Inflamm‐aging does not simply reflect increases in pro‐inflammatory markers
Morissette-Thomas, Vincent; Cohen, Alan; Fülöp, Tamas; Riesco, Éléonore; Legault, Véronique; Li, Qing; Milot, Emmanuel; Dusseault‐Bélanger, Françis; Ferrucci, Luigi
Abstract: Many biodemographic studies use biomarkers of inflammation to understand or predict chronic disease and aging. Inflamm-aging, i.e. chronic low-grade inflammation during aging, is commonly characterized by pro-inflammatory biomarkers. However, most studies use just one marker at a time, sometimes leading to conflicting results due to complex interactions among the markers. A multidimensional approach allows a more robust interpretation of the various relationships between the markers. We applied principal component analysis (PCA) to 19 inflammatory biomarkers from the InCHIANTI study. We identified a clear, stable structure among the markers, with the first axis explaining inflammatory activation (both pro- and anti-inflammatory markers loaded strongly and positively) and the second axis innate immune response. The first but not the second axis was strongly correlated with age (r = 0.56, p < 0.0001, r = 0.08 p = 0.053), and both were strongly predictive of mortality (hazard ratios per PCA unit (95% CI): 1.33 (1.16–1.53) and 0.87 (0.76–0.98) respectively) and multiple chronic diseases, but in opposite directions. Both axes were more predictive than any individual markers for baseline chronic diseases and mortality. These results show that PCA can uncover a novel biological structure in the relationships among inflammatory markers, and that key axes of this structure play important roles in chronic disease.
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