# data[].attributes.title
The Effects of COVID-19 on the Well-being, Cognition and Mortality of Persons Living With Dementia

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Although the prevalence of Alzheimer’s disease and related dementias (ADRD) has been decreasing, the COVID-19 pandemic may have halted or reversed that trend. This project will quantify the effects of the pandemic and of attendant public health and social measures on the cognitive status, mortality, and well-being of persons living with ADRD and of the older population in general. Persons living with dementia were especially vulnerable to COVID-19 because many were living in nursing homes, and even those residing in the community were disproportionately vulnerable because of caregivers coming to their homes. Further, those initially not living with dementia may have experienced accelerated cognitive decline because of COVID-19 infections, as well as due to disruption of daily routines, social isolation and stress. Subpopulations by race, ethnicity and socioeconomic status were impacted unequally.  This project has three specific aims. The first is to use a new and updated model of cognition to estimate trends in ADRD prevalence, incidence, and mortality prior to the pandemic. We will use data from the Health and Retirement Study (HRS), a large, nationally representative, longitudinal survey of the U.S. population over age 50. The HRS has a wide range of information on cognitive abilities, mortality, dementia risks, and physical and mental health, but only a subsample of the HRS from the Aging, Demographic, and Memory Study (ADAMS) has a clinical assessment of dementia. In prior research, we used ADAMS to develop a model of the probability of dementia to estimate the cognitive status of the entire HRS sample. In this work, we will expand this model to estimate dementia incidence and mortality as well, and incorporate recently released data from the Harmonized Cognitive Assessment Protocol, further increasing precision so as to permit the study of changes in ADRD resulting from the pandemic in subpopulations, such as race and ethnicity, marital status, and socioeconomic status.  Second, we will document changes associated with the pandemic in mortality, well-being, use of formal and informal care, and other outcomes. We will incorporate variation in state policies to assess their effect on individual outcomes. We will compare these effects among those who were living with dementia prior to the pandemic to those whose cognitive function was normal. We will use innovative models and data from various HRS supplements focusing on COVID-19 to estimate these effects with precision.  Third, we will estimate the incidence of dementia and dementia mortality after the pandemic through 2026 and find the extent to which COVID-19 altered pre-pandemic trends. We will assess whether ADRD incidence differed by individual characteristics, such as geographic location, race, socioeconomic status, and living arrangements. The developed cognition measures will be made publicly available to enhance future research.

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Improving emergency psychiatric care through machine learning, causal inference, and psychometrics

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National Institute of Mental Health (NIMH)

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Background: The United States is experiencing a crisis in mental health care, in which long-term shifts towards the emergency department (ED) for psychiatric treatment have been exacerbated by the COVID-19 pandemic – reduced inpatient hospitalization capacity, delayed outpatient appointments, extended ED boarding, and staffing shortages, combined with substantial growth in demand for mental health services (due in part to pandemic-related increases in stress, depression, social isolation, and anxiety, and with differential impacts on vulnerable populations). Data-driven approaches have not been widely applied to understand mechanisms and predictors of ED utilization for psychiatric patients, or to optimize clinical decision-making to improve patient outcomes. Research: In this study, I will conduct secondary data analysis of 141,431 ED visits for psychiatric care in a large regional health system from 2017-2023, extracting and preparing over 5,000 patient characteristics from the electronic health record (diagnoses, labs, medications, procedures, visits, and notes). Aim 1: I will create a transdiagnostic subtyping system, using latent class analysis, hierarchical density- based clustering, and neural network autoencoders, to reliably categorize and track major trends in patient populations receiving emergency psychiatric care. Aim 2: I will develop a suite of ensemble machine learning models to predict ED length of stay, ED boarding duration, short-term ED re-admission, transfer to inpatient hospitalization, and post-discharge adverse events (suicide attempt, overdose, or psychotic episode). Aim 3: I will estimate a precision treatment rule, using targeted causal inference and ensemble machine learning, to capture heterogeneous treatment effects for primary ED disposition decisions (inpatient hospitalization, partial hospitalization / intensive outpatient program, or outpatient monitoring) on adverse psychiatric events. Candidate's Career Development, Goals, and Environment: This proposal's research aims and the candidate's career development will be supported by the extensive resources available at Massachusetts General Hospital (MGH) and Harvard Medical School, as well as formal training, coursework, and mentorship in (T1) mental disorders and psychopathology, (T2) precision treatment optimization, (T3) hybrid pragmatic effectiveness trials, and (T4) professional development in preparation for a future R01 submission. The mentorship team includes Primary Mentor Dr. Jordan Smoller, a leading expert in precision psychiatry; Co- Mentors Dr. Matthew Nock, a leader in mental disorders and suicide prevention; Dr. Susan Murphy, a leader in precision treatment optimization; and Dr. Stephen Bartels, a leader in implementation science and hybrid pragmatic trials; and Consultants Dr. Suzanne Bird, expert in emergency psychiatry and director of MGH Acute Psychiatry Services; Dr. Edwin Boudreaux, expert in hybrid pragmatic trials in emergency psychiatry; and Dr. Soroush Saghafian, expert in reinforcement learning to optimize hospital decision-making. This award will enable the candidate to develop an independent, rigorous research program in computational mental health.

