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

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 mul...

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Autores principales: Zhang, Siwei, Strayer, Nick, Vessels, Tess, Choi, Karmel, Wang, Geoffrey W, Li, Yajing, Bejan, Cosmin A, Hsi, Ryan S, Bick, Alexander G., Velez Edwards, Digna R, Savona, Michael R, Philips, Elizabeth J, Pulley, Jill, Self, Wesley H, Hopkins, Wilkins Consuelo, Roden, Dan M, Smoller, Jordan W., Ruderfer, Douglas M, Xu, Yaomin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10402210/
https://www.ncbi.nlm.nih.gov/pubmed/37547012
http://dx.doi.org/10.1101/2023.07.23.23293047
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author Zhang, Siwei
Strayer, Nick
Vessels, Tess
Choi, Karmel
Wang, Geoffrey W
Li, Yajing
Bejan, Cosmin A
Hsi, Ryan S
Bick, Alexander G.
Velez Edwards, Digna R
Savona, Michael R
Philips, Elizabeth J
Pulley, Jill
Self, Wesley H
Hopkins, Wilkins Consuelo
Roden, Dan M
Smoller, Jordan W.
Ruderfer, Douglas M
Xu, Yaomin
author_facet Zhang, Siwei
Strayer, Nick
Vessels, Tess
Choi, Karmel
Wang, Geoffrey W
Li, Yajing
Bejan, Cosmin A
Hsi, Ryan S
Bick, Alexander G.
Velez Edwards, Digna R
Savona, Michael R
Philips, Elizabeth J
Pulley, Jill
Self, Wesley H
Hopkins, Wilkins Consuelo
Roden, Dan M
Smoller, Jordan W.
Ruderfer, Douglas M
Xu, Yaomin
author_sort Zhang, Siwei
collection PubMed
description 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 and patterns that are interoperable across different systems and organizations. RESULTS: PheMIME 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 IMPLEMENTATION: The PheMIME knowledge base and web application are accessible at https://prod.tbilab.org/PheMIME/. A comprehensive tutorial, including a use-case example, is available at https://prod.tbilab.org/PheMIME_supplementary_materials/. Furthermore, the source code for PheMIME can be freely downloaded from https://github.com/tbilab/PheMIME. DATA AVAILABILITY STATEMENT: The data underlying this article are available in the article and in its online web application or supplementary material.
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spelling pubmed-104022102023-08-05 PheMIME: An Interactive Web App and Knowledge Base for Phenome-Wide, Multi-Institutional Multimorbidity Analysis Zhang, Siwei Strayer, Nick Vessels, Tess Choi, Karmel Wang, Geoffrey W Li, Yajing Bejan, Cosmin A Hsi, Ryan S Bick, Alexander G. Velez Edwards, Digna R Savona, Michael R Philips, Elizabeth J Pulley, Jill Self, Wesley H Hopkins, Wilkins Consuelo Roden, Dan M Smoller, Jordan W. Ruderfer, Douglas M Xu, Yaomin medRxiv Article 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 and patterns that are interoperable across different systems and organizations. RESULTS: PheMIME 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 IMPLEMENTATION: The PheMIME knowledge base and web application are accessible at https://prod.tbilab.org/PheMIME/. A comprehensive tutorial, including a use-case example, is available at https://prod.tbilab.org/PheMIME_supplementary_materials/. Furthermore, the source code for PheMIME can be freely downloaded from https://github.com/tbilab/PheMIME. DATA AVAILABILITY STATEMENT: The data underlying this article are available in the article and in its online web application or supplementary material. Cold Spring Harbor Laboratory 2023-07-30 /pmc/articles/PMC10402210/ /pubmed/37547012 http://dx.doi.org/10.1101/2023.07.23.23293047 Text en https://creativecommons.org/licenses/by-nc/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Zhang, Siwei
Strayer, Nick
Vessels, Tess
Choi, Karmel
Wang, Geoffrey W
Li, Yajing
Bejan, Cosmin A
Hsi, Ryan S
Bick, Alexander G.
Velez Edwards, Digna R
Savona, Michael R
Philips, Elizabeth J
Pulley, Jill
Self, Wesley H
Hopkins, Wilkins Consuelo
Roden, Dan M
Smoller, Jordan W.
Ruderfer, Douglas M
Xu, Yaomin
PheMIME: An Interactive Web App and Knowledge Base for Phenome-Wide, Multi-Institutional Multimorbidity Analysis
title PheMIME: An Interactive Web App and Knowledge Base for Phenome-Wide, Multi-Institutional Multimorbidity Analysis
title_full PheMIME: An Interactive Web App and Knowledge Base for Phenome-Wide, Multi-Institutional Multimorbidity Analysis
title_fullStr PheMIME: An Interactive Web App and Knowledge Base for Phenome-Wide, Multi-Institutional Multimorbidity Analysis
title_full_unstemmed PheMIME: An Interactive Web App and Knowledge Base for Phenome-Wide, Multi-Institutional Multimorbidity Analysis
title_short PheMIME: An Interactive Web App and Knowledge Base for Phenome-Wide, Multi-Institutional Multimorbidity Analysis
title_sort phemime: an interactive web app and knowledge base for phenome-wide, multi-institutional multimorbidity analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10402210/
https://www.ncbi.nlm.nih.gov/pubmed/37547012
http://dx.doi.org/10.1101/2023.07.23.23293047
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