SPUR 2019 Projects: Medicine

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SPUR projects are listed in alphabetical order by faculty mentor last name.

Biomedical Informatics | School of Medicine


A TEMPORAL ANALYTICS FRAMEWORK FOR PREDICTING EARLY THE CO-OCCURRENCE OF SHOCKS IN THE INTENSIVE CARE UNIT

Samir Abdelrahman, Assistant Professor

Several types of patients are hospitalized in intensive care units (ICU), such as patients with acute myocardial infarction, bleeding, and sepsis-yielding shock, a life-threatening condition, and, in many cases, the co-occurrence of shocks or death. One-third of ICU patients suffer from some types of shocks. Of them, cardiogenic shock comprises approximately 20%, hypovolemic about 20%, and septic shock about 60% of cases. Shock types may have temporal co-occurrences that lead to further complications including mortality. Therefore, clinicians may depend on their intuition when analyzing time-sensitive information to make several clinical decisions for predicting early the likelihood of more than one type of shock at occurring at the same time (i.e., multi-shock). Most previous modeling studies have focused on predicting a single shock rather than multi-shocks. Moreover, most of them use machine learning techniques in their clinics that may not accurately predict such temporal co-occurrences among different types of shocks. The Abdelrahman lab has developed many temporal solutions that have been used effectively in critical care settings. Our primary goal is to develop a novel temporal solution that leverages our prior preliminary results, MIMIC dataset, and advanced machine learning techniques to better predict patient outcome in the shock domain. The proposed solution impact is to support the clinicians with early and accurate predictions of multi-shocks. This project entails collaborations between informatics researchers and clinical experts to identify challenges and propose relevant solutions and will require the student selected for the project and lab students to exchange ideas and solve problems together.

This SPUR project is funded by a supplement to the National Library of Medicine Training grant T15LM007124-22; Wendy Chapman (PI), Julio Facelli (co-I).

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Internal Medicine | School of Medicine


STIMULATORY NEURAL CIRCUITS INVOLVED IN REGULATION OF THE HORMONE RESPONSE TO HYPOGLYCEMIA
Owen Chan, Associate Professor

Iatrogenic hypoglycemia (low blood sugar) is the most serious acute complication in insulin-treated diabetes and it remains the limiting factor in maintaining proper glycemic control. The brain, and especially the ventromedial hypothalamus (VMH), plays a crucial role in sensing hypoglycemia and initiating the physiological "counterregulatory" hormone responses to correct it. However, both recurrent exposure to hypoglycemia and longstanding diabetes can impair the mechanisms that normally correct the fall in blood glucose levels. Our laboratory utilizes a combination of neuroscience (microdialysis, microinjection, optogenetics), metabolic (glucose clamps), genetic (targeted knockdown or overexpression) and molecular biology (qRT-PCR, westerns, immunohistochemistry) techniques to identify the neural mechanisms that are involved in the detection of hypoglycemia and how these central sensing mechanisms are impaired following recurring exposure to hypoglycemia and in diabetes.

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Radiology & Imaging Sciences | School of Medicine


IMPROVED METHODS FOR MEASURING CARDIAC PERFUSION AND FIBROSIS WITH MRI
Ed DiBella, Professor

The DiBella lab seeks to invent and refine new and better methods for the acquisition, reconstruction, and post-processing of MRI, with particular emphasis on cardiac and stroke applications. Our lab seeks to translate these improvements to clinical studies, and to use the methods to better understand physiology in health and disease.

One set of current projects involves development of improved methods for measuring myocardial perfusion and fibrosis with MRI. Methods for higher spatial resolution, greater coverage, and elucidating differences across the cardiac cycle are being developed. We have pulse programmed new simultaneous multi-slice (SMS) and 3D acquisitions on the MRI scanner. Advanced reconstruction methods including constrained reconstruction and deep learning methods are also being developed for cardiac applications.

The stipend for this SPUR project is funded by an American Heart Association grant awarded to Dr. Stavros Drakos, MD, PhD.