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United States Substance Abuse and Mental Health Services Administration

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Development and Characterization of Phage QBeta-Based SARS-CoV-2 RT-qPCR Assay Calibration Standards

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National Institute of Allergy and Infectious Diseases (NIAID)

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SARS-CoV-2 RT-PCR assays, one of the two major testing modalities used for diagnosis of COVID-19, are inherently quantitative. This has led to use of cycle threshold values for determining (a) if a tested individual remains infectious; (b) whether therapeutic approaches are working in immunocompromised patients; (c) whether a specific illness is more or less likely to be a result of SARS-CoV-2 infection or some other cause; and (d) whether a positive PCR test represents a current infection or prolonged detection of residual SARS-CoV-2 RNA that may linger for months after an original infection. Cycle threshold (Ct) values are the first cycle during PCR amplification during which fluorescence signal crosses a reliable instrument detection threshold. Unfortunately, Ct values are both assay and instrument specific. In fact, for any given Ct value, viral loads (the amount of virus in a nasal or nasopharyngeal sample) may vary over one thousand-fold depending on the testing platform. Traditionally, quantitative PCR assays are calibrated with standards which allow conversion of a test method-dependent Ct value to a test method-independent viral load. The latter directly reflects the amount of virus in a sample. Therefore, there is strong impetus to develop calibrators covering the billion-fold range of viral loads observed in COVID-19 infected individuals. Furthermore, these calibrators should be inexpensive and accessible to diagnostic and research laboratories. However, currently available calibration standards are very expensive, available in small quantities, labile, and/or do not reflect the higher viral load levels that identify infectious individuals and signify ongoing infection in immunocompromised patients. Therefore, here we propose to develop calibrators that address these needs. We identified the positive-strand RNA Qb bacteriophage as a compelling vector in which to clone SARS-CoV-2 PCR target sequence for calibrator development. Importantly, as an encapsidated single-strand RNA calibrator, such Qb derivatives will be able to assess inefficiencies in extraction, reverse transcription, and amplification phases of PCR tests; are inherently stable; and can be grown to high titers that encompass the upper range of viral loads observed in specimens. The proposal will examine the ability of the Qb to tolerate heterologous SARS-CoV-2 PCR target sequence inserted into Qb A1 and RNA- dependent RNA polymerase genes with or without complementation of phage functionality in trans. Lastly, we will validate calibrators through interrogation of two major commercial platform diagnostic SARS-CoV-2 PCR assays, and, as proof-of-principle, use these calibrators as a tool to establish their comparative analytical measurement range and limit of detection. Taken together, we will establish a new set of inexpensive, readily available reagents for use by the clinical and scientific community to enhance standardization and rigor of data available from SARS-CoV-2 PCR diagnostics.

