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The value of prospective metabolomic susceptibility endotypes: broad applicability for infectious diseases
BACKGROUND: As new infectious diseases (ID) emerge and others continue to mutate, there remains an imminent threat, especially for vulnerable individuals. Yet no generalizable framework exists to identify the at-risk group prior to infection. Metabolomics has the advantage of capturing the existing...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10518609/ https://www.ncbi.nlm.nih.gov/pubmed/37734204 http://dx.doi.org/10.1016/j.ebiom.2023.104791 |
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author | Chen, Yulu Mendez, Kevin Begum, Sofina Dean, Emily Chatelaine, Haley Braisted, John Fangal, Vrushali D. Cote, Margaret Huang, Mengna Chu, Su H. Stav, Meryl Chen, Qingwen Prince, Nicole Kelly, Rachel Christopher, Kenneth B. Diray-Arce, Joann Mathé, Ewy A. Lasky-Su, Jessica |
author_facet | Chen, Yulu Mendez, Kevin Begum, Sofina Dean, Emily Chatelaine, Haley Braisted, John Fangal, Vrushali D. Cote, Margaret Huang, Mengna Chu, Su H. Stav, Meryl Chen, Qingwen Prince, Nicole Kelly, Rachel Christopher, Kenneth B. Diray-Arce, Joann Mathé, Ewy A. Lasky-Su, Jessica |
author_sort | Chen, Yulu |
collection | PubMed |
description | BACKGROUND: As new infectious diseases (ID) emerge and others continue to mutate, there remains an imminent threat, especially for vulnerable individuals. Yet no generalizable framework exists to identify the at-risk group prior to infection. Metabolomics has the advantage of capturing the existing physiologic state, unobserved via current clinical measures. Furthermore, metabolomics profiling during acute disease can be influenced by confounding factors such as indications, medical treatments, and lifestyles. METHODS: We employed metabolomic profiling to cluster infection-free individuals and assessed their relationship with COVID severity and influenza incidence/recurrence. FINDINGS: We identified a metabolomic susceptibility endotype that was strongly associated with both severe COVID (OR(ICUadmission) = 6.7, p-value = 1.2 × 10(−08), OR(mortality) = 4.7, p-value = 1.6 × 10(−04)) and influenza (OR(incidence) = 2.9; p-values = 2.2 × 10(−4), β(recurrence) = 1.03; p-value = 5.1 × 10(−3)). We observed similar severity associations when recapitulating this susceptibility endotype using metabolomics from individuals during and after acute COVID infection. We demonstrate the value of using metabolomic endotyping to identify a metabolically susceptible group for two–and potentially more–IDs that are driven by increases in specific amino acids, including microbial-related metabolites such as tryptophan, bile acids, histidine, polyamine, phenylalanine, and tyrosine metabolism, as well as carbohydrates involved in glycolysis. INTERPRETATIONS: These metabolites may be identified prior to infection to enable protective measures for these individuals. FUNDING: The Longitudinal EMR and Omics COVID-19 Cohort (LEOCC) and metabolomic profiling were supported by the 10.13039/100000050National Heart, Lung, and Blood Institute and the Intramural Research Program of the 10.13039/100006108National Center for Advancing Translational Sciences, National Institutes of Health. |
format | Online Article Text |
id | pubmed-10518609 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-105186092023-09-26 The value of prospective metabolomic susceptibility endotypes: broad applicability for infectious diseases Chen, Yulu Mendez, Kevin Begum, Sofina Dean, Emily Chatelaine, Haley Braisted, John Fangal, Vrushali D. Cote, Margaret Huang, Mengna Chu, Su H. Stav, Meryl Chen, Qingwen Prince, Nicole Kelly, Rachel Christopher, Kenneth B. Diray-Arce, Joann Mathé, Ewy A. Lasky-Su, Jessica eBioMedicine Articles BACKGROUND: As new infectious diseases (ID) emerge and others continue to mutate, there remains an imminent threat, especially for vulnerable individuals. Yet no generalizable framework exists to identify the at-risk group prior to infection. Metabolomics has the advantage of capturing the existing physiologic state, unobserved via current clinical measures. Furthermore, metabolomics profiling during acute disease can be influenced by confounding factors such as indications, medical treatments, and lifestyles. METHODS: We employed metabolomic profiling to cluster infection-free individuals and assessed their relationship with COVID severity and influenza incidence/recurrence. FINDINGS: We identified a metabolomic susceptibility endotype that was strongly associated with both severe COVID (OR(ICUadmission) = 6.7, p-value = 1.2 × 10(−08), OR(mortality) = 4.7, p-value = 1.6 × 10(−04)) and influenza (OR(incidence) = 2.9; p-values = 2.2 × 10(−4), β(recurrence) = 1.03; p-value = 5.1 × 10(−3)). We observed similar severity associations when recapitulating this susceptibility endotype using metabolomics from individuals during and after acute COVID infection. We demonstrate the value of using metabolomic endotyping to identify a metabolically susceptible group for two–and potentially more–IDs that are driven by increases in specific amino acids, including microbial-related metabolites such as tryptophan, bile acids, histidine, polyamine, phenylalanine, and tyrosine metabolism, as well as carbohydrates involved in glycolysis. INTERPRETATIONS: These metabolites may be identified prior to infection to enable protective measures for these individuals. FUNDING: The Longitudinal EMR and Omics COVID-19 Cohort (LEOCC) and metabolomic profiling were supported by the 10.13039/100000050National Heart, Lung, and Blood Institute and the Intramural Research Program of the 10.13039/100006108National Center for Advancing Translational Sciences, National Institutes of Health. Elsevier 2023-09-19 /pmc/articles/PMC10518609/ /pubmed/37734204 http://dx.doi.org/10.1016/j.ebiom.2023.104791 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Articles Chen, Yulu Mendez, Kevin Begum, Sofina Dean, Emily Chatelaine, Haley Braisted, John Fangal, Vrushali D. Cote, Margaret Huang, Mengna Chu, Su H. Stav, Meryl Chen, Qingwen Prince, Nicole Kelly, Rachel Christopher, Kenneth B. Diray-Arce, Joann Mathé, Ewy A. Lasky-Su, Jessica The value of prospective metabolomic susceptibility endotypes: broad applicability for infectious diseases |
title | The value of prospective metabolomic susceptibility endotypes: broad applicability for infectious diseases |
title_full | The value of prospective metabolomic susceptibility endotypes: broad applicability for infectious diseases |
title_fullStr | The value of prospective metabolomic susceptibility endotypes: broad applicability for infectious diseases |
title_full_unstemmed | The value of prospective metabolomic susceptibility endotypes: broad applicability for infectious diseases |
title_short | The value of prospective metabolomic susceptibility endotypes: broad applicability for infectious diseases |
title_sort | value of prospective metabolomic susceptibility endotypes: broad applicability for infectious diseases |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10518609/ https://www.ncbi.nlm.nih.gov/pubmed/37734204 http://dx.doi.org/10.1016/j.ebiom.2023.104791 |
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