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Internal Medicine | School of Medicine


MECHANISM OF MYOCARDIAL SALVAGE WITH SIMULTANEOUS MECHANICAL UNLOADING AND REPERFUSION AFTER ACUTE MYOCARDIAL INFARCTION
Stavros Drakos, Associate Professor

Coronary artery disease and the associated ischemic heart disease is the leading cause of death and disability worldwide. Significant advances have been achieved with reperfusion after acute myocardial infarction (AMI). However, reperfusion injury accounts for up to 50% of the myocardial damage after AMI. Currently there are no effective interventions to limit reperfusion injury. Despite the increasing rates of primary percutaneous coronary intervention, chronic heart failure after AMI is still highly prevalent with its well-known tremendous burden on the health care system. Our studies will provide new insights into the molecular and metabolic mechanisms that are associated with enhanced myocardial salvage after AMI and thus help reduce subsequent development of chronic heart failure. The goal of this project is to investigate new strategies that could minimize the deleterious effect of reperfusion injury after AMI. We hypothesize that early LV mechanical unloading combined with coronary reperfusion will result in improved myocardial salvage following AMI. This is likely through a mechanism that attenuates ischemia/reperfusion (I/R) deleterious effects on mitochondrial proteome expression and possibly promotes normal substrate utilization by myocardial cells. We will investigate in our porcine I/R model the effect of combined mechanical unloading and reperfusion on mitochondrial proteome expression and cardiac cell metabolism. During ischemia there is a metabolic shift from β-oxidation of fatty acids to glycolysis as the primary mechanism of ATP synthesis in cardiac muscle. We propose to investigate how the cardiac specific MPC deletion in adult mice will affect the myocardial salvage in a mouse model of I/R.

The stipend for this SPUR project is funded by an American Heart Association grant awarded to Dr. Stavros Drakos, MD, PhD.

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Biomedical Informatics | School of Medicine


Developing Strategies and Tools to Mine Clinical Variant Assertions
Karen Eilbeck, Professor

As sequencing technologies have advanced; sequencing data has shown the extent of polymorphism in the human population. Understanding which of these DNA changes impact an individual’s clinical phenotype (cause disease), and which are silent is necessary for the interpretation of genetic tests. ClinVar is an international, submission-driven archive of variant-condition-interpretations hosted by the National Center for Biotechnology Information (NCBI). ClinVar is increasingly becoming the central repository of interpreted genomic variants; as of July 2018, 997 submitters had contributed 427,882 unique variants and 11099 conditions to ClinVar. Sharing variants and associated supporting evidence in the ClinVar database enables the transparent review of data by users and supports clinical variant interpretation. Submissions to ClinVar represent the first time that clinical labs and other submitters have shared and compared their variant interpretations, and this reveals both conformity and discrepancy in variant interpretation. In some cases the disagreement in interpretation is clinically significant – pathogenic versus benign. This growing and evolving database relies on submitters to resolve discrepancies and update findings when knowledge changes. It also provides the starting point for expert curation of variants and genes. My group developed ClinVar Miner; a tool that enables deep exploration of the ClinVar dataset. The goal of ClinVar Miner is to enable management of the upstream and downstream processes related to submitting to and using the data. ClinVar Miner as a counterpoint to facilitate use of ClinVar data.

This SPUR project is funded by a supplement to the National Library of Medicine Training grant T15LM007124-22; Wendy Chapman (PI), Julio Facelli (co-I).

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Biomedical Informatics | School of Medicine


Structural Bioinformatics Approaches to Gain Insight on Variant Pathogenicity
Julio Facelli, Professor

Computational modeling in biomedical sciences has become increasingly common, effective, and even necessary. The development of these techniques and the unparalleled increase of computational power has contributed to making biology a more computationally and data-centered discipline. They have also increased interest in using modelling and simulation in developing in silico methods like molecular dynamics simulations and protein structure prediction, which are essential to structural bioinformatics. Structural bioinformatics uses models to study the folding of proteins, their environments, and their interactions. This has been achieved through two major approaches: homology modelling and de novo structure prediction. Homology modeling, also known as template-based modeling, is based upon linking homologous sequences and their corresponding structure models/crystal structures for use as modeling templates. De novo structure prediction is based upon using force fields to compute the likely structures based upon energetic calculations and/or statistical probability of conformations. These developments are significant, because when compared to the number of proteins for which their amino acid sequences are known, there are comparatively very few experimentally determined protein structures. Thus, the vast majority of protein structures are unknown, which limits our mechanistic understanding of biological process. Furthermore, much less is known about the changes in protein structure upon mutations and how this relates to their pathogenicity and/or lack of thereof. We use a large collection of structural bioinformatics approaches to gain insight into the relationship between mutations and pathogenicity and its mechanisms.

