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Machine Learning to Understand the Immune-Inflammatory Pathways in Fibromyalgia
Fibromyalgia (FM) is a chronic syndrome characterized by widespread musculoskeletal pain, and physical and emotional symptoms. Although its pathophysiology is largely unknown, immune-inflammatory pathways may be involved. We examined serum interleukin (IL)-6, high sensitivity C-reactive protein (hs-...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6747258/ https://www.ncbi.nlm.nih.gov/pubmed/31470635 http://dx.doi.org/10.3390/ijms20174231 |
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author | Andrés-Rodríguez, Laura Borràs, Xavier Feliu-Soler, Albert Pérez-Aranda, Adrián Rozadilla-Sacanell, Antoni Arranz, Belén Montero-Marin, Jesús García-Campayo, Javier Angarita-Osorio, Natalia Maes, Michael Luciano, Juan V. |
author_facet | Andrés-Rodríguez, Laura Borràs, Xavier Feliu-Soler, Albert Pérez-Aranda, Adrián Rozadilla-Sacanell, Antoni Arranz, Belén Montero-Marin, Jesús García-Campayo, Javier Angarita-Osorio, Natalia Maes, Michael Luciano, Juan V. |
author_sort | Andrés-Rodríguez, Laura |
collection | PubMed |
description | Fibromyalgia (FM) is a chronic syndrome characterized by widespread musculoskeletal pain, and physical and emotional symptoms. Although its pathophysiology is largely unknown, immune-inflammatory pathways may be involved. We examined serum interleukin (IL)-6, high sensitivity C-reactive protein (hs-CRP), CXCL-8, and IL-10 in 67 female FM patients and 35 healthy women while adjusting for age, body mass index (BMI), and comorbid disorders. We scored the Fibromyalgia Severity Score, Widespread Pain Index (WPI), Symptom Severity Scale (SSS), Hospital Anxiety (HADS-A), and Depression Scale and the Perceived Stress Scale (PSS-10). Clinical rating scales were significantly higher in FM patients than in controls. After adjusting for covariates, IL-6, IL-10, and CXCL-8 were lower in FM than in HC, whereas hs-CRP did not show any difference. Binary regression analyses showed that the diagnosis FM was associated with lowered IL-10, quality of sleep, aerobic activities, and increased HADS-A and comorbidities. Neural networks showed that WPI was best predicted by quality of sleep, PSS-10, HADS-A, and the cytokines, while SSS was best predicted by PSS-10, HADS-A, and IL-10. Lowered levels of cytokines are associated with FM independently from confounders. Lowered IL-6 and IL-10 signaling may play a role in the pathophysiology of FM. |
format | Online Article Text |
id | pubmed-6747258 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-67472582019-09-27 Machine Learning to Understand the Immune-Inflammatory Pathways in Fibromyalgia Andrés-Rodríguez, Laura Borràs, Xavier Feliu-Soler, Albert Pérez-Aranda, Adrián Rozadilla-Sacanell, Antoni Arranz, Belén Montero-Marin, Jesús García-Campayo, Javier Angarita-Osorio, Natalia Maes, Michael Luciano, Juan V. Int J Mol Sci Article Fibromyalgia (FM) is a chronic syndrome characterized by widespread musculoskeletal pain, and physical and emotional symptoms. Although its pathophysiology is largely unknown, immune-inflammatory pathways may be involved. We examined serum interleukin (IL)-6, high sensitivity C-reactive protein (hs-CRP), CXCL-8, and IL-10 in 67 female FM patients and 35 healthy women while adjusting for age, body mass index (BMI), and comorbid disorders. We scored the Fibromyalgia Severity Score, Widespread Pain Index (WPI), Symptom Severity Scale (SSS), Hospital Anxiety (HADS-A), and Depression Scale and the Perceived Stress Scale (PSS-10). Clinical rating scales were significantly higher in FM patients than in controls. After adjusting for covariates, IL-6, IL-10, and CXCL-8 were lower in FM than in HC, whereas hs-CRP did not show any difference. Binary regression analyses showed that the diagnosis FM was associated with lowered IL-10, quality of sleep, aerobic activities, and increased HADS-A and comorbidities. Neural networks showed that WPI was best predicted by quality of sleep, PSS-10, HADS-A, and the cytokines, while SSS was best predicted by PSS-10, HADS-A, and IL-10. Lowered levels of cytokines are associated with FM independently from confounders. Lowered IL-6 and IL-10 signaling may play a role in the pathophysiology of FM. MDPI 2019-08-29 /pmc/articles/PMC6747258/ /pubmed/31470635 http://dx.doi.org/10.3390/ijms20174231 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Andrés-Rodríguez, Laura Borràs, Xavier Feliu-Soler, Albert Pérez-Aranda, Adrián Rozadilla-Sacanell, Antoni Arranz, Belén Montero-Marin, Jesús García-Campayo, Javier Angarita-Osorio, Natalia Maes, Michael Luciano, Juan V. Machine Learning to Understand the Immune-Inflammatory Pathways in Fibromyalgia |
title | Machine Learning to Understand the Immune-Inflammatory Pathways in Fibromyalgia |
title_full | Machine Learning to Understand the Immune-Inflammatory Pathways in Fibromyalgia |
title_fullStr | Machine Learning to Understand the Immune-Inflammatory Pathways in Fibromyalgia |
title_full_unstemmed | Machine Learning to Understand the Immune-Inflammatory Pathways in Fibromyalgia |
title_short | Machine Learning to Understand the Immune-Inflammatory Pathways in Fibromyalgia |
title_sort | machine learning to understand the immune-inflammatory pathways in fibromyalgia |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6747258/ https://www.ncbi.nlm.nih.gov/pubmed/31470635 http://dx.doi.org/10.3390/ijms20174231 |
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