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Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts
Published on: September 20, 2024
Factors Associated with Multiple Biomarkers of Systemic Inflammation
Sandi L Navarro1, Elizabeth D Kantor2, Xiaoling Song3
1Fred Hutchinson Cancer Research Center, Division of Public Health Sciences, Seattle, Washington. snavarro@fredhutch.org.
Background:
While much is known about correlates of C-reactive protein (CRP), little is known about correlates of other inflammation biomarkers. As these measures are increasingly being used in epidemiologic studies, it is important to determine what factors affect inflammation biomarker concentrations.
Methods:
Using age, sex, and body mass index (BMI) adjusted linear regression, we examined 38 exposures (demographic and anthropometric measures, chronic disease history, NSAIDs, dietary factors, and supplement use) of 8 inflammation biomarkers [CRP, IL1β, IL6, IL8, TNFα, and soluble TNF receptors (sTNFR) in plasma; and prostaglandin E2 metabolite (PGE-M) in urine] in 217 adults, ages 50 to 76 years.
Results:
Increasing age was associated with higher concentrations of all biomarkers except IL1β. BMI was positively associated with CRP and sTNFR I and II. Saturated fat intake was associated with increased CRP, sTNFRII, TNFα, and IL1β, whereas eicosapentaenoic acid + docosahexaenoic acid (EPA+DHA) intake (diet or total) was associated with decreased CRP, TNFα, and IL1β. Results for sex were varied: CRP and IL6 were lower among men, whereas PGE-M and sTNFRI were higher. Higher CRP was also associated with smoking, hormone replacement therapy use, and γ-tocopherol intake; lower CRP with physical activity, and intakes of dietary vitamin C and total fiber.
Conclusions:
Although the associations varied by biomarker, the factors having the greatest number of significant associations (P ≤ 0.05) with the inflammation biomarkers were age, BMI, dietary saturated fat, and EPA+DHA omega-3 fatty acids.
Impact:
Our results suggest that potential confounders in epidemiologic studies assessing associations with inflammation biomarkers vary across specific biomarkers.
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