This SPUR project is funded by a supplement to the National Library of Medicine Training grant T15LM007124-22; Wendy Chapman (PI), Julio Facelli (co-I).

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Biomedical Informatics | School of Medicine


Exploring Molecular Aspects of the Exposome
Ram Gouripeddi, Research Assistant Professor

About 50 – 70% of health and well-being is determined by the environment an individual lives in and their behaviors within these environments. The sum total of all the environmental exposures an individual encounters in their life-time is called the exposome. The exposome includes molecular constituents involved in direct biological pathway alterations as well as mutagenic and epigenetic mechanisms of environmental influences on the phenome. Exposures to different chemicals have been shown to play a role in different conditions including asthma, obesity, as well as other respiratory, cardiovascular, endocrine, and metabolic conditions and cancers. Understanding the effects of these chemical exposures requires representing these molecules in research studies that involve generating and utilizing exposomes. The Utah PRISMS (Pediatric Research using Integrated Sensor Monitoring Systems) Informatics Ecosystem (UPIE) is developing systematic informatics methods for generating and utilizing such exposomes for performing translational research.

This SPUR project is funded by a supplement to the National Library of Medicine Training grant T15LM007124-22; Wendy Chapman (PI), Julio Facelli (co-I).

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Orthopaedics | School of Medicine


Application of machine learning for oral health care
Man Hung, Associate Professor

Over the last decade, there has been an increase in the application of machine learning techniques towards medical research. One area that machine learning is well-suited to target is in directing services to areas of the greatest need. Resource mismanagement in primary oral health care places an undue burden on general health service delivery. For example, when emergency departments must address non-traumatic dental problems, patients are treated by providers without specialized dental training, and extensive post-discharge follow up by a dental practitioner is typically still required. The result is added health system burden without any improvements to the patient experience or outcomes.

A steady increase in the prevalence of dental caries and the varying implications of poor oral health21 have prompted the passage of public policy and oral health imperatives that aim to increase access to dental care for all people. To date, policy changes have addressed issues of access for people of different socioeconomic statuses, provided for the creation of school-based dental clinics, interventions at crucial early stages of development, and train dental care providers to service areas of increased need. What has not been addressed in improvements is a method to streamline identification of those at greatest need for dental care. Machine-learning applications that capitalize on information extracted from large stores of public health data are an opportunity to provide resources in a way that is targeted and personalized. This goal of this study is to use machine learning algorithms to create a useful, predictive model for dental care recommendations for individuals based on need.

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Surgery | School of Medicine


Patterned Silicone Surfaces for Limiting Infection in Breast Prostheses
Sujee Jeyapalina, Research Assistant Professor

Breast prosthesis placement secondary to mastectomy remains one of the most commonly performed procedures in reconstructive surgery. Post-operatively, one of the major complication is periprosthetic infection. It is estimated that approximately 15% of breast prostheses complications are due to infection, while an additional ~35% are attributed to aggressive capsular contracture (CC) formation. Interestingly, recent publications attribute these CC to biofilm formation and also associate the presence of acute infection as a potential etiology. Since micro-patterned surfaces, such as Sharklet™, have been shown to limit bacterial adhesion and biofilm formation while promoting adhesion of healthy cells, one option to reduce these high infection rates is to modify the breast prosthetic surfaces with micro-patterns. This concept is based on the “race-for-the-surface” principle—where anti-biofilm adhesive surfaces provide a protective environment for host eukaryotic cells to adhere and proliferate first. To date, no studies have been attempted to test these surfaces on breast prostheses. Thus, our group is investigating a range of surface patterns with micro-scaled repeating units on silicone surfaces to reduce or eliminate bacterial adhesion, thereby deterring biofilm formation while allowing directional adhesion of the fibroblasts and limiting cancer cell proliferation.

