# data[].attributes.title
IND-enabling development of MM010, a PEG-specific intervention that blocks allergic response and restores repeated dosing for select PEGylated medicines impacted by anti-PEG antibody

# data[].attributes.funder_divisions[]
National Institute of Allergy and Infectious Diseases (NIAID)

# data[].attributes.abstract
Project Summary:  Polyethylene glycol (PEG) is routinely used in protein and nanoparticle therapeutics, with dozens of PEGylated drugs approved to date. Although PEG itself is exceptionally safe, patients can form high titers of anti-PEG antibodies (APA) to some PEGylated drugs. This results not only in loss of efficacy from APA- induced rapid clearance of the drug, but also increases the risks of severe allergic responses, as exemplified by adverse clinical experiences with Krystexxa, Oncaspar and Palynziq that leave tens of thousands of Americans without viable treatments. Furthermore, APA induced by one drug can impact the efficacy and safety of a second PEGylated drug. Given the increasing number of PEGylated drugs on the market (including COVID-19 mRNA vaccines), there is an urgent need for safe and effective interventions that prevent APA induction and PEG-allergy.  Mucommune has in-licensed a technology that can safely and effectively overcome the impact of APA on PEGylated medicines, without the need for broad immunosuppression or new polymers to replace PEG. The technology is based on the use of high MW free PEG to competitively saturate circulating APA and B-cell receptors on the surface of APA+ B-cells, thereby limiting the “hapten” effect of PEG-drugs. In published and pilot studies, free PEG markedly suppresses APA-induction against PEG-liposomes and Krystexxa (PEG- uricase) in immunocompetent mice and swine, and effectively restored the prolonged circulation of both in animals with high APA titers. Importantly, repeated injection of free PEG does not simulate further APA induction, unlike PEG-proteins or PEG-liposomes. Perhaps most surprisingly, free PEG completely eliminated hypersensitive reactions to PEG-liposomes in swine (the gold standard model for PEG-induced pseudoallergy). Swine receiving PEG-liposomes alone experienced strong anaphylaxis requiring immediate epinephrine intervention and resuscitation. These findings strongly underscore the promise of using free PEG to overcome allergic response to PEGylated medicines and to restore their efficacious use.  Free PEG is inexpensive (pennies per dose), offers outstanding safety, and can be rapidly advanced into late stage clinical studies. Our overarching goal in this Phase 1 SBIR proposal is to establish the foundation to quickly advance this intervention into the clinic. We will file a pre-IND (Type B) application with the FDA to confirm the suitability of our proposed preclinical and clinical pathway, and will develop and qualify key assays for quantifying APA and free PEG necessary to support GLP and future clinical studies. We will then execute a GLP tox study in rats (a common model for PEG-drugs) to support first-in-human studies. Successful completion of these activities will allow us to file IND for MM010, putting us at the doorstep of advancing this intervention into the clinic, potentially providing relief for the tens of thousands of Americans suffering from responses to PEG-drugs that limit their use of essential treatments.

