co-mentor: Areej El-Jawahri, MD), quantitative methods (co- mentor: William Pirl, MD), implementation science (co-mentor: Elyse Park, PhD, MPH), and biostatistics (research advisor: Brian Healy, PhD). Dr. Amonoo’s mentorship will be supplemented by structured coursework, seminars, and conferences. In sum, this K08 award will prepare Dr. Amonoo to become an independent R01- funded investigator and leader who develops novel evidence-based supportive care interventions to improve health outcomes for allogeneic transplant patients and other vulnerable cancer populations.

NIH Research Projects · FY 2024 · 2020-09

PROJECT SUMMARY/ABSTRACT This is a new application proposing to conduct the SUBstituting with Preferred OPtions (SUB-POP) trial, a parallel-arm RCT to test the effects of substituting SSBs with non-caloric options on body weight and markers of T2D and cardiometabolic health. Eligible adult participants will be randomized to 1 of 4 beverage groups (N=135 per group) at the baseline in-person visit and all will receive at-home monthly deliveries of beverages via Amazon for 6 months. In-person clinic visits will be conducted at baseline, 6, and 12 months. After the 6 months of assigned beverage substitution and delivery, all participants will be instructed to substitute SSBs with water only for a final 6 month observational period. In-person clinic visits will collect technician-measured anthropometrics, blood pressure, biospecimen samples (blood, urine, stool [subset n=50 per group]), and questionnaires (physical activity, beverage frequency), and taste preference test. The SUB-POP app-based assessments and online diet recall will ascertain repeated measures of beverage adherence, diet, physical activity, and appetite in the interim, every 3 months. A subset (n=60 per group) will receive at home Wi-Fi digital scales to measure body weight approximately daily for novel energy balance and caloric compensation modeling. Our proposal will leverage the many strengths and state-of-the-art clinical trial infrastructure of the Division of Preventive Medicine at BWH. The highly collaborative investigator team is comprised of experts in nutritional and obesity epidemiology, clinical trial design, implementation and analysis, energy balance and weight loss, and interpretation for public health dietary guidelines. SUB-POP is a novel RCT that will enroll adult regular SSB consumers with overweight or obesity to evaluate the effectiveness of substituting SSBs with non-caloric options in a real-world, un-blinded setting. Our trial will leverage modern recruitment methods, achieve ≥30% non-White participants, implement innovative intervention delivery, adherence, and data collection tools, and partition the two most common artificial sweetener types to explore potential heterogeneity. It is unknown whether ASBs, which are largely free of calories and sugar, provide a healthful interim strategy to transition to water among habitual SSB consumers. Thus, by addressing this large gap in our understanding of how to address a highly prevalent and concerning dietary exposure, we will inform dietary guidelines and clinical recommendations for the prevention of obesity, T2D, and cardiometabolic disease risks.

NIH Research Projects · FY 2024 · 2020-09

PROJECT SUMMARY Acute kidney injury (AKI) is a common and often devastating complication of cardiac surgery, critical illness, and other clinical settings. No pharmacologic therapy reliably prevents or treats AKI. Abundant data from both animal models and humans indicates that iron plays a key role in the pathogenesis of AKI, particularly in the setting of cardiac surgery. We propose a phase II, double-blind, randomized controlled trial to test whether administration of the iron chelating agent, deferoxamine (DFO), prevents AKI following cardiac surgery. We will enroll 300 adult patients at high risk of AKI following cardiac surgery at three major academic medical centers in Boston. Patients will be randomly assigned, in a 1:1 fashion (n=150/group), to receive DFO (30 mg/kg) or an equal volume of normal saline. DFO (or normal saline) will be administered as a continuous 24-hour intravenous infusion beginning immediately prior to surgery. In Aim 1 we will test the effects of DFO compared to placebo on the incidence of postoperative AKI (primary endpoint). AKI will be defined by changes in serum creatinine and urine output, according to the KDIGO criteria. As secondary endpoints, we will assess longitudinal changes in urinary tubular injury markers, NGAL and KIM-1. We will also test the effects of DFO on the incidence of the following common and biologically plausible extrarenal postoperative endpoints: myocardial infarction, atrial fibrillation, delirium, prolonged mechanical ventilation, and sepsis. In Aim 2 we will tests the effects of DFO compared to placebo on longitudinal measures of circulating iron and oxidative stress, and the inflammatory phenotype of monocytes. Serum iron parameters will include catalytic iron – a toxic, non-physiologic iron species – as well as transferrin saturation and ferritin. Plasma markers of oxidative stress will include F(2)-isoprostane and myeloperoxidase. We will also assess the effect of DFO versus placebo on monocyte (CD14+) expression of IL-6, TNFα, and other markers of inflammation using flow cytometry. In exploratory analyses, we will use next-generation RNA sequencing (RNA-Seq) to assess the effect of DFO on the transcriptome of monocytes, which will facilitate discovery of novel transcripts influenced by DFO. We will also determine the extent to which the effect of DFO on renal and extrarenal acute organ injury (assessed in Aim 1) varies depending on the preoperative expression of key parameters measured in Aim 2. In aggregate, the studies proposed here will test a novel and promising therapeutic strategy for AKI prevention. These studies have strong potential to improve clinical outcomes in patients at risk for AKI. Further, the translational studies proposed here will yield important scientific insights into the role of iron metabolism in the pathophysiology of AKI.