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Pediatrics | School of Medicine


Trafficking and utilization of long-chain fatty acid supplementation during development
Lisa Joss-Moore, Research Associate Professor

Neonatal supplementation of preterm infants with long chain fatty acids, particularly docosahexaenoic acid (DHA) is the subject of several ongoing clinical trials. The rationale for supplementation is that preterm infants have low DHA, and that low DHA predisposes to the development of bronchopulmonary dysplasia (BPD). However, initial results from the clinical trial suggests inconclusive results at best, and possibly even a detrimental effect of DHA on BPD. A significant knowledge gap in the field, however, is the trafficking and utilization of supplemental DHA during development. Our lab is studying the whole body trafficking and utilization of supplemental DHA in the developing rat, with an emphasis on lung and liver.

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Biomedical Informatics | School of Medicine


Re-Imagine EHR: Enhancing Patient Care and the Provider Experience through Standards-Based, Interoperable Extensions to the Electronic Health Record (EHR)
Ken Kawamoto, Associate Professor

The University of Utah’s ReImagine EHR initiative is a multi-stakeholder effort to re-imagine how patient care and the provider experience can be optimized in the EHR, including through the development, evaluation, and dissemination of innovative, interoperable extensions of native functionality provided in the electronic health record (EHR). Through ReImagine EHR, we are developing various provider-facing clinical applications and decision support capabilities that are seamlessly integrated with the rest of the EHR, patient-facing smartphone applications that are synched with the EHR, and various supportive tooling such as a multi-institutional, open-source clinical decision support platform known as OpenCDS. We are leveraging emerging health IT standards such as FHIR, SMART, and CDS Hooks with the goal of enabling these apps and services to be shared across healthcare organizations and EHR platforms. We are developing apps and services spanning the continuum of care, including prevention, chronic disease management, acute care, and transitions of care. Several of these initiatives are being pursued with the support of research grants, such as a project funded by the National Cancer Institute for identifying and managing individuals with elevated risks of breast and colorectal cancer using standards-based, interoperable, and ultimately widely scalable approaches.

This SPUR project is funded by a supplement to the National Library of Medicine Training grant T15LM007124-22; Wendy Chapman (PI), Julio Facelli (co-I).

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Internal Medicine | School of Medicine


Peripheral Limitations to Maximal Oxygen Uptake in Patients with Heart Failure and Preserved Ejection Fraction
Russell Richardson, Professor

Heart failure with preserved ejection fraction (HFpEF) accounts for greater than 50% of all heart failure cases, and the prevalence relative to heart failure with reduced ejection fraction (HFrEF) continues to rise at a rate of 1% per year, with a 5-year survival rate as low as 50%. The pathophysiological differences between HFpEF and HFrEF, coupled with unsuccessful therapeutic strategies, highlight the need for improved understanding of HFpEF. The pathophysiological differences between HFpEF and heart failure with reduced ejection fraction (HFrEF), coupled with unsuccessful therapeutic strategies, highlight the need for improved understanding of HFpEF.

The defining symptom of HFpEF is marked exercise intolerance that greatly limits physical activity and quality of life. In patients with HFpEF, maximal oxygen uptake (VO2max), a primary determinant of prognosis and quality of life, has best quantified the severity of exercise intolerance. The peripheral limitations to VO2max will be determined in patients with HFpEF and controls by measuring leg maximal O2 delivery, O2 consumption, and mitochondrial oxidative capacity (Aim 1). Next, the identification of an O2-supply or O2-demand limitation will be validated by measuring the hyperoxia-induced changes in leg maximal O2 delivery and O2 consumption in patients with HFpEF and controls (Aim 2). Finally, the effect of knee-extensor training on the peripheral limitations to VO2max will be assessed by measuring the training-induced changes in leg maximal O2 delivery, O2 consumption, and mitochondrial oxidative capacity in patients with HFpEF and controls (Aim 3).