# data[].attributes.keywords[]
Small Business Innovation Research Grant

# data[].attributes.title
Population genetics of rapid evolutionary processes

# data[].attributes.funder_divisions[]
National Institute of General Medical Sciences (NIGMS)

# data[].attributes.abstract
Project Summary. Rapid evolution lies at the core of some of the greatest challenges humanity faces today, ranging from the evolution of drug and antibiotic resistance to the rapid emergence of new Covid variants. Researchers are now envisioning even faster evolutionary dynamics brought about by CRISPR gene drives. This fascinating new technology could be used to directly suppress wild populations, or to rapidly spread an engineered allele through a population, for example a gene that reduces pathogen transmission in mosquitoes. Unfortunately, current population genetic models are not well-suited to describing such rapid processes, because they are often still grounded in simplistic assumptions such as a homogeneous, randomly mating population. Research in my lab centers on the development of new population genetic models and computational tools for studying rapid evolutionary processes such as CRISPR gene drives that allow us to better predict their expected outcomes. Over the past five years, my lab has developed a comprehensive modeling framework for gene drive dynamics. Here, we propose to incorporate increasing levels of biological realism into this framework to address three broad questions: (1) How can we systematically identify the features and parameters that are most critical for determining the outcome of a drive release in our simulations? (2) Is it possible to reliably confine a gene drive to an intended target population, and how could this be achieved? (3) Could a suppression drive in a mosquito population eradicate diseases such as malaria or dengue even when it does not achieve complete suppression of the mosquito vector? As gene drive technology comes ever closer to field experimentation, answers to these questions will be essential for a realistic evaluation of the expected outcomes of a drive release into a wild population. Motivated by insights from our modeling work on gene drives, we propose a second line of research focusing on the question of how continuous space can affect the dynamics of other rapid evolutionary processes, such as strong selective sweeps, which conceptually resemble the spread of a gene drive in many ways. We hypothesize that similar to what we found for gene drives, continuous spatial structure could also have a profound impact on the population dynamics of strong selective sweeps, and thus the signatures they leave in population genomic data. We plan to study this question using forward genetic simulations together with recently developed methods for inferring sweep parameters based on supervised machine learning. Finally, we plan to implement critical improvements in our SLiM evolutionary simulation framework, enabling forward simulation of populations of billions of individuals, so that we can predict the outcomes of the release of a CRISPR gene drive into a mosquito population with sufficient accuracy and robustness to facilitate a well-informed discussion about the feasibility, reliability, and risks of such approaches.

# data[].attributes.title
Investigating Novel Interventions for Low Back Pain in US Military Veterans: A Randomized Controlled Adaptive Phase II Trial

# data[].attributes.abstract
Background: There is currently a severe dearth of safe, non-habit forming pharmacological interventions for chronic pain disorders, and the clinical need to develop efficacious new therapeutics has never been more urgent. Fueled by the worsening opioid crisis and further exacerbated by the COVID-19 pandemic, opioid and other drug overdose deaths have climbed to staggeringly high levels. The rapid development of pharmacological agents for the management of chronic pain conditions that are safe, well-tolerated, efficacious and non-addicting is thus of paramount importance. Neurosteroids are naturally occurring molecules that are enriched in human brain and potentially ideal candidates for the safe and effective treatment of pain. The proposed project is a randomized, double-blind, placebo-controlled adaptive design study to determine the safety and efficacy of two promising neurosteroid molecules for the treatment of chronic low back pain in Veterans. The project logically builds upon the findings from our prior randomized clinical trial (RCT) demonstrating that the highest dose of pregnenolone (500mg/day) significantly improves chronic low back pain (Naylor et al., 2020), while also suggesting that higher doses of this molecule a may be even more efficacious. A second neurosteroid molecule, dehydroepiandrosterone (DHEA) has also been implicated in the pathophysiology of pain. DHEA levels are inversely associated with pain and our preliminary data demonstrate that 8-weeks of DHEA treatment is well-tolerated and reduces pain symptoms. Our strong biomarker and clinical data suggest that both pregnenolone and DHEA appear to have great therapeutic potential for the treatment of chronic pain conditions. We will thus investigate if these molecules exhibit possible efficacy in low back pain and determine maximally well-tolerated doses that are safe and optimally efficacious in the proposed three-arm trial (pregnenolone, DHEA, placebo). Methods: The proposed project is a Phase II randomized clinical trial utilizing an adaptive design to determine the safety and efficacy of pregnenolone and DHEA for the treatment of chronic low back pain in Veterans. Participants will be randomized in a 1:1:1 ratio to 4 weeks of treatment with pregnenolone, DHEA or matching placebo (N=108, approximately 36 per group). Pregnenolone dosing will begin at 500mg/day and escalate every week by 500mg as tolerated (to a potential maximum dose 2000mg/day). DHEA dosing will begin at 100mg/day and increase weekly by 100mg/day (to a potential maximum dose 400mg/day). The primary endpoint will be post-treatment change scores in mean daily pain intensity ratings (numerical rating scale, 0- 10). Secondary endpoint will be changes in pain interference measures (Brief Pain Inventory). Safety will be thoroughly monitored throughout study participation (SAEs, AEs, clinical laboratory parameters, vital signs, ECG). Neurosteroid quantifications will be conducted by highly sensitive state-of-the-art and specific mass spectrometry to investigate baseline and post-treatment neurosteroid levels as biomarker predictors of therapeutic response, and to determine optimal therapeutic ranges for these neurosteroid interventions. Conclusion: Chronic pain symptoms profoundly influence quality of life and function in a very large number of Veterans, and efficacious new treatments that are safe, well-tolerated, and non-habit forming are urgently needed. Compelling preclinical and clinical data support the possibility that neurosteroids such as pregnenolone and DHEA may be extremely promising treatments for pain conditions. The proposed RCT would thus provide pivotal evidence to optimize neurosteroid dosing in pain disorders and could rapidly translated into Phase 3 clinical trials. Findings from the proposed clinical trial efforts could thus lead to a potential therapeutic breakthrough for chronic pain conditions.