NIH Research Projects · FY 2025 · 2020-09

Stroke survivors are vulnerable to reduced social interactions. Reduced interactions are related to worse physical recovery after stroke. Enhancing social interactions after stroke may be one of the most powerful strategies to improve stroke recovery. Social interactions are defined as the synchronous interactions, commonly verbal, between individuals who are usually co-present in the same physical location. Current ways to detect social interactions rely on self-report, which cannot be performed reliably by patients with language or cognitive deficits. Patients with such deficits are most vulnerable to social isolation. This project introduces a new wearable social sensor, SocialBit, that can detect audio signatures of social interactions in real-world settings. Our preliminary data show that SocialBit can detect social interactions accurately (~95%), and it can do so by processing select audio features without storing raw audio data. Therefore, the technology detects and measures the duration of the social interaction while preserving the privacy of the content during the interaction. Based on these findings, we have developed a research plan to establish the usefulness of SocialBit in stroke survivors in the immediate post-stroke period. The post-stroke period is apt for such a study because 1) patients are vulnerable to social deprivation in this time period, and 2) the bounded nature of an inpatient setting provides an ideal environment to test SocialBit against a ground truth of directly observed social interactions. Our central hypothesis is that SocialBit can accurately detect social interactions in stroke survivors in inpatient settings. This project is primarily designed to establish the accuracy of SocialBit to detect social interaction in patients with varying deficits against the ground truth of video-assisted, real- time observation in the post-stroke period. First, we will examine the accuracy of SocialBit to detect the social interaction time against direct observation in 200 patients (Aim 1). Second, we will determine the association of social interaction time to social isolation and stroke outcomes at 3 months (Aim 2). Finally, we will determine the medical factors associated with social interaction time (Aim 3). This study will establish the key criteria of quantifying social interaction in stroke recovery research. The project will (a) identify automatic and unobtrusive methods to measure social interaction, (b) determine key design and outcome criteria for a future intervention trial, and (c) increase our understanding of underlying mechanisms in social changes after stroke. In so doing, this study will address the public health priority of building better behavioral modification strategies for patients with stroke.

NIH Research Projects · FY 2024 · 2020-09

Summary/Abstract High throughput sequencing of the rearranged T cell receptor genes (HTS) has transformed the diagnosis, care and assessment of therapeutic responses in patients with cutaneous T cell lymphoma (CTCL) and this assay is becoming the gold standard in CTCL clinical trials. HTS results are highly reproducible in frozen CTCL skin biopsies but the formalin used to preserve skin biopsies in many clinical trials degrades DNA and affects HTS measurements, potentially causing errors in patient diagnosis, assessment of responses and choices of therapy. We seek to identify a single uniform tissue processing approach for small CTCL skin biopsies that will give accurate and reproducible HTS results, support DNA, RNA and protein measurements, maintain excellent histology, and preserve remaining tissue for future measurement of emerging biomarkers. In Aim 1, we identify optimal tissue transport conditions and test non-cross-linking fixatives for their ability to support nucleic acid, protein and histologic studies on small skin biopsies. Aim 2 studies the effects of storage time and temperature on nucleic acid integrity, histologic performance and HTS readings, and tests two approaches to mitigate the effects of DNA degradation on HTS measurements. Aim 3 provides real world testing of our optimized sample handling procedures, using them to study skin biopsies obtained in the industry sponsored, randomized, placebo- controlled phase III trial of topical resiquimod gel in CTCL. Our overall goals are to establish new best tissue handling practices for future clinical trials and to establish corrections that allow accurate analyses of existing specimens. HTS is now frequently used in many cancer types to measure tumor T cell numbers, diversity and responses to immune therapies. The optimized tissue handling procedures we identify therefore have the potential to be useful in many cancer types.

