Linking longitudinal and cross-sectional biomarker data to understand host-pathogen dynamics: Leptospira in California sea lions (Zalophus californianus) as a case study.
Confronted with the challenge of understanding population-level processes, disease ecologists and epidemiologists often simplify quantitative data into distinct physiological states (e.g. susceptible, exposed, infected, recovered). However, data defining these states often fall along a spectrum rath...
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ftdoajarticles:oai:doaj.org/article:f7d07a0c335b4eaf80585d51ef0c2efc 2023-05-15T15:16:43+02:00 Linking longitudinal and cross-sectional biomarker data to understand host-pathogen dynamics: Leptospira in California sea lions (Zalophus californianus) as a case study. K C Prager Michael G Buhnerkempe Denise J Greig Anthony J Orr Eric D Jensen Forrest Gomez Renee L Galloway Qingzhong Wu Frances M D Gulland James O Lloyd-Smith 2020-06-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0008407 https://doaj.org/article/f7d07a0c335b4eaf80585d51ef0c2efc EN eng Public Library of Science (PLoS) https://doi.org/10.1371/journal.pntd.0008407 https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0008407 https://doaj.org/article/f7d07a0c335b4eaf80585d51ef0c2efc PLoS Neglected Tropical Diseases, Vol 14, Iss 6, p e0008407 (2020) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2020 ftdoajarticles https://doi.org/10.1371/journal.pntd.0008407 2022-12-31T05:04:46Z Confronted with the challenge of understanding population-level processes, disease ecologists and epidemiologists often simplify quantitative data into distinct physiological states (e.g. susceptible, exposed, infected, recovered). However, data defining these states often fall along a spectrum rather than into clear categories. Hence, the host-pathogen relationship is more accurately defined using quantitative data, often integrating multiple diagnostic measures, just as clinicians do to assess their patients. We use quantitative data on a major neglected tropical disease (Leptospira interrogans) in California sea lions (Zalophus californianus) to improve individual-level and population-level understanding of this Leptospira reservoir system. We create a "host-pathogen space" by mapping multiple biomarkers of infection (e.g. serum antibodies, pathogen DNA) and disease state (e.g. serum chemistry values) from 13 longitudinally sampled, severely ill individuals to characterize changes in these values through time. Data from these individuals describe a clear, unidirectional trajectory of disease and recovery within this host-pathogen space. Remarkably, this trajectory also captures the broad patterns in larger cross-sectional datasets of 1456 wild sea lions in all states of health but sampled only once. Our framework enables us to determine an individual's location in their time-course since initial infection, and to visualize the full range of clinical states and antibody responses induced by pathogen exposure. We identify predictive relationships between biomarkers and outcomes such as survival and pathogen shedding, and use these to impute values for missing data, thus increasing the size of the useable dataset. Mapping the host-pathogen space using quantitative biomarker data enables more nuanced understanding of an individual's time course of infection, duration of immunity, and probability of being infectious. Such maps also make efficient use of limited data for rare or poorly understood diseases, by ... Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLOS Neglected Tropical Diseases 14 6 e0008407 |
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Directory of Open Access Journals: DOAJ Articles |
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English |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 K C Prager Michael G Buhnerkempe Denise J Greig Anthony J Orr Eric D Jensen Forrest Gomez Renee L Galloway Qingzhong Wu Frances M D Gulland James O Lloyd-Smith Linking longitudinal and cross-sectional biomarker data to understand host-pathogen dynamics: Leptospira in California sea lions (Zalophus californianus) as a case study. |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
description |
Confronted with the challenge of understanding population-level processes, disease ecologists and epidemiologists often simplify quantitative data into distinct physiological states (e.g. susceptible, exposed, infected, recovered). However, data defining these states often fall along a spectrum rather than into clear categories. Hence, the host-pathogen relationship is more accurately defined using quantitative data, often integrating multiple diagnostic measures, just as clinicians do to assess their patients. We use quantitative data on a major neglected tropical disease (Leptospira interrogans) in California sea lions (Zalophus californianus) to improve individual-level and population-level understanding of this Leptospira reservoir system. We create a "host-pathogen space" by mapping multiple biomarkers of infection (e.g. serum antibodies, pathogen DNA) and disease state (e.g. serum chemistry values) from 13 longitudinally sampled, severely ill individuals to characterize changes in these values through time. Data from these individuals describe a clear, unidirectional trajectory of disease and recovery within this host-pathogen space. Remarkably, this trajectory also captures the broad patterns in larger cross-sectional datasets of 1456 wild sea lions in all states of health but sampled only once. Our framework enables us to determine an individual's location in their time-course since initial infection, and to visualize the full range of clinical states and antibody responses induced by pathogen exposure. We identify predictive relationships between biomarkers and outcomes such as survival and pathogen shedding, and use these to impute values for missing data, thus increasing the size of the useable dataset. Mapping the host-pathogen space using quantitative biomarker data enables more nuanced understanding of an individual's time course of infection, duration of immunity, and probability of being infectious. Such maps also make efficient use of limited data for rare or poorly understood diseases, by ... |
format |
Article in Journal/Newspaper |
author |
K C Prager Michael G Buhnerkempe Denise J Greig Anthony J Orr Eric D Jensen Forrest Gomez Renee L Galloway Qingzhong Wu Frances M D Gulland James O Lloyd-Smith |
author_facet |
K C Prager Michael G Buhnerkempe Denise J Greig Anthony J Orr Eric D Jensen Forrest Gomez Renee L Galloway Qingzhong Wu Frances M D Gulland James O Lloyd-Smith |
author_sort |
K C Prager |
title |
Linking longitudinal and cross-sectional biomarker data to understand host-pathogen dynamics: Leptospira in California sea lions (Zalophus californianus) as a case study. |
title_short |
Linking longitudinal and cross-sectional biomarker data to understand host-pathogen dynamics: Leptospira in California sea lions (Zalophus californianus) as a case study. |
title_full |
Linking longitudinal and cross-sectional biomarker data to understand host-pathogen dynamics: Leptospira in California sea lions (Zalophus californianus) as a case study. |
title_fullStr |
Linking longitudinal and cross-sectional biomarker data to understand host-pathogen dynamics: Leptospira in California sea lions (Zalophus californianus) as a case study. |
title_full_unstemmed |
Linking longitudinal and cross-sectional biomarker data to understand host-pathogen dynamics: Leptospira in California sea lions (Zalophus californianus) as a case study. |
title_sort |
linking longitudinal and cross-sectional biomarker data to understand host-pathogen dynamics: leptospira in california sea lions (zalophus californianus) as a case study. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2020 |
url |
https://doi.org/10.1371/journal.pntd.0008407 https://doaj.org/article/f7d07a0c335b4eaf80585d51ef0c2efc |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
PLoS Neglected Tropical Diseases, Vol 14, Iss 6, p e0008407 (2020) |
op_relation |
https://doi.org/10.1371/journal.pntd.0008407 https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0008407 https://doaj.org/article/f7d07a0c335b4eaf80585d51ef0c2efc |
op_doi |
https://doi.org/10.1371/journal.pntd.0008407 |
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PLOS Neglected Tropical Diseases |
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14 |
container_issue |
6 |
container_start_page |
e0008407 |
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