# data[].attributes.funder_divisions[]
Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)

# data[].attributes.abstract
The Centers for Disease Control recommends breastfeeding for the first six months of an infant’s life due to significant long term health benefits for the infant and breastfeeding parent. Beyond meeting the nutritional needs of the infant, human milk is a dynamic fluid with composition that changes to meet the needs of the infant as it develops and bioactive components which provide protective immunity to the infant. However, much is still unknown about the cells in the mammary gland which produce these prized components of human milk. Currently, there are no FDA approved interventions known to boost milk production, so the 60-70% of parents who struggle to lactate are left with little support to improve lactation outcomes and set infants up for the long- term health benefits of breastfeeding. Recent studies using single cell RNA-sequencing (scRNA-seq) of the mammary gland cells exfoliated into human milk have begun to characterize the cells that produce this dynamic substance with the ultimate goal of improving understanding of the factors impacting milk production at a cellular level. Still, the transcriptional pathways involved in milk production as well as the way these pathways change as a result of maternal and infant factors remains poorly understood. This proposal will utilize existing data generated from human milk to improve the understanding of transcriptional basis of milk production by (1) using integrative analysis of existing scRNA-seq data to identify shared transcriptional pathways of lactation, (2) developing statistical models to expose genes and pathways that change in milk in concordance with maternal and infant characteristics, COVID-19 infection and vaccination, antibody concentrations, and human milk oligosaccharide concentration, and (3) apply these and other models to understand the changes in the mammary gland and milk composition as a result of COVID-19 infection and vaccination. This improved characterization of milk production will lead to future studies on interventions to improve lactation outcomes and immune protection from human milk. Research will take place at the Gladstone Institute of Data Science and Biotechnology, a highly collaborative research institution with a commitment to postdoctoral training. The trainee with receive training in statistical analysis and method development, lactation biology, immunology, and responsible conduct of research from an interdisciplinary and multi-institutional team of mentors and collaborators. The training plan will prepare the trainee for an independent career as a computational biologist studying lactation and maternal and infant health.