NIH Research Projects · FY 2025 · 2020-08

Multiple sclerosis (MS) is a chronic inflammatory neurodegenerative disorder of the central nervous system (CNS) and is the leading cause of disability in young adults, afflicting some 400,000 U.S. citizens and generating an economic burden of approximately $10 billion annually. MS results from an incompletely understood interaction between genetic and environmental factors that triggers an autoimmune response against CNS myelin. Chronic CNS inflammation induces pro-inflammatory programs in CNS-resident cells such as astrocytes and microglia, which are not responsive to the therapeutic approaches currently available for MS. Astrocytes are abundant CNS-resident cells which participate in multiple aspects of CNS homeostasis in health and disease, including pro-inflammatory signaling in the context of MS and its animal model, experimental autoimmune encephalomyelitis (EAE). Thus, the study of the mechanisms that regulate astrocyte pro-inflammatory activities may identify mechanisms of disease pathogenesis in MS, as well as novel efficacious therapies, particularly for its progressive phase. In previous studies focused on environmental factors in MS, we identified a signaling pathway in astrocytes that is controlled by environmental pollutants, and drives astrocyte pathogenic activities that promote inflammation and neurodegeneration in EAE and MS. Specifically, we found that the endoplasmic reticulum (ER)-localized receptor SigmaR1 stabilizes the inositol requiring enzyme 1-alpha (IRE1a), leading to the activation of the transcription factor X-box binding protein 1 (XBP1) which promotes pro-inflammatory gene expression in astrocytes. In genetic perturbation studies we demonstrated that SigmaR1-driven IRE1a-XBP1 activation boosts the expression of pro-inflammatory and neurotoxic transcriptional programs in astrocytes such as Nos2, Ccl2, Il6, Csf2 (GM-CSF), and Csf2ra (the GM-CSF receptor) during EAE. Moreover, we detected increased IRE1a-XBP1 activation in astrocytes localized to MS lesions. I hypothesize that SigmaR1-IRE1a- XBP1 signaling drives astrocyte pathogenic activities in EAE and MS. Thus, I propose the following Aims: AIM 1: Mentored phase (K99). Define astrocyte subpopulations driven by SigmaR1-IRE1a-XBP1 signaling (XBP1+ astrocytes) in both EAE (Aim 1.1) and MS (Aim 1.2) using single-cell RNA sequencing (scRNA-seq). AIM 2: Mentored phase (K99). Test the therapeutic potential of suppressing XBP1 signaling with clinically- relevant SigmaR1 inhibitors using EAE mouse models (Aims 2.1-2.2), and scRNA-seq (Aim 2.3). AIM 3: Independent investigator phase (R00). Study the regulation of GM-CSF signaling in XBP1+ astrocytes using spatial transcriptomic approaches including NICHE-seq (Aim 3.1) and MERFISH (Aim 3.2). Taken together, these studies will define a novel disease-associated astrocyte population, identify the molecular mechanisms that control it, and evaluate the therapeutic value of its pharmacologic manipulation.

