NCATS is administering 18 new NIH Extracellular RNA (exRNA) Communication program projects as a next phase to test and validate exRNA molecules for their potential as disease biomarkers and treatments. Funded by the NIH Common Fund, these projects are aimed at developing clinically validated biomarkers.
- Circulating MicroRNAs as Disease Biomarkers in Multiple Sclerosis
- Clinical Utility of Extracellular RNA as Marker of Kidney Disease Progression
- Clinical Utility of MicroRNAs as Diagnostic Biomarkers of Alzheimer’s Disease
- Clinical Utility of Salivary ExRNA Biomarkers for Gastric Cancer Detection
- ExRNA Biomarkers for Human Glioma
- ExRNA Signatures Predict Outcomes After Brain Injury
- ExRNAs for Early Identification of Pregnancies at Risk for Placental Dysfunction
- Extracellular Non-Coding RNA Biomarkers of Hepatocellular Cancer
- Extracellular RNAs: Biomarkers for Cardiovascular Risk and Disease
- Plasma MiRNA Predictors of Adverse Mechanical and Electrical Remodeling After Myocardial Infarction
Investigators: Howard L. Weiner, M.D., and Roopali Gandhi, Ph.D., Brigham and Women’s Hospital, Boston
Grant Number: UH2-TR000890
Multiple sclerosis (MS) is a disease in which the body’s immune system attacks and destroys the protective covering of the nerves. Over time, the brain, the spinal cord and the rest of the body lose the ability to communicate with each other. Many people with MS eventually lose the ability to walk or speak clearly. MS affects 2.5 million people worldwide, including 400,000 in the United States. Currently, no cure exists, but some treatments can slow the disease. A better understanding of the biology and progression of MS could lead to better treatments or a cure. This study team previously measured a type of exRNA called microRNA (miRNA) in the blood of patients with MS and found that it was related to disease stage, response to therapy and level of disability. This project’s investigators will continue to study these biomarkers, or indicators of the presence, absence or stage of a disease, and assess their usefulness in diagnosing and monitoring MS progression and response to therapy. MiRNA biomarkers for MS may provide a new way for clinicians to better understand the nature of the disease in individual patients.
Investigators: Thomas Tuschl, Ph.D., The Rockefeller University, New York, and Manikkam Suthanthiran, M.D., Weill Cornell Medical College, New York
Grant Number: UH2-TR000933
Chronic kidney disease (CKD) is a condition in which the kidneys partly or completely lose their ability to function and can result from high blood pressure, diabetes, disorders of the immune system, genetic defects and developmental disorders. CKD causes early death from heart disease, infections and cancer. Many CKD patients develop end-stage kidney disease and need dialysis or kidney transplants. Recipients of kidney transplants also are prone to CKD. Current tests cannot predict which patients will have CKD that worsens over time. Identifying CKD patients at risk for disease progression could allow clinicians to treat patients earlier and slow further decline in kidney function. It also could help scientists develop therapies that prevent decline in kidney function in patients at risk. This research team will identify types of exRNA in the urine of CKD patients and will determine whether this approach can identify patients at risk for worsening disease. The team plans to use these findings to develop a urine test that clinicians can use to guide treatment of CKD patients.
Investigators: Julie Anne Saugstad, Ph.D., and Joseph M. Quinn, M.D., Oregon Health and Science University, Portland
Grant Number: UH2-TR000903
Alzheimer’s disease (AD) is the most common form of dementia and is the sixth leading cause of death in the United States. AD symptoms include memory loss, personality changes and trouble thinking, and the disease typically worsens over time. Current AD treatments cannot stop the disease from progressing, but they can slow the development of symptoms temporarily. Currently, clinicians diagnose AD by noting the degree of a patient’s mental decline, which is not obvious until severe and permanent brain damage has occurred. No biomarkers exist that can be used to predict the onset of AD or distinguish early AD from age-related memory loss. ExRNA could have an important role as a diagnostic biomarker for AD. This project team will examine miRNA found in the fluid surrounding the brain and spinal cord for its usefulness as a biomarker to diagnose AD earlier. Earlier diagnosis could allow patients to start treatments sooner, possibly slowing or preventing brain function decline and damage.
Investigator: David T.W. Wong, D.M.D., D.M.Sc., University of California, Los Angeles
Grant Number: UH2-TR000923
Gastric (stomach) cancer kills about 800,000 people worldwide each year. This cancer is quite deadly because most people do not notice symptoms until the disease has advanced. Studies suggest that exRNA in saliva can be used as a biomarker to detect oral cancer, Sjögren’s syndrome (a disease in which immune cells attack and destroy the glands that produce tears and saliva), pancreatic cancer, breast cancer, lung cancer and ovarian cancer. This project team will study exRNA in saliva to determine its usefulness as a biomarker for gastric cancer. The study will compare exRNA in saliva from people with and without gastric cancer to assess which types of exRNA are specific to gastric cancer. The use of exRNA in saliva as a biomarker of gastric cancer could enable clinicians to perform simple tests to detect and treat gastric cancer at earlier stages.