# data[].attributes.keywords[]
Centers for Disease Control and Prevention (U.S.)

# data[].attributes.title
Control of cancer cachexia via stimulation of resolution of inflammation

# data[].attributes.abstract
While cancer cachexia is a devastating syndrome characterized by progressive muscle wasting, inflammation, and metabolic disruption, the underlying mechanisms remain poorly characterized. There are currently no treatments for cachexia. Cancer cachexia is driven by systemic inflammation, pro-inflammatory cytokines, and apoptosis (“cellular debris”). A paradigm shift is emerging in understanding the resolution of inflammation as an active biochemical process with our discovery of novel specialized pro-resolving mediators (SPMs), such as resolvins and endogenous resolution programs. SPMs stimulate macrophage-mediated clearance of debris, promote tissue/muscle regeneration, and counter-regulate pro-inflammatory cytokines at nanogram doses without immunosuppression. Despite approaches to block systemic inflammation, there are no current “pro- resolving” therapies in cancer or cancer cachexia. Moreover, the impact of cancer cachexia on eicosanoids and the novel pro-resolving lipid mediators, both key endogenous regulators of initiation and resolution of inflammation, are unknown. This proposal builds on our recent finding that stimulating resolution of inflamma- tion prevents tumor growth by counter-regulating pro-inflammatory cytokines/eicosanoids and clearing debris. Therefore, the overarching theme is to elucidate the underlying processes of failed resolution of inflamma- tion that drive cancer cachexia. We will rely on a set of established experimental systems, including genetic and pharmacological manipulation of SPMs and their receptors in animal models and macrophages. We shall test this in a multi-pronged approach. In Specific Aim 1, the mechanisms of dysregulated resolution of in- flammation in cachexia will be investigated. We will profile lipid autacoid mediators, including eicosanoids and SPMs, to test our innovative hypothesis that failed resolution of inflammation is necessary and sufficient to cause cachexia, which induces a rapid eicosanoid storm with dysregulated SPMs that leads to an un- controlled cytokine storm. We will evaluate pro-resolving lipid mediators as interventional targets in ca- chexia. In Specific Aim 2, we will optimize the delivery of SPM mimetics and humanized nano-pro- resolving medicines (NPRMs) carrying SPM cargo to cachectic tissues and determine whether SPMs can prevent chemotherapy-induced cachexia. These studies will complement Specific Aim 3, which seeks to pre- vent cancer cachexia via stimulation of resolution by precision nutrition. Parabiosis studies will determine whether cancer-induced cachexia is caused by an effect on the primary tumor or the metastatic site as most patients with cachexia die from metastases. These studies can offer a new animal system to evaluate cachexia at an early stage. We will connect our preclinical findings to clinical disease phenotypes using a computational framework to understand failed inflammation resolution in cachexia. Since SPMs have proven safe and effec- tive in human inflammatory disorders, these studies shall provide the basis for rapid translation of resolution- directed treatments in humans as a new direction to potentially prevent and/or reverse cancer cachexia.

