PheMIME: An interactive web app and knowledge base for phenome-wide, multi-institutional multimorbidity analysis
Presenting author: Yaomin Xu, Department of Biostatistics, Vanderbilt University Medical Center
Co-authored by:
- Siwei Zhang, Department of Biostatistics, Vanderbilt University Medical Center
- Nick Strayer, Posit PBC
- Tess Vessels, Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center
- Karmel Choi, Psychiatric & Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital
- Geoffrey W. Wang, Department of Statistics, North Carolina State University
- Yajing Li, Department of Biostatistics, Vanderbilt University Medical Center
- Cosmin A. Bejan, Department of Biomedical informatics, Vanderbilt University School of Medicine
- Ryan S. Hsi, Department of Urology, Vanderbilt University Medical Center
- Alexander G. Bick, Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center
- Digna R. Velez Edwards, Department of Obstetrics and Gynecology, Vanderbilt University Medical Center
- Michael R. Savona, Division of Hematology and Oncology, Department of Medicine, Vanderbilt University Medical Center
- Elizabeth J. Philips, Center for Drug Safety and Immunology, Department of Medicine, Vanderbilt University Medical Center
- Jill Pulley, Vanderbilt Institute for Clinical and Translational Science, Vanderbilt University Medical Center
- Wesley H. Self, Vanderbilt Institute for Clinical and Translational Science, Vanderbilt University Medical Center
- Wilkins Consuelo Hopkins, Vanderbilt Institute for Clinical and Translational Science, Vanderbilt University Medical Center
- Dan M. Roden, Department of Pharmacology, Vanderbilt University Medical Center
- Jordan W. Smoller, Psychiatric & Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital
- Douglas M. Ruderfer, Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center
Abstract:
Motivation: Multimorbidity, characterized by the simultaneous occurrence of multiple diseases in an individual, is an increasing global health concern, posing substantial challenges to healthcare systems. Comprehensive understanding of disease-disease interactions and intrinsic mechanisms behind multimorbidity can offer opportunities for innovative prevention strategies, targeted interventions, and personalized treatments. Yet, there exist limited tools and datasets that characterize multimorbidity patterns across different populations. To bridge this gap, we used large-scale electronic health record (EHR) systems to develop the Phenome-wide Multi-Institutional Multimorbidity Explorer (PheMIME), which facilitates research in exploring and comparing multimorbidity patterns among multiple institutions, potentially leading to the discovery of novel and robust disease associations that are interoperable across different systems and organizations.