Uncovering the Molecular Drivers of Gastroesophageal Reflux Disease (GERD), Bringing Relief to Millions

THIS STUDY UTILIZES THE DHF BIOREPOSITORY Principal Investigator: Marie-Pier Tétreault, PhD, Assistant Professor of Medicine (Gastroenterology and Hepatology), Northwestern Medicine, Northwestern Feinberg School of Medicine Gastroesophageal reflux disease (GERD) affects up to 27% of the adult U.S. population, resulting in more than seven million patient visits annually. Over time, GERD leads to serious complications such as erosive esophagitis, Barrett’s esophagus and esophageal cancers. However, how GERD functions at the molecular level is unclear, making it difficult to develop better treatments for patients living with this condition. This year, DHF is supporting Dr. Marie-Pier Tétreault’s work in identifying the molecular mechanisms that drive the development and progression of GERD, in the hopes of changing the future for patients living with this destructive esophageal condition. DHF funding will enable researchers to utilize state-of-the-art, single-cell RNA technology to rapidly look at the precise gene expression patterns of tens of thousands of cells in hopes of uncovering and identifying rare populations of diseased cells. Previous successful DHF funding of the Tétreault team uncovered valuable new insights and created new technology in profiling the unique cells involved in eosinophilic esophagitis (EoE) and scleroderma esophageal disease. This year, the research team is focusing on the widespread disease of GERD with a focus on new, critical treatment options for patients to decrease the risks of major esophageal complications, including...

Exposing and Confronting Destructive Chronic Inflammation in Acid Reflux (GERD)

Principal Investigator: Marie-Pier Tétreault, PhD, Research Assistant Professor of Medicine (Gastroenterology and Hepatology), Northwestern University Feinberg School of Medicine Gastroesophageal reflux disease (GERD/acid reflux) affects over ¼ (up to 27 percent) of U.S. adults, resulting in more than 7 million patient visits annually. GERD leads to complications such as erosive esophagitis, Barrett’s esophagus and esophageal cancer. Learning more about the molecular basis for the development and progression of GERD is critical to improving treatment options and decreasing the risks for these esophageal conditions. Dr. Tetreault is looking at the role of the crucial mediator of inflammation IKKβ in the development of chronic GERD. The team will use molecular approaches to shut down the expression of IKKβ and evaluate the impact of this loss on the development of GERD. This project will also employ a new technology called single-cell RNA sequencing (scRNA-seq) that enables the rapid determination of the precise gene expression patterns of tens of thousands of individual cells. Employing scRNA-seq should help give greater insight into how IKKβ signaling impacts the regulation of the inflammatory process in chronic gastroesophageal reflux. Interrupting the disease process of GERD can crucially impact long term patient prognosis and risk of...

Discovery of Role of Certain Immune Cells in Increasingly Diagnosed Esophagus Disease (EoE) in Children

Principal Investigator: Joshua Wechsler, MD, MS, Attending Physician, Gastroenterology, Hepatology and Nutrition; CURED (Campaign Urging Research for Eosinophilic Disease) Foundation Research Scholar, Assistant Professor of Pediatrics (Gastroenterology, Hepatology, and Nutrition) and Medicine (Allergy and Immunology), Northwestern University Feinberg School of Medicine Eosinophilic Esophagitis (EoE) is a chronic immune disorder of the esophagus caused by certain foods triggering an allergic response, or by chronic GERD (Gastroesophageal reflux disease/acid reflux). Over time, chronic inflammation from EoE can lead to fibrosis (scarring) and subsequent esophageal stiffness and narrowing of the esophagus. Patients experience difficulty passing food and impaction when food becomes trapped in the esophagus. Identifying early signs and drivers of scarring would help prevent the development of these and other serious complications. Endoscopic Functional Luminal Impedance Probe (EndoFLIP) is used to measure esophageal distensibility (stiffness or stretchiness). Prior research has demonstrated that eosinophils—a type of immune cell—have a weak association with esophageal distensibility. While different types of immune cells play a role in EoE, the association of non-eosinophil immune cells has never been studied. Dr. Wechsler is examining the correlation between esophageal distensibility and non-eosinophil immune cell populations in children with EoE. The team expects this work will guide future studies on EndoFLIP, as well as how immune cells, such as mast cells and T-cells, impact esophageal fibrosis to help develop targeted treatments for EoE that can inhibit disease progression and its destructive effects on pediatric...

Cutting Edge Technology (HRIM) Reveals Next Generation Testing in Esophageal Diseases

Principal Investigator: Wenjun Kou, PhD, Research Assistant Professor of Medicine (Gastroenterology and Hepatology), Northwestern Feinberg School of Medicine Many serious esophageal motility disorders and diseases are diagnosed with the newer technology of High-Resolution Impedance Manometry (HRIM). HRIM measures pressures and fluid movement in the esophagus and lower esophageal sphincter connecting to the stomach. Dr. Kou’s team is transforming an HRIM-based analysis technique into new tools with metrics/outcomes for use by physicians in clinical practice. Taking HRIM analytics a step further offers more specific evaluation of esophageal function. The esophageal metrics being studied include bolus retention; intrabolus pressure (IBP) and distensibility of the esophageal body at each phase; pressure and distensibility of esophagogastric junction (EGJ) as well as emptying flow rate. Dr. Kou’s research study involves: 1) designing and implementing metrics-based algorithms to analyze esophageal function; and 2) deriving a metrics dataset from HRIM studies of various tissue/cellular phenotypes. The research team will then use complex statistical analysis and the new field of ‘machine learning’ to evaluate the discriminating power (usefulness) of the metrics, and derive classification models of esophageal function for use in diagnosing esophageal diseases. Dr. Kou will conduct a further comparison of those results with similar outcomes from panometry—another recently developed technology used in esophageal evaluations. Using these high-level tools to develop precise metrics and advanced classifications in esophageal diseases ultimately improves physicians’ ability to diagnose and treat esophageal diseases as accurately and quickly as possible, minimizing the long-term effects of these potentially debilitating and life-threatening...

Division of Gastroenterology and Hepatology Northwestern Medicine/Feinberg School of Medicine
Center for Artificial Intelligence and Mathematics in Gastroenterology

Division of Gastroenterology and Hepatology Northwestern Medicine/Feinberg School of Medicine Center for Artificial Intelligence and Mathematics in Gastroenterology The Center for Artificial Intelligence and Mathematics in Gastroenterology (AIM-GI) is a first of its kind program developed in a division of Gastroenterology.  Artificial Intelligence and Machine Learning have the potential to vastly improve our ability to accurately predict, diagnose and treat our patients living with digestive diseases.  Through collaboration with engineers at the McCormick School of Engineering and physician scientists at the Feinberg School of Medicine at Northwestern University, our team has been incorporating mathematical modeling and advanced programming to study the mechanisms that lead to poor gastrointestinal function.  This work led to the development of a more formalized center that focuses on three main initiatives. Development of virtual organs which can be used to study the effects of surgery and medications; Development of new hybrid diagnostic tools using AI and machine learning to enhance diagnosis; Using machine learning and neutral networks to predict disease outcome. Although this is a new program, we have already had success developing an NIH funded Center of Research Expertise (CORE) and we have also developed new AI prototypes that can improve diagnostic accuracy and reliability of motility tests.  This work is supported by the generosity of the Digestive Health Foundation and these funds help provide the computational power and expertise required to continue to develop these innovative tools.  Our goal is to continue invent and develop new approaches and our partnership with the Digestive Disease Foundation will continue to allow us to grow and evolve this...