The stipend for this SPUR project is funded by an American Heart Association grant awarded to Dr. Stavros Drakos, MD, PhD.

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Internal Medicine | School of Medicine


Thirst, excretion and the response to dehydration
Aylin Rodan, Assistant Professor

Multicellular organisms maintain homeostasis of the internal milieu for optimal cellular functioning. This includes homeostasis of electrolyte concentrations, osmolality and pH. During dehydration, a rise in osmolality sensed by osmosensing neurons in the brain triggers release of a hormone that stimulates water retention by the kidney, and also results in increased thirst and drinking behavior. Using the powerful genetic model organism, Drosophila melanogaster (fruit fly), we have developed assays to look at both drinking behavior and excretion during periods of dehydration. Published work, which we have recapitulated, has shown that manipulating genes in osmosensing neurons in the fly brain changes drinking behavior in dehydrated flies. Based on this, we are interested in whether manipulating other genes of interest will change drinking behavior and excretion by the fly.

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Biochemistry | School of Medicine


Immune cell function in disease
Minna Roh-Johnson, Assistant Professor

Macrophages are one of the body's first responders to infection. They eat debris, attack foreign substances, and help keep the body healthy. So then it is surprising that macrophages can play a sinister role in tumors. Instead of attacking cancer cells, macrophages promote metastasis of many cancers. What kind of communication occurs between macrophages and cancer cells for this to occur? To answer these questions, we use a combination of animal models and cell culture techniques to visualize and manipulate macrophage behaviour when in contact with cancer cells. We also visualize cancer cell behaviour during specific steps of metastasis in living animals. With these approaches, we have discovered unexpected modes of cell-cell communication between cancer cells and their environment, and are now determining the molecular mechanisms of this communication.

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Surgery | School of Medicine


Porous Fluorapatite Scaffolding with Adipose Derived Stem Cells for de novo Bone Formation
Jill Shea, Research Assistant Professor

Bone loss due to trauma or disease is an increasingly serious health problem within the military and civilian populations. Bone grafts are utilized in these situations to aid bone repair and regeneration. Material and performance are considered as two main problems in the development of customizable bone scaffolding. An ideal bone substitute material should have osteogenic properties and the capability to fill and integrate large bone defects with a variety of shapes and sizes. The goal of this project is to develop a scaffold that can be used to repair bone defects or injuries. The device will consist of a 3-D bone scaffold, adipose derived stem cells, and localized growth factor release. The overall aims are: 1) design device, 2) evaluate release of growth factor from device and stem cell differentiation in vitro, and 3) evaluate in vivo efficacy in a model system. This multi-pronged approach is hypothesized to increase bone growth following an injury and improve patient outcomes.

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Pediatrics | School of Medicine


Induced pluripotent stem cell derived cardiomyocyte models of human cardiovascular disorders
Martin Tristani-Firouzi, Professor

Advances in induced pluripotent stem cell (iPSC) technology allow for reprogramming of adult somatic cells into stem cells from which patient-specific (and thus disease-specific) cardiomyocytes (CM) can be derived. The impact of this technology has far-reaching implications, ranging from drug discovery, pre-clinical drug screening, mechanistic understanding of disease processes, and advances in personalized medicine. Specifically human iPSC-CMs offer a unique model system to study phenotypic variation in Long QT Syndrome (LQTS), by allowing for direct comparisons of gene expression in human cardiac cells derived from family members who share the same mutation, but manifest severe versus mild symptoms. However, the potential of iPSC technology to answer this and other crucial research questions is limited by several technological barriers. For example, human iPSC-CMs in culture behave more like embryonic than mature myocytes and thus may not recapitulate key features of childhood or adult-onset disease. The overall goal of this proposal is to overcome the maturational hurdles in order to design a valid iPSC-CM model system for the study human arrhythmia disorders. This proposal utilizes cutting-edge technological approaches that will advance the field of cardiovascular medicine in a very practical manner.

The stipend for this SPUR project is funded by an American Heart Association grant awarded to Dr. Stavros Drakos, MD, PhD.

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