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Smoking Functions as a Negative Regulator of IGF1 and Impairs Adipokine Network in Patients with Rheumatoid Arthritis
Objectives. Smoking is pathogenic for rheumatoid arthritis (RA) being tightly connected to the genetic and serological risk factors for this disease. This study aims to understand connections between cigarette smoking and serum levels of IGF1 and adipokines in RA. Methods. Serum levels of IGF1 and a...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4794568/ https://www.ncbi.nlm.nih.gov/pubmed/27041823 http://dx.doi.org/10.1155/2016/3082820 |
Sumario: | Objectives. Smoking is pathogenic for rheumatoid arthritis (RA) being tightly connected to the genetic and serological risk factors for this disease. This study aims to understand connections between cigarette smoking and serum levels of IGF1 and adipokines in RA. Methods. Serum levels of IGF1 and adipokines leptin, adiponectin, resistin, and visfatin were measured in two independent cohorts of RA patients from Gothenburg (n = 350) and Leiden (n = 193). An association of these parameters with smoking was tested in a direct comparison and proved by bivariate correlation analysis. The obtained associations were further tested in multivariate regression models where the confounders (age, gender, disease duration, and BMI) were controlled. Results. The smokers had significantly lower serum levels of IGF1, adiponectin, and leptin compared to never smokers. In regression analysis, smoking and low leptin, but not adiponectin, were associated and predicted low IGF1. Additionally, high disease activity and high BMI increased the probability of low leptin. Conclusions. The study indicates cigarette smoking as an important cause of a relative IGF1 and leptin deficiency in RA patients. This novel association between smoking and hypoleptinemia may be of importance for long-term prognosis of RA and for prediction of comorbidities. |
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