Investigators: Bob S. Carter, M.D., Ph.D., University of California, San Diego, and Fred Hochberg, M.D., Massachusetts General Hospital, Boston
Grant Number: UH2-TR000931
Gliomas are the most common type of brain tumor and, when malignant, require care that poses an economic and emotional burden to many individuals. The tumors are hard to diagnose and treat. Surgeons use biopsies to provide diagnoses, but many patients cannot sustain an operation or obtain benefit, as surgery requires removal of brain tissue responsible for language or movement. These investigators will change patient care by providing diagnoses of malignant and benign gliomas, without surgery, based on “liquid biopsies” of blood and fluid covering the brain. Working with a consortium composed of 20 American brain surgeons, the investigators have developed techniques to characterize small amounts of exRNA within exosomes that are released by brain tumors. By using state-of-the-art technologies, they can identify the exRNA without surgery but with a high degree of accuracy. This approach sets the stage for “personalized medical care” of brain tumor patients. This research could lead to safer, less expensive forms of diagnosis and a more rapid, personalized, effective treatment of brain tumors. Findings from this research also could be used to improve scientists’ understanding of risk factors for gliomas, improve how patients respond to brain tumor treatments and create a roadmap of therapies for patients.
Investigators: Kendall Van Kueren-Jensen, Ph.D., and Matthew J. Huentelman, Ph.D., Translational Genomics Research Institute, Phoenix; P. David Adelson, M.D., Phoenix Children’s Hospital; and Robert Spetzler, M.D., St. Joseph’s Hospital and Medical Center, Phoenix
Grant Number: UH2-TR000891
Intracranial hemorrhage (ICH) ― bleeding in the brain ― is most often caused by head injuries or strokes. These life-threatening conditions can severely damage brain tissue and often leave patients disabled. Scientists still do not fully understand what goes wrong in the brain during and after these events. A biomarker to detect patients at risk for poor outcomes following ICH could lead to better treatments while improving understanding of the biology of the disease. Certain types of exRNA may be used as biomarkers to predict how patients will respond after ICH. The investigators will identify exRNA biomarkers that can indicate presence of injury and predict a patient’s outcome after ICH. Ultimately, this research could allow for earlier and better treatments and outcomes in patients as well as improved understanding of the disease biology.
Investigator: Louise C. Laurent, M.D., Ph.D., University of California, San Diego
Grant Number: UH2-TR000906
Placental dysfunction occurs when too little blood, carrying oxygen and nutrients, flows from the mother to the fetus in the womb. The condition can cause poor growth of the fetus and dangerously high blood pressure in the mother during pregnancy. Placental dysfunction is a major cause of maternal and fetal disability and death worldwide. Scientists believe that abnormal cell growth and activity in the placenta during the first trimester of pregnancy causes placental dysfunction. However, clinicians usually do not detect placental dysfunction until the late second and third trimesters. Early detection of pregnancies at risk for this disorder would help clinicians prevent or better treat it. This project’s investigators aim to develop such a method by examining whether exRNA in the blood could be used as a biomarker of risk for placental dysfunction. Accurately determining a woman’s risk would enable clinicians to identify high-risk patients so that high blood pressure or poor growth of the fetus can be detected earlier while sparing low-risk patients unnecessary anxiety.
Investigator: Tushar Patel, M.B., Ch.B., Mayo Clinic, Jacksonville, Florida
Grant Number: UH2-TR000884
Hepatocellular carcinoma (HCC), the most common type of liver cancer, is becoming more prevalent, yet survival remains poor. The earlier HCC is diagnosed, the better a patient’s chance for survival. Unfortunately, current tests for HCC are not very good at detecting the cancer early enough for clinicians to treat it effectively. HCC cells release several types of exRNA within exosomes, tiny particles produced by most cells that carry exRNA through body fluids. This project is designed to determine whether this exRNA can be used as a biomarker to indicate the presence of HCC in a patient. The investigator also aims to develop a clinically useful way to detect and measure these potential biomarkers and determine their usefulness in identifying patients with HCC earlier than current methods allow.
Investigator: Jane E. Freedman, M.D., University of Massachusetts Medical School, Worcester
Grant Number: UH2-TR000921
Cardiovascular disease (CVD) is the leading cause of death in the United States. Heart disease and stroke, the most common forms of CVD, have common risk factors, including high blood pressure, diabetes, obesity, cigarette smoking and high cholesterol. Certain types of exRNA in the blood affect development and progression of CVD. Researchers have found connections between some of this exRNA and specific forms of CVD. The amounts and types of exRNA may change over time or due to the presence of certain CVD risk factors. Different types of this exRNA could be useful as biomarkers to predict CVD events. To test this possibility, the project team will use blood samples to look for links between exRNA and the presence of CVD. The investigators ultimately will attempt to develop a quick and effective blood test for CVD and its risk factors, using exRNA as a biomarker.
Investigators: Saumya Das, M.D., Ph.D., and Anthony Rosenzweig, M.D., Beth Israel Deaconess Medical Center, Boston; and Raymond Y. Kwong, M.D., M.P.H., and Marc Sabatine, M.D., M.P.H., Brigham and Women’s Hospital, Boston
Grant Number: UH2-TR000901
Each year, complications from heart attacks (also called myocardial infarctions) contribute to more than half a million cases of heart failure and 300,000 cases of sudden cardiac arrest, due to lethal arrhythmias. Both of these conditions are closely related to changes in the structure and function of the heart — called remodeling — that follow a heart attack. Current tests to predict which patients are at risk for these complications are not accurate enough. This team of investigators will (1) identify exRNA that are related to poor heart remodeling, (2) assess the functionality and prognostic ability of exRNA signatures in animal models of heart disease, and (3) determine whether exRNA signatures can predict which patients are at risk for poor health outcomes after heart attacks. This test could replace current tests by more accurately identifying patients at higher risk and in need of more frequent monitoring and medical care.