The relation of genetic and environmental factors to systemic inflammatory biomarker concentrations

BACKGROUND: Environmental and genetic correlates of inflammatory marker variability are incompletely understood. In the family-based Framingham Heart Study, we investigated heritability and candidate gene associations of systemic inflammatory biomarkers.

METHODS AND RESULTS: In offspring participants (n=3710), we examined 11 inflammatory biomarkers (CD40 ligand, C-reactive protein, intercellular adhesion molecule-1, interleukin-6, urinary isoprostanes, monocyte chemoattractant protein-1, myeloperoxidase, P-selectin, tumor necrosis factor-alpha, tumor necrosis factor receptor II, fibrinogen). Heritability and bivariate genetic and environmental correlations were assessed by Sequential Oligogenic Linkage Analysis routines in 1012 family members. We examined 1943 tagging single-nucleotide polymorphisms in 233 inflammatory pathway genes with >or=5 minor allele carriers using a general genetic linear model. Clinical correlates explained 2.4% (CD40 ligand) to 28.5% (C-reactive protein) of the variability in inflammatory biomarkers. Estimated heritability ranged from 10.9% (isoprostanes) to 44.8% (P-selectin). Most correlations between biomarkers were weak although statistically significant. A total of 45 single-nucleotide polymorphism-biomarker associations met the q-value threshold of 0.25. Novel top single-nucleotide polymorphisms were observed in ICAM1 gene in relation to intercellular adhesion molecule-1 concentrations (rs1799969, P=1.32 x 10(-8)) and MPO in relation to myeloperoxidase (rs28730837, P=1.9 x 10(-5)). Lowest P values for trans-acting single-nucleotide polymorphisms were observed for APCS with monocyte chemoattractant protein-1 concentrations (rs1374486, P=1.01 x 10(-7)) and confirmed for IL6R with interleukin-6 concentrations (rs8192284, P=3.36 x 10(-5)). Novel potential candidates (APCS, MPO) need to be replicated.

CONCLUSIONS: Our community-based data support the relevance of clinical and genetic factors for explaining variation in inflammatory biomarker traits.