NIH Research Projects · FY 2024 · 2020-08

ABSTRACT Recent meta-analyses have found that participation in the appropriate fall-prevention exercise program for an older adult reduces the risk of falls by 23% in relative terms, for an absolute reduction of 0.20 falls per person per year. Many guidelines, including the US Preventive Service Task Force (USPSTF), recommend that older adults at risk of falls are referred to appropriate fall-prevention exercise programs (USPSTF Level B). Despite this evidence, many older adults do not receive appropriate referrals and support for fall-prevention exercises, with one study finding that less than half of older persons report discussing their falls with their primary care providers (PCPs). Older people living in rural areas are more likely to fall but are less likely to participate in fall prevention programs. Advances in computing technology can help to identify older people at risk of falls and disseminate guidance about the most effective interventions using clinical decision support (CDS) systems. Patients can be supported in their exercise programs through a patient-focused App distributed through the PCP or through content on their patient portal. Well-implemented CDS that is integrated into the electronic health record (EHR) can support prescribing or recommending effective strategies and engaging patients in fall prevention decision-making thus integrating evidence-based guidelines into clinical practice. The long-term goal of our research program is to enhance the safety of community-based older adults by reducing falls through an effective patient-centered learning health system called eSTEPS (electronic Strategies for Tailored Exercise to Prevent FallS). With eSTEPS, an exercise algorithm will be integrated into the EHR which will trigger a Best Practice Alert (BPA) and Smart Set to provide actionable CDS within primary care clinic workflows and facilitate the use of CDS with patients to ensure evidence-based recommendations are tailored to patient preferences. The resulting fall prevention exercise care plan will be sent to the EHR as a note and to a patient-facing App for the patient to view after their visit. In this proposal we will use traditional fall risk screening and machine learning approaches to accurately identify older adults at risk for falls. We will then develop, CDS implemented into the electronic health record that helps primary care providers and older patients develop a tailored fall prevention exercise plan. We will conduct a cluster randomized control trial in urban and rural primary care clinics to test the efficacy of the eSTEPS CDS intervention. Development of the eSTEPS CDS within the widely adopted Epic EHR will support dissemination of evidence for older adults, with a focus on rural elders.

NIH Research Projects · FY 2024 · 2020-08

Project Summary/Abstract Multiple myeloma (MM) is an incurable cancer of terminally differentiated plasma cells (PC), characterized by abundant immunoglobulin (Ig) synthesis. Most PC are short lived and die only a few days after differentiation through unclear molecular mechanisms. MM pathogenesis also remain elusive with no single genetic driver mutation, but pervasive DNA damage. We have previously shown increased cargo of polyubiquitinated (polyUb) proteins and decreased proteasome activity in differentiating B lymphocytes and we hypothesized proteotoxicity as driver of PC death. By using absolute mass spectrometry (AQUA) to quantify ubiquitin (Ub) in the same B cell differentiation model, our preliminary data show that 60% free Ub depletion occurs in PC compared to resting B cells, concomitantly with maximal Ig secretion and apoptosis. Second, we discovered that cells surviving long term post differentiation can be identified and display markers of ongoing DNA damage. As Ub is necessary for proper DNA damage response (DDR), polyUb protein degradation and DDR compete for the same Ub pool. Based on our work, we propose a unifying model for short-lived PC death and MM pathogenesis centered on critical Ub depletion. Our core hypothesis is that in PC, proteotoxic stress secondary to sustained Ig synthesis, leads to free Ub depletion thus causing impaired DDR. Most PC will be unable to recover from this crisis, however a small subset of genomically unstable PC may survive, presumably due to accumulation of survival promoting mutations, constituting a premalignant state for MM. We further hypothesize that Ub gene Ubc may be a haploinsufficient tumor suppressor genes in B cell malignancies. Herein, the applicant, Dr. Giada Bianchi, presents a comprehensive plan to test these hypotheses articulated in 2 specific aims: (1) to probe a causative link between Ig synthesis, Ub depletion and apoptosis in PC; and (2) to evaluate whether Ub depletion is sufficient to cause genomic instability in PC and drive MM pathogenesis. Data gathered during the course of our investigation will provide novel data regarding the biology of normal and malignant PC and potentially uncover a novel oncogenic mechanism - functional depletion of Ub - with applicability to other malignancies and opportunity for innovative, molecularly targeted therapies. To this end, Dr. Bianchi has carefully selected a mentoring committee and collaborators who are world-renowned experts in Ub, MM, DDR, proteomics and B cell biology. Such team will provide knowledge, models and technologies to render the testing of Dr. Bianchi’s hypotheses feasible within the proposed 5-year frame. The applicant’s mentoring committee has furthermore designed a detailed career plan based on regular meeting, attendance of workshops, classes and international meetings which will further accelerate the trajectory of Dr. Bianchi to become an independent investigator in cancer biology in the next 5 years.