McKay Heather S, Bream Jay H, Margolick Joseph B, Martínez-Maza Otoniel, Phair John P, Rinaldo Charles R, Abraham Alison G, Jacobson Lisa P
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Cytokine. 2016 Sep;85:71-9. doi: 10.1016/j.cyto.2016.05.016. Epub 2016 Jun 10.
Chronic systemic inflammation contributes to the development of adverse health conditions, yet the influence of fixed and modifiable risk factors on many serologic biomarkers of inflammation remains largely unknown. Serum concentrations of twenty-three biomarkers, including C-reactive protein (CRP), cytokines (CXCL11, CXCL8, CXCL10, CCL2, CCL13, CCL4, CCL17, CXCL13, IL-10, IL-12p70, IL-6, TNF-α, IL-2, IFN-γ, IL-1β, GM-CSF, BAFF), and soluble immune receptors (sCD14, sIL-2Rα, sCD27, sgp130, sTNF-R2) were measured longitudinally using multiplexed immunometric assays in 250 HIV-uninfected men followed in the Multicenter AIDS Cohort Study (1984-2009). Generalized gamma regression was used to determine the statistical significance of factors associated with each biomarker. After accounting for age, race, and education, and for analysis of multiple biomarkers, higher concentrations of specific individual biomarkers were significantly (P<0.002) associated with hypertension, obesity, hepatitis C infection, stimulant use, and diabetes and lower concentrations with hypercholesterolemia. These associations should be taken into account in epidemiological studies of these biomarkers, and may provide potential targets for disease prevention and treatment.
慢性全身性炎症会促使不良健康状况的发展,然而固定和可改变的风险因素对许多炎症血清生物标志物的影响在很大程度上仍不清楚。在多中心艾滋病队列研究(1984 - 2009年)中,对250名未感染艾滋病毒的男性进行纵向研究,使用多重免疫测定法测量了包括C反应蛋白(CRP)、细胞因子(CXCL11、CXCL8、CXCL10、CCL2、CCL13、CCL4、CCL17、CXCL13、IL - 10、IL - 12p70、IL - 6、TNF -α、IL - 2、IFN -γ、IL - 1β、GM - CSF、BAFF)以及可溶性免疫受体(sCD14、sIL - 2Rα、sCD27、sgp130、sTNF - R2)在内的23种生物标志物的血清浓度。使用广义伽马回归来确定与每种生物标志物相关因素的统计学意义。在考虑年龄、种族和教育因素以及对多种生物标志物进行分析后,特定个体生物标志物的较高浓度与高血压、肥胖、丙型肝炎感染、使用兴奋剂和糖尿病显著相关(P<0.002),而较低浓度与高胆固醇血症相关。在这些生物标志物的流行病学研究中应考虑这些关联,它们可能为疾病预防和治疗提供潜在靶点。