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Reverse Transcriptase Polymerase Chain Reaction

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Targeted treatment of acute lung injury using isolated lung perfusion

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National Heart Lung and Blood Institute (NHLBI)

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Acute lung injury in the form of acute respiratory distress syndrome (ARDS) or ischemia-reperfusion injury (IRI) after lung transplant remains a major clinical issue associated with high morbidity and mortality. Currently, no methods exist for targeted treatment and rapid rehabilitation of lungs affected by ARDS. The majority of treatment strategies remain supportive in nature and are associated with continued poor outcomes. We have demonstrated breakthrough methods for treatment or prevention of acute lung injury via normothermic perfusion of isolated lungs in the form of ex vivo lung perfusion (EVLP) for marginal donor lungs or in vivo lung perfusion (IVLP) for ARDS. IVLP combines the benefits of extracorporeal membrane oxygenation and EVLP to provide a platform upon which injured lungs can be treated in vivo with targeted therapies in an isolated fashion without the potential risks of systemic treatment. We have demonstrated the rehabilitative capacity of isolated lung perfusion with Steen solution whereby sepsis-induced ARDS as well as IRI of transplanted donation after circulatory death (DCD) lungs are attenuated. We have also demonstrated that Steen solution directly preserves pulmonary endothelial barrier function and that inhibition of Panx1 or TRPV4 channels attenuates lung IRI via endothelial barrier protection. Thus, this project will test the overall hypothesis that rehabilitation of injured lungs by isolated, normothermic perfusion with Steen solution can be augmented by Panx1- or TRPV4-targeted therapy aimed at preserving endothelial barrier function to attenuate vascular inflammation and improve lung function.  We will test our hypothesis using porcine and murine models of IVLP and EVLP of lungs injured by ARDS or IRI in three specific aims. Aim 1 will determine if isolated perfusion with Steen solution will rehabilitate injured lungs and if inhibition of Panx1 or TRPV4 during perfusion will augment rehabilitation and endothelial barrier function. Aim 1A will use a porcine, LPS-induced ARDS model to determine if IVLP provides durable lung rehabilitation up to 24 hours after IVLP. Aim 1B will determine if IVLP rehabilitates lungs injured in a porcine model of gastric aspiration-induced ARDS. Aim 1C will determine if EVLP rehabilitates murine lungs injured by ARDS caused by SARS-CoV-2 infection. Aim 2 will use a porcine lung transplant model to determine if rehabilitation of DCD lungs by EVLP can be augmented by treatment with Panx1 or TRPV4 inhibitor for successful transplant. Aim 3 will use in vitro models of LPS-induced injury to determine protective mechanisms of Steen solution involving direct anti-inflammatory effects on alveolar-capillary barrier or leukocytes. Our recent studies demonstrate the potential of IVLP for the treatment of severe ARDS, representing a major paradigm shift in the management of ARDS. If successful, our proposed studies will define IVLP as a novel platform for targeted therapy of severe ARDS and will facilitate clinical translation.

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Mechanisms of anosmia and brain infection in a genetic mouse model of COVID-19

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National Institute on Deafness and Other Communication Disorders (NIDCD)

