Machine learning to understand the immune-inflammatory pathways in fibromyalgia
Autor/a
Andrés-Rodríguez, Laura
Albert, Feliu-Soler
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.
Fecha de publicación
2019ISSN
1422-0067
Resumen
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.
Tipo de documento
Artículo
Versión del documento
Versión publicada
Lengua
Inglés
Materias (CDU)
61 - Medicina
616.8 - Neurología. Neuropatología. Sistema nervioso
Palabras clave
Fibromiàlgia
Dolor generalitzat
Citocines
Inflamació
Neuroimmune
Fibromialgia
Dolor generalizado
Citocinas
Inflamación
Neuroinmune
Fibromyalgia
Widespread pain
Cytokines
Inflammation
Neuro-immune
Páginas
16
Publicado por
MDPI
Colección
20;17
Publicado en
International Journal of Molecular Sciences
Citación
Andrés-Rodríguez, Laura; Albert, Feliu-Soler; Borràs, Xavier [et al.]. Machine learning to understand the immune-inflammatory pathways in fibromyalgia. International Journal of Molecular Sciences, 2019, 20(17), 4231. Disponible en: <https://www.mdpi.com/1422-0067/20/17/4231>. Fecha de acceso: 25 ene. 2022. DOI: 10.3390/ijms20174231
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