PheMIME: An Interactive Web App and Knowledge Base for Phenome-Wide, Multi-Institutional Multimorbidity Analysis

Author:

Zhang SiweiORCID,Strayer NickORCID,Vessels TessORCID,Choi KarmelORCID,Wang Geoffrey W,Li Yajing,Bejan Cosmin AORCID,Hsi Ryan SORCID,Bick Alexander G.ORCID,Velez Edwards Digna RORCID,Savona Michael RORCID,Philips Elizabeth J,Pulley JillORCID,Self Wesley HORCID,Hopkins Wilkins Consuelo,Roden Dan MORCID,Smoller Jordan W.ORCID,Ruderfer Douglas MORCID,Xu YaominORCID

Abstract

ABSTRACTMotivationMultimorbidity, 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 and patterns that are interoperable across different systems and organizations.ResultsPheMIME integrates summary statistics from phenome-wide analyses of disease multimorbidities. These are currently derived from three major institutions: Vanderbilt University Medical Center, Mass General Brigham, and the UK Biobank. PheMIME offers interactive exploration of multimorbidity through multi-faceted visualization. Incorporating an enhanced version of associationSubgraphs, PheMIME enables dynamic analysis and inference of disease clusters, promoting the discovery of multimorbidity patterns. Once a disease of interest is selected, the tool generates interactive visualizations and tables that users can delve into multimorbidities or multimorbidity networks within a single system or compare across multiple systems. The utility of PheMIME is demonstrated through a case study on schizophrenia.Availability and implementationThe PheMIME knowledge base and web application are accessible athttps://prod.tbilab.org/PheMIME/. A comprehensive tutorial, including a use-case example, is available athttps://prod.tbilab.org/PheMIME_supplementary_materials/.Furthermore, the source code for PheMIME can be freely downloaded fromhttps://github.com/tbilab/PheMIME.Data availability statementThe data underlying this article are available in the article and in its online web application or supplementary material.

Publisher

Cold Spring Harbor Laboratory

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