# data[].attributes.title
Prepare Bioanalytical Aptamer Tools and Train Next-generation Scientists for SARS-CoV-3

# data[].attributes.funder_divisions[]
National Institute of Allergy and Infectious Diseases (NIAID)

# data[].attributes.abstract
In the past two decades, the world has witnessed the outbreaks of three Beta-coronaviruses: SARS-CoV-1 in 2002, MERS-CoV in 2012, and SARS-CoV-2 in 2019. As the potential for future outbreaks, including the possibility of SARS-CoV-3, remains high and unabated, the development of universal bioanalytical sensors in advance assumes paramount importance. Notably, while the spike proteins of different Beta-coronaviruses exhibit distinct characteristics, they also contain highly conserved domains. For instance, the S2 domains of SARS-CoV-1 and CoV-2 display significant conservation (approximately 93.1% conserved residues). Considering this scientific foundation, the anticipated emergence of the future Beta-coronavirus, SARS-CoV-3, from the same lineage B of SARS-CoV-1 and CoV-2, suggests the presence of the same highly conserved S2 domain. Consequently, it is imperative for scientists to develop probes targeting the S2 domain that can serve as universal tools for various Beta-coronaviruses. Recent studies have reported the efficient neutralization of diverse SARS-CoV-2 variants using anti-S2 antibodies, and we have successfully developed the first anti-S2 aptamer, which is a single-stranded deoxynucleic acid (DNA) molecule capable of specifically recognizing the S2 domain.  Preliminary data support the following observations: 1) Our aptamers, S2A2C1 and A1C1, recognize conserved spike domains of various SARS-CoV-2 variants; 2) They also recognize the spike proteins of SARS- CoV-1; 3) Dimeric fusion aptamers demonstrate enhanced binding avidities compared to monovalent aptamers. Hence, we are confident in the feasibility of developing cost-effective DNA aptamers with the ability to universally recognize different spike proteins of diverse Beta-coronaviruses. Two Specific Aims include: 1) To determine the potential of our aptamers against various spike proteins and prepare aptamer based bioanalytical sensors; 2) To construct homo- and hetero-dimeric aptamer based biosensors. It is important to note that Aim 2 of our research is independent of Aim 1, with the exception of protein production considerations. Building upon the outcomes of the Specific Aims, we will assess these aptamer-based bioanalytical sensors against various Beta-coronavirus pseudoviruses following the construction of these tools.  The proposed studies hold substantial potential for determining the efficacy of universal anti-Beta-coronavirus aptamers and lay the foundation for designing universal bioanalytical tools against diverse Beta-coronaviruses. Furthermore, our research on discovering universal aptamer tools targeting the highly conserved S2 domain can expand the scope of aptamer-based research, facilitate the development of bioanalytical sensors for molecular diagnostics of SARS-CoV-3, and provide valuable insights for the design of future anti-SARS-CoV-3 antibodies and vaccines that target conserved S2 domains.

# data[].attributes.keywords[]
Middle East Respiratory Syndrome Coronavirus

# data[].attributes.title
Arterivirus receptors: rules of engagement for cross-species infection

# data[].attributes.funder_divisions[]
National Institute of Allergy and Infectious Diseases (NIAID)

# data[].attributes.abstract
As COVID-19 has illustrated, the emergence of novel RNA viruses from wild animals poses a significant threat to human health. In this proposal, we will begin to assess the zoonotic potential of an entire family of viruses: the arteriviruses. The arteriviruses are the only mammalian RNA virus family not known to infect humans; as such they have been largely ignored by the biomedical research community. However, these viruses cause severe disease in many other mammals including monkeys. Due to historical neglect, the research community has not developed the resources and knowledge that would be required to rapidly develop medical countermeasures in the event of an arterivirus emergence in humans. Thus, these viruses are uniquely positioned in our pandemic preparedness blindspot. In this project we will characterize the zoonotic risk posed by arteriviruses using a diverse collection of arteriviruses and variety of host tools. In Aim 1, we will build upon our recent discoveries that identified CD163 as a host molecule required for arterivirus entry into cells. We will create a panel of cells expressing CD163 orthologs from various species (human, monkey, mouse, pig) and examine the susceptibility of these cells to a panel of arteriviruses. Next, we will create CD163 molecules with mutations and deletions to map the key domains and residues required for arterivirus binding. Finally, we will use our knowledge of CD163 to try and grow novel arterivirus isolates that so far cannot be grown in culture. In Aim 2, we will build upon our recent discovery that the neonatal Fc receptor (FcRn) is required for arterivirus infection of cells. We hypothesize that FcRn acts as an attachment factor, allowing the virus to adhere to the cell surface and become internalized in the endosomal compartment where it contacts CD163. To test this, we will perform a series of binding and internalization assays (in the presence and absence of CD163) to establish a role of FcRn as a pan-arterivirus attachment factor. We will also overexpress CD163 and FcRn in the background of FcRn- and CD163-knockout cells to determine if these molecules are each required in sequential fashion or are redundant for arterivirus infection. Finally, we will perform a pair-wise species comparison of FcRn orthologs and divergent arteriviruses to examine whether FcRn acts as a barrier to cross-species infection. Upon conclusion of this project we will have a greater appreciation for the zoonotic risk posed by these viruses. We will also have developed tools, biological systems, and knowledge that will serve as a critical resource for the rapid development of life-saving medical countermeasures in the event of an arterivirus outbreak in humans.

