Intake frequency of vegetables or seafoods negatively correlates with disease activity of rheumatoid arthritis.
Aged
Aged, 80 and over
Arthritis, Rheumatoid
/ drug therapy
Blood Sedimentation
/ drug effects
Cohort Studies
Feeding Behavior
/ physiology
Female
Humans
Male
Matrix Metalloproteinase 3
/ analysis
Middle Aged
Nutrients
/ therapeutic use
Seafood
/ analysis
Severity of Illness Index
Vegetables
/ metabolism
Journal
PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081
Informations de publication
Date de publication:
2020
2020
Historique:
received:
13
11
2019
accepted:
23
01
2020
entrez:
14
2
2020
pubmed:
14
2
2020
medline:
4
6
2020
Statut:
epublish
Résumé
To clarify the relationship between dietary habit and disease activity of rheumatoid arthritis (RA). This study enrolled RA patients who met the ACR/EULAR 2010 classification criteria from Kyoto University Rheumatoid Arthritis Management Alliance (KURAMA) cohort in 2015. 22-item food frequency questionnaire (FFQ) was taken for the measurement of dietary habit in a single-institution cohort of RA (Kyoto University Rheumatoid Arthritis Management Alliance: KURAMA) in 2015. The disease activities of RA using the Disease Activity Score calculated based on the erythrocyte sedimentation rate (DAS28-ESR), Simplified Disease Activity Index (SDAI), Health Assessment Questionnaire (HAQ), and serum matrix metalloproteinase-3 (MMP-3) level, the use of disease-modifying anti-rheumatic drugs (DMARDs), disease duration, rheumatoid factor, anti-cyclic citrullinated antibody, and body mass index were also examined. All of them were combined and statistically analyzed. 441 RA patients (81% women; mean age 65 years; mean disease duration 15 years) were enrolled from the KURAMA cohort. Average Disease Activity Score-28 using the erythrocyte sedimentation rate (DAS28-ESR) was 2.7. Univariate analysis showed that intake frequency of vegetables had a statistically significant negative correlation with disease activity markers, such as DAS28-ESR (ρ = -0.11, p<0.01), Simplified Disease Activity Index (SDAI) (ρ = -0.16, p<0.001), matrix metalloproteinase-3 (MMP-3) (ρ = -0.21, p<0.0001), and Health Assessment Questionnaire (HAQ) (ρ = -0.13, p<0.01). Factor analysis with varimax rotation was done to simplify the relevance of disease activity to various food items. 22 foods were categorized into five dietary patterns: "seafoods", "vegetables/fruits", "meats/fried foods", "snacks", and "processed foods". The multivariate analysis adjusted for clinically significant confounders showed that "seafoods" had statistically significant negative correlations with DAS28-ESR (β = -0.15, p<0.01), SDAI (β = -0.18, p<0.001), MMP-3 (β = -0.15, p<0.01), and HAQ (β = -0.24, p<0.0001). "Vegetables/fruits" had statistically significant negative correlations with SDAI (β = -0.11 p<0.05), MMP-3 (β = -0.12, p<0.01), and HAQ (β = -0.11, p<0.05). These results suggest that high intake frequency of vegetables/fruits and/or seafoods might correlate with low disease activity.
Identifiants
pubmed: 32053642
doi: 10.1371/journal.pone.0228852
pii: PONE-D-19-31605
pmc: PMC7018088
doi:
Substances chimiques
Matrix Metalloproteinase 3
EC 3.4.24.17
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e0228852Déclaration de conflit d'intérêts
I.M. has declared no conflicts of interests. K.M. has received speaking fees, and/or consulting fees from Eisai Co. Ltd. M.H. received research grant and/or speaker fee from Astellas, Eisai, Tanabe-Mitsubishi, and Brystol-Meyers. T. M. received research grants and/or speaking fees from Asahikasei Pharma Corp., Astellas Pharma Inc., AYUMI Pharmaceutical Corp., Bristol-Myers Squibb, Chugai Pharmaceutical Co, Ltd., Diaichi-Sankyo Co.,Ltd., Eisai Co., Ltd., Eli Lilly Japan K.K., Mitsubishi-Tanabe Pharma Co., Pfizer Japan Inc., Sanofi K.K. and Takeda Pharmaceutical Co., Ltd.. These companies had no role in the design of the study, the collection or analysis of the data, the writing of the manuscript or decision to submit the manuscript for the publication. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
Références
Nutrition. 2018 Jan;45:114-124.e4
pubmed: 28965775
Obesity (Silver Spring). 2017 Jun;25(6):1022-1032
pubmed: 28452404
Diabetes Res Clin Pract. 2018 Jul;141:26-34
pubmed: 29679632
Rheumatol Int. 2018 May;38(5):737-747
pubmed: 29256100
Asian Pac J Cancer Prev. 2004 Jan-Mar;5(1):40-3
pubmed: 15075003
Arthritis Care Res (Hoboken). 2019 Sep;71(9):1216-1223
pubmed: 30295427
Arthritis Care Res (Hoboken). 2018 Mar;70(3):327-332
pubmed: 28635117
Ann Rheum Dis. 2017 Jun;76(6):960-977
pubmed: 28264816
PLoS One. 2014 Jan 15;9(1):e85376
pubmed: 24454853
Nutr Hosp. 2015 Feb 26;31 Suppl 3:49-56
pubmed: 25719771
Clin Nutr. 2018 Apr;37(2):675-680
pubmed: 28285975
J Nutr Sci Vitaminol (Tokyo). 2018;64(2):129-137
pubmed: 29710030
Arthritis Rheum. 2003 Dec 15;49(6):784-8
pubmed: 14673964
Reumatologia. 2018;56(4):259-267
pubmed: 30237632
Clin Rheumatol. 2012 Feb;31(2):363-6
pubmed: 21922187
JCI Insight. 2016 Apr 21;1(5):e85922
pubmed: 27158677
Nutrition. 2012 Nov-Dec;28(11-12):1109-14
pubmed: 23044162
Mod Rheumatol. 2019 Jul;29(4):589-595
pubmed: 30092163
Lancet. 2016 Oct 22;388(10055):2023-2038
pubmed: 27156434
J Acad Nutr Diet. 2015 Dec;115(12):1986-95
pubmed: 26422452
Phytother Res. 2012 Aug;26(8):1246-8
pubmed: 22162258
Best Pract Res Clin Rheumatol. 2017 Feb;31(1):3-18
pubmed: 29221595
Arthritis Rheum. 2008 Oct 15;59(10):1416-23
pubmed: 18821642
Ann Rheum Dis. 2010 Sep;69(9):1580-8
pubmed: 20699241
Best Pract Res Clin Rheumatol. 2017 Feb;31(1):19-30
pubmed: 29221594
Nature. 2013 Dec 19;504(7480):446-50
pubmed: 24226770