Genomic Resources for Enhancing Available Therapies (GREAT1.0) Study
Last updated on July 2021Recruitment
- Recruitment Status
- Recruiting
- Estimated Enrollment
- Same as current
Summary
- Conditions
- Celiac Disease
- Acute Pancreatitis
- Cystic Fibrosis
- Constipation Chronic Idiopathic
- Diabetes Mellitus
- Pancreatic Exocrine Insufficiency
- Crohn Disease
- Bile Acid Synthesis Defect
- Dyslipidemias
- Biliary Cirrhosis
- Cholecystitis
- Cholelithiases
- IPMN
- Diarrhea Chronic
- Chronic Disease
- NASH - Nonalcoholic Steatohepatitis
- Chronic Kidney Diseases
- Rheumatoid Arthritis
- Irritable Bowel Syndrome
- Multiple Sclerosis
- Hepatitis
- Inflammatory Bowel Diseases
- Cyst Pancreas
- Gastritis
- Chronic Pain
- Chronic Pancreatitis
- Constipation - Functional
- Type
- Observational
- Design
- Observational Model: Case-ControlTime Perspective: Prospective
Participation Requirements
- Age
- Between 12 years and 125 years
- Gender
- Both males and females
Description
The Genomic Resource to Enhance Available Therapies (GREAT1.0) Study is a research program for personalized medicine. It is a highly annotated genetic and biosample resource for multiple nested observational cohort studies. It is designed to begin to understand the mechanisms underlying complex dise...
The Genomic Resource to Enhance Available Therapies (GREAT1.0) Study is a research program for personalized medicine. It is a highly annotated genetic and biosample resource for multiple nested observational cohort studies. It is designed to begin to understand the mechanisms underlying complex diseases using clinical information from the UPMC electronic health record (EHR), from case-report forms, and from biological samples. Aim 1. To test the hypothesis that point-of-care electronic health record (EHR)-based phenotyping and clinical measures will be useful for classifying patient by disease risk, subtype, activity, complications, quality of life or using statistical or systems approaches. Aim 2. To test the hypothesis that common diseases can be subtyped using genotype data. Aim 3. To test the hypothesis biological samples will provide additional functional and mechanistic information about subject health, disease or state. The study will be conducted using UPMC patients and population controls. Consent will allow EHR and/or case report form data, plus biological samples to be given a unique code number and transferred to researchers for analysis. Consent will also allow for a secure link to be maintained allowing the research data or samples to be updated, and to contact the clinical team and/or subject to provide them with additional information.
Tracking Information
- NCT #
- NCT04306939
- Collaborators
- Not Provided
- Investigators
- Principal Investigator: David C Whitcomb, MD PhD University of Pittsburgh
Get Well Soon