# data[].attributes.keywords[]
Clustered Regularly Interspaced Short Palindromic Repeats

# data[].attributes.title
Mentoring and Patient-Oriented Research in Clinical Informatics and Data Science

# data[].attributes.funder_divisions[]
National Heart Lung and Blood Institute (NHLBI)

# data[].attributes.abstract
This K24 mid-career investigator award in patient-oriented research is to support the mentoring, research, and career development activities of Dr. Tell Bennett. Dr. Bennett is an Associate Professor in the University of Colorado School of Medicine and a practicing pediatric ICU physician and informaticist/data scientist with research concentrations in predictive analytics, electronic health record (EHR) data, and clinical decision support (CDS) tool implementation. He is the Informatics Director for the Colorado Clinical and Translational Sciences Institute (CCTSI) and Vice Chair of Clinical Informatics in the Department of Biomedical Informatics. His combined leadership roles have enabled him to build a rich mentoring environment for patient-oriented informatics research. This K24 application proposes to sustain and grow that mentorship program. He currently mentors clinician-scientists in a variety of clinical fields including intensive care, pharmacy, surgery, endocrinology, malignant hematology, and clinical psychology. The K24 Mentoring Plan aligns with Dr. Bennett’s mission to grow patient-oriented research using informatics and data science methods and tools. The mentoring plan leverages educational, career development, and research support programs available through the CCTSI and the new Department. The K24 Research Plan is to develop and implement machine learning and computational physiology models deployable as EHR-based CDS tools. Dr. Bennett currently leads and mentors projects developing CDS tools in both outpatient and inpatient care settings and in a variety of clinical domains include heart failure, traumatic brain injury, serious bacterial infection and sepsis, COVID- 19, thyroid cancer, and postpartum depression. In this K24, developing CDS tools to improve decision-making and outcomes in children with acute respiratory failure (ARF) is a natural next step in this work. ARF is a common, important, and NIH-relevant condition that causes significant pediatric morbidity and mortality. The aims of the project are to 1) develop and validate a dynamic machine learning-based real-time prediction model for intubation in children with ARF and 2) phenotype current lung injury state in mechanically ventilated children using computational physiology models. These models can be deployed as CDS tools and tested as interventions in future clinical trials to improve patient outcomes. The K24 Career Development Plan includes formal mentorship training and coursework in signal processing and dynamical systems models. This group of skills will make Dr. Bennett a more successful mentor.