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Infection of the olfactory epithelium in COVID-19 patients is thought to underlie loss of smell (anosmia), a pathognomonic symptom that can be long-term in some patients, significantly affecting quality of life. The olfactory epithelium is also believed to be a major entry point for systemic SARS-CoV-2 infection, which can result in neurological as well as respiratory symptoms. Wild-type SARS-CoV-2 cannot bind the mouse ACE2 receptor, and existing human ACE2 (hACE2)-expressing mouse models either do not permit conditional analysis or do not confer severe illness after infection. Due to the lack of genetically manipulable models that display severe disease, the infected cell types responsible for acute and long-term anosmia, and the route(s) by which the virus penetrates the brain, have not been definitively identified. To address these gaps in knowledge and test cell type-specific requirements for COVID-19-related pathologies we generated conditional hACE2fl knockin mice that express hACE2 in similar cell types to humans. hACE2fl mice nasally inoculated with a high dose of wild-type SARS-CoV-2 display initial infection of olfactory epithelium and rapidly develop anosmia. This is followed by infection of neurons in the olfactory bulb and brain, which is associated with lethality and requires neuronal hACE2 expression. Importantly, specific destruction of olfactory epithelium via methimazole treatment prevents olfactory bulb and brain infection and lethality, identifying the olfactory epithelium as an essential gateway to CNS infection. hACE2fl mice inoculated with a low dose of wild-type SARS-CoV-2 show reversible disease and survive, but a subset displays a long-term decrease in odor sensitivity (hyposmia) like that observed in humans. We propose to use hACE2fl mice to provide definitive genetic evidence for cellular mechanisms of short- and long-term loss of smell and identify the pathways for brain infection during COVID-19. These studies are expected to complement existing descriptive human studies to identify causal pathogenic mechanisms and preventative and therapeutic targets. Three specific aims will be pursued: (i) define the cellular requirements for acute loss of smell; (ii) determine the mechanisms of long-term hyposmia; and (iii) uncover the cellular mechanisms of olfactory bulb and brain infection.

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Proyecto Tariki: Implementation Science for Community-Mobilized Risk Reduction of Dengue

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National Institute of Allergy and Infectious Diseases (NIAID)

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There is scientific consensus that there are effective tools and strategies to control dengue, but program failures are linked to improper implementation. This project brings together researchers with >23 years of experience in community-based epidemiological dengue research in Iquitos, implementation science, and a team that successfully developed and implemented a software platform DengueChat, in Nicaragua and Paraguay, that mobilized communities to control mosquito producing containers in their own homes. Our project directly addresses past implementation failures by using implementation science theories, models, and frameworks (INSPIRE, CFIR), dengue epidemiology and entomology expertise, infrastructure and relationships developed in Iquitos and Lima, and addresses three programmatic gaps identified in Iquitos and incorporates key lessons learned from the Covid pandemic (differential response to changing risk level), to develop, implement and evaluate “Proyecto Tariki” – an integrated dengue risk reduction program. Tariki will: (1) mobilize community members to take control measures in their own homes, (2) enhance surveillance of disease vectors and febrile case outbreaks, (3) improve triage and management of cases, (4) target and deploy effective responses during periods of high transmission, (5) promote bi-directional data exchange between community residents, health care providers and authorities, and other stakeholders, and (6) support government programs through community engagement and training and implementation on pragmatic evaluation protocols. We will conduct key-informant interviews and focus group discussions with health and community stakeholders to understand the system problems and establish a fixed-group of stakeholders called the ‘Tariki Champions’ (Aim 1). We will also adapt the proven DengueChat application to Iquitos and expand the platform to include fever surveillance; DengueChat Plus will be the cornerstone of the Tariki program. Tariki Champions will participate in group model building (GMB) workshops throughout the 5-year project to find leverage within the system to plan, implement, and monitor and evaluate Tariki using mixed methods based on RE-AIM metrics focused on epidemiological, entomological, and cost outcomes (Aims 1 and 2). In Year 3, after reviewing all data using the CFIR domains (including program characteristics, costs, and processes), the RMOH will take over management of Tariki and scale up program activities across the city of Iquitos (Aim 3), continuing to monitor the program through RE-AIM metrics and pragmatic evaluations. We hypothesize that Tariki will reduce risk for dengue by improving community mobilization for control, increasing community surveillance for febrile illness and case management, and implementing pragmatic protocols for intervention evaluation.

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Reach  Effectiveness  Adoption  Implementation  and Maintenance

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What is the human antibody response to measles virus vaccination?

