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Network structure underpinning (dys)homeostasis in chronic fatigue syndrome; Preliminary findings
INTRODUCTION: A large body of evidence has established a pattern of altered functioning in the immune system, autonomic nervous system and hypothalamic pituitary adrenal axis in chronic fatigue syndrome. However, the relationship between components within and between these systems is unclear. In thi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6433252/ https://www.ncbi.nlm.nih.gov/pubmed/30908516 http://dx.doi.org/10.1371/journal.pone.0213724 |
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author | Clark, James E. Ng, Wan-Fai Rushton, Stephen Watson, Stuart Newton, Julia L. |
author_facet | Clark, James E. Ng, Wan-Fai Rushton, Stephen Watson, Stuart Newton, Julia L. |
author_sort | Clark, James E. |
collection | PubMed |
description | INTRODUCTION: A large body of evidence has established a pattern of altered functioning in the immune system, autonomic nervous system and hypothalamic pituitary adrenal axis in chronic fatigue syndrome. However, the relationship between components within and between these systems is unclear. In this paper we investigated the underlying network structure of the autonomic system in patients and controls, and a larger network comprising all three systems in patients alone. METHODS: In a sample of patients and controls we took several measures of autonomic nervous system output during 10 minutes of supine rest covering tests of blood pressure variability, heart rate variability and cardiac output. Awakening salivary cortisol was measured on each of two days with participants receiving 0.5mg dexamethasone during the afternoon of the first day. Basal plasma cytokine levels and the in vitro cytokine response to dexamethasone were also measured. Symptom outcome measures used were the fatigue impact scale and cognitive failures questionnaire. Mutual information criteria were used to construct networks describing the dependency amongst variables. Data from 42 patients and 9 controls were used in constructing autonomic networks, and 15 patients in constructing the combined network. RESULTS: The autonomic network in patients showed a more uneven distribution of information, with two distinct modules emerging dominated by systolic blood pressure during active stand and end diastolic volume and stroke volume respectively. The combined network revealed strong links between elements of each of the three regulatory systems, characterised by three higher modules the centres of which were systolic blood pressure during active stand, stroke volume and ejection fraction respectively. CONCLUSIONS: CFS is a complex condition affecting physiological systems. It is important that novel analytical techniques are used to understand the abnormalities that lead to CFS. The underlying network structure of the autonomic system is significantly different to that of controls, with a small number of individual nodes being highly influential. The combined network suggests links across regulatory systems which shows how alterations in single nodes might spread throughout the network to produce alterations in other, even distant, nodes. Replication in a larger cohort is warranted. |
format | Online Article Text |
id | pubmed-6433252 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-64332522019-04-08 Network structure underpinning (dys)homeostasis in chronic fatigue syndrome; Preliminary findings Clark, James E. Ng, Wan-Fai Rushton, Stephen Watson, Stuart Newton, Julia L. PLoS One Research Article INTRODUCTION: A large body of evidence has established a pattern of altered functioning in the immune system, autonomic nervous system and hypothalamic pituitary adrenal axis in chronic fatigue syndrome. However, the relationship between components within and between these systems is unclear. In this paper we investigated the underlying network structure of the autonomic system in patients and controls, and a larger network comprising all three systems in patients alone. METHODS: In a sample of patients and controls we took several measures of autonomic nervous system output during 10 minutes of supine rest covering tests of blood pressure variability, heart rate variability and cardiac output. Awakening salivary cortisol was measured on each of two days with participants receiving 0.5mg dexamethasone during the afternoon of the first day. Basal plasma cytokine levels and the in vitro cytokine response to dexamethasone were also measured. Symptom outcome measures used were the fatigue impact scale and cognitive failures questionnaire. Mutual information criteria were used to construct networks describing the dependency amongst variables. Data from 42 patients and 9 controls were used in constructing autonomic networks, and 15 patients in constructing the combined network. RESULTS: The autonomic network in patients showed a more uneven distribution of information, with two distinct modules emerging dominated by systolic blood pressure during active stand and end diastolic volume and stroke volume respectively. The combined network revealed strong links between elements of each of the three regulatory systems, characterised by three higher modules the centres of which were systolic blood pressure during active stand, stroke volume and ejection fraction respectively. CONCLUSIONS: CFS is a complex condition affecting physiological systems. It is important that novel analytical techniques are used to understand the abnormalities that lead to CFS. The underlying network structure of the autonomic system is significantly different to that of controls, with a small number of individual nodes being highly influential. The combined network suggests links across regulatory systems which shows how alterations in single nodes might spread throughout the network to produce alterations in other, even distant, nodes. Replication in a larger cohort is warranted. Public Library of Science 2019-03-25 /pmc/articles/PMC6433252/ /pubmed/30908516 http://dx.doi.org/10.1371/journal.pone.0213724 Text en © 2019 Clark et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Clark, James E. Ng, Wan-Fai Rushton, Stephen Watson, Stuart Newton, Julia L. Network structure underpinning (dys)homeostasis in chronic fatigue syndrome; Preliminary findings |
title | Network structure underpinning (dys)homeostasis in chronic fatigue syndrome; Preliminary findings |
title_full | Network structure underpinning (dys)homeostasis in chronic fatigue syndrome; Preliminary findings |
title_fullStr | Network structure underpinning (dys)homeostasis in chronic fatigue syndrome; Preliminary findings |
title_full_unstemmed | Network structure underpinning (dys)homeostasis in chronic fatigue syndrome; Preliminary findings |
title_short | Network structure underpinning (dys)homeostasis in chronic fatigue syndrome; Preliminary findings |
title_sort | network structure underpinning (dys)homeostasis in chronic fatigue syndrome; preliminary findings |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6433252/ https://www.ncbi.nlm.nih.gov/pubmed/30908516 http://dx.doi.org/10.1371/journal.pone.0213724 |
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