# data[].attributes.keywords[]
Mid-Career Clinical Scientist Award (K24)

# data[].attributes.keywords[]
Midcareer Investigator Award in Patient-Oriented Research

# data[].attributes.keywords[]
National Heart  Lung  and Blood Institute

# data[].attributes.keywords[]
United States National Institutes of Health

# data[].attributes.title
Ion channels regulating plasma cell differentiation and humoral immunity

# data[].attributes.funder_divisions[]
National Institute of Allergy and Infectious Diseases (NIAID)

# data[].attributes.abstract
B cells are critical for immune responses to infection and in many forms of autoimmune disease. They develop in the bone marrow and migrate to lymph nodes and spleen, where they further mature. At the end of this process, B cells express a high affinity B cell receptor with which they recognize antigen and which allows them to develop further into either memory B cells or long-lived plasma cells. Both types of cells migrate to the bone marrow and provide long-term protection from reinfection with the same pathogen. Plasma cells are a B cell type that produces large quantities of antibodies that are critical for neutralizing pathogens such as influenza virus, or more recently, SARS-CoV2. Several forms of primary immunodeficiency are caused by defects in B cell development or maturation including agammaglobulinemia and common variable immunodeficiency (CVID), which are characterized by a complete or partial lack of antibody production. Underlying these forms of immunodeficiency are mutations in a plethora of genes that encode transcription factors, cell surface receptors and signal transduction molecules. Some of these mutations occur in genes encoding ion channels. Ion channels are located in the cell membrane or membranes of intracellular organelles. They function as gateways to mediate the transport of charged ions such as calcium, zinc or chloride. Inherited mutations in two ion channels were shown to prevent the development of B cells resulting in agammaglobulinemia. Studies in mice have identified additional ion channels that are required for B cell function. Overall however, the role of ion channels in B cells is poorly understood with only a handful of the more than 600 known ion channel genes implicated in B cell function to date. This is even more extreme for plasma cells because no ion channel has yet been reported that specifically regulates plasma cell development or function. This lack of information is in strong contrast to the well established role of ion channels in cells of the brain, nerves, heart, muscle or kidney. It also represents a missed opportunity from a basic science perspective and our ability to understand how immune responses to infection are regulated, and from a therapeutic perspective because ion channels are excellent drug targets. Drugs modulating ion channel function are a mainstay in the treatment of cardiovascular diseases, neurological and psychiatric disorders and type 2 diabetes. We have therefore conducted genetic screens to identify novel ion channels that regulate the development of B cells into plasma cells and identified around 10 such channels. We investigated several of these further and confirmed that inhibiting their expression in B cells interferes with plasma cell development. In this proposal, we will focus on two of these channels and determine the molecular and cellular mechanisms by which they control the development of B cells into plasma cells and their ability to mount an antibody response to infection with viral pathogens such as influenza.

# data[].attributes.keywords[]
Clustered Regularly Interspaced Short Palindromic Repeats

# data[].attributes.keywords[]
Structure of germinal center of lymph node

# data[].attributes.title
Modeling the dynamics and composition of T-cell receptor repertoires in post-acute sequelae of COVID-19 (PASC)

# data[].attributes.funder_divisions[]
National Institute of Allergy and Infectious Diseases (NIAID)

# data[].attributes.abstract
Post-acute sequelae of COVID-19 (PASC), colloquially known as long covid, has been reported in 31%-69% of COVID-19 patients. The prevalence of PASC among patients, even those with mild infection, and those with prior vaccination, underscores the importance of principled approaches for uncovering and addressing the cause of these issues. We propose to conduct a detailed analysis of the immune repertoire dynamics of PASC patients and compare them to both COVID-19 patients without PASC, and healthy individuals. These will be secondary analyses, conducted on existing data from a previous study with the Institute of Systems Biology and Swedish Health Services, which includes longitudinal deep immunophenotyping with single cell and plasma multiomics, repertoire sequencing, electronic health records, viremia measurements, and antibody titers for 209 COVID-19 patients. In Aim 1, we will conduct inference, analysis, and comparison of T-cell receptor repertoire dynamics in PASC. Using interpretable statistical, biophysical, and machine learning approaches, we will conduct a detailed analysis of T-cell repertoires aimed at finding PASC specific clonotypes and their corresponding receptor features. This involves building cohort specific models of thymic selection, examining how these models differ between cohorts and over time, inferring the dynamics of repertoire size, sharing and diversity, and uncovering the receptor features which drive these differences. In Aim 2, we will develop new methods for the integration of T-cell repertoire and single cell dynamics. The existing breadth of multiomics data allows us to explore new methodologies for integrating different modalities of longitudinal data. For T-cell repertoires in particular, we plan to extend existing models of thymic selection to include gene expression of relevant T-cell specific genes and to study how the expansion and contraction of clonotypes affects the dynamics of T-cells in gene expression space. By using interpretable biophysical and machine learning methods, we can construct generative models of TCRs including gene expression values and study how these distributions change in time. Results have strong potential to accelerate our understanding of the etiology of immune-based PASC responses, which is essential for prioritizing potential therapeutic targets for prevention and treatment. Further, results will advance methods for future research across a wide range of infectious diseases and immune-mediated medical conditions.

# data[].attributes.keywords[]
Post-Acute Sequelae of SARS-CoV-2 Infection