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National Institute of Allergy and Infectious Diseases (NIAID)

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Vaccines are the greatest bang for our public health buck, yet vaccine development is still sometimes hit or miss. Recent efforts with SARS-CoV-2 demonstrated that acceleration of vaccine programs is possible, especially when supported by prior studies characterizing successful immune responses against related prototype pathogens. The measles virus vaccination campaign is a global success story; the live-attenuated vaccine developed in the 1960’s still elicits highly protective antibodies to strains circulating today. Yet Measles outbreaks persist due to obstacles in vaccination programs such as global health inequities, vaccine hesitancy, extreme weather events related to climate change, and the SARS-CoV-2 pandemic. Furthermore, a growing population with compromised immune systems cannot receive live-attenuated viral vaccines. Thus, the threat of measles remains (there are still approximately 9-10 million cases annually), and innovative solutions will be needed to achieve global measles eradication. However, very little is known about the human antibody response to measles infection or vaccination beyond neutralizing antibody titers. Importantly, there are no structures of any antibodies in complex with any measles virus antigens. As a result, we do not know which sites on measles virus are immunodominant and protective. Much of this fundamental knowledge is lacking largely because measles was effectively eradicated from developed nations before needed scientific tools had been developed. In this work, we will use state-of-the-art tools to directly visualize the structure of human antibodies from vaccinee polyclonal sera bound to measles surface glycoproteins to understand which antigenic sites dominate in the human vaccinee response. We will also use microfluidics and rapid microscale multiplexed competition analyses to rapidly discover and analyze individual human monoclonal antibodies against measles virus for the first time. This work will reveal what components of the human immune response to this prototype paramyxovirus lead to vaccine-mediated protection, and will help guide development of modern vaccines for the immunocompromised and other vaccines against paramyxoviruses yet to emerge.

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National Institute of Allergy and Infectious Disease

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The Impact of SARS-CoV-2 Infection and Vaccination on the Risk of Alzheimer’s Disease and Related Dementias

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The growing prevalence of Alzheimer’s disease and Alzheimer’s related disorders (ADRD) is a critical public health concern, potentially exacerbated by the COVID-19 pandemic. Infectious diseases may increase ADRD risk by causing neuroinflammation and oxidative damage in the central nervous system, promoting atherosclerosis and endothelial dysfunction, or via other inflammatory, immune-response, and vascular mechanisms. Despite intriguing links between several infectious and neurodegenerative conditions, whether and how infectious diseases influence ADRD risk remains underexplored. This question is urgent especially during the COVID-19 pandemic, where the widespread SARS-CoV-2 infection has heavily impacted global public health. Mounting evidence suggests a significant fraction of those infected with SARS-CoV-2 may experience substantial and long-lasting sequelae, including cognitive decline and neurologic deficits. Many unknowns remain, including long-term outcomes and the role of COVID-19 vaccination and viral variants in modifying the effect of SARS-CoV-2 infection on cognitive decline and ADRD risk. This proposed F99/K00 project seeks to address these gaps with two specific aims using complementary longitudinal datasets and rigorous, advanced epidemiological and statistical methods. Aim 1 (F99 dissertation phase: 2023-2025) will use the previously identified COVID-19 brain magnetic resonance imaging (MRI) signature region to infer the long-term effects of infection on ADRD risk via brain structure changes. The COVID-19 MRI signature region comprises brain regions where cortical thickness and gray-white matter contrast was reduced after SARS- CoV-2 infection (identified in a longitudinal MRI study). The candidate will quantify the association between the COVID-19 MRI signature region and future ADRD risk among UK Biobank participants. Aim 2 (K00 postdoctoral phase: 2025-2029) will evaluate the effects of vaccination status and timing of SARS-CoV-2 infection on cognitive outcomes and ADRD among COVID-19 survivors. The candidate will use data from electronic health records (EHR) and a nationally representative cohort. Methodological innovations include the use of neuroimaging, causal survival analysis, machine learning methods for classification algorithms, as well as multiple data sources (i.e., clinical data from EHR and survey data from cohort studies). This proposal directly responds to the call to study the impact of COVID-19 on risk of ADRD and cognition from the National Alzheimer's Project Act (NAPA). The proposal extends the candidate’s quantitative expertise with advanced training in clinical and biological perspectives on ADRD as well as causal inference methods for aging research. Strong interdisciplinary mentorship teams and outstanding supportive training environments at the University of California, San Francisco (F99) and the Massachusetts General Hospital (K00) provide a foundation for the candidate to fill an important scientific gap on infectious disease and immune-related determinants of cognitive aging and ADRD, including infection with SARS-CoV-2.

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National Clinical Cohort Collaborative (N3C)

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National Center for Advancing Translational Sciences (NCATS)

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N3C is a national resource of real-world data that researchers are using to speed medical research.  With stewardship from NCATS, more than 75 institutions worked together to build N3C. N3C systematically collects data derived from electronic health records from different institutions and harmonizes these data into data enclaves. The enclaves offer spaces for collaborative research. In addition, the enclaves can connect to other data sets, which creates a more complete picture of health outcomes.  Initially created in response to the COVID-19 pandemic, NCATS is piloting the use of the original N3C infrastructure for additional health conditions.  We know that the data in the enclaves represent people. As the steward of the data, we take the responsibility for keeping those data safe very seriously. We have taken a comprehensive approach to address the security of the N3C COVID Enclaves and protect patient privacy.

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CD14 collaborates with TRIF to mediate septic responses downstream of TNF receptors

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National Institute of Allergy and Infectious Diseases (NIAID)

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CD14 is a coreceptor that facilitates the innate immune responses triggered by a broad range of pathogen- derived molecules and host damage-derived danger signals. These properties, which contribute to the rapid mobilization of the immune system, can also contribute to the exacerbation of inflammatory immune responses, particularly when tissue damage is extensive. Because of this, CD14 is an attractive target for the modulation of the 'cytokine storms' associated with severe bacterial sepsis, cancer immunotherapies, and the acute respiratory distress syndrome (ARDS) that is seen in severe cases of COVID-19. Tumor necrosis factor (TNFα) is one of the most prominent inflammatory cytokines associated with these storms, and TNFα-blocking biologicals have proven useful in treating these inflammatory syndromes. However, we currently lack therapies for the persistent immune paralysis associated with sepsis and ARDS. Here, we build on recent findings from our collaborators, who have extended the in vitro coreceptor-like functions of CD14 to the death domain- containing receptors FAS and TNFR1. This is clinically significant, because it suggests that CD14 participates in the induction of inflammatory cytokines and in the effector responses set in motion by those very cytokines. Further studies established that CD14 and TRIF are required for the induction of lethal sepsis by TNFα. In conjunction with in vitro biochemical data, these findings indicate that CD14 modulates the signals initiated by TNFR1 in precisely the same way that it augments LPS-induced signals: by engaging endosomal signaling pathways that act via TRAM, TRIF, TBK1, and IRF3 to promote type-I interferon production and inflammatory cell death. Thus, CD14 may contribute to septic immunoparalysis by inducing the death of immune cells exposed to FasL or TNFα. For this reason, it is crucial to understand how CD14 interacts with these receptors. However, these receptors do not share ligands, and CD14, which is a GPI-anchored protein, lacks the transmembrane and cytoplasmic regions typically associated with signaling effectors. Via an exhaustive analysis of the evolutionary histories of CD14, TNFα, and TNFR1, we identified features that appear to have coevolved in placental mammals and that could plausibly link CD14 to TNFα/TNFR1 complexes. In order to clarify how CD14 contributes to septic phenomena in vivo, this proposal will evaluate the hypothesized link between CD14 and TNFα/TNFR1 complexes (Aim 1), and will determine whether CD14 promotes sepsis via cell-intrinsic signaling events occurring in myeloid cells and/or stromal tissues (Aim 2). These efforts are intended to rapidly narrow the scope of future enquiry by identifying viable mechanisms with the greatest explanatory power. In so doing, this work will set the stage for examinations of these pathways in vivo.