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.

中文翻译：

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炎症老化不仅仅反映促炎标志物的增加。

许多生物人口学研究使用炎症生物标志物来了解或预测慢性疾病和衰老。炎症老化，即老化过程中的慢性低度炎症，通常以促炎生物标志物为特征。然而，大多数研究一次只使用一种标记，有时会由于标记之间复杂的相互作用而导致结果相互矛盾。多维方法允许对标记之间的各种关系进行更可靠的解释。我们将主成分分析 (PCA) 应用于 InCHIANTI 研究中的 19 种炎症生物标志物。我们在标记中确定了一个清晰、稳定的结构，第一个轴解释了炎症激活（促炎和抗炎标记都被强烈和积极地加载），第二个轴解释了先天免疫反应。第一个而非第二个轴与年龄密切相关（r=0.56，p<0.0001，r=0.08，p=0.053），并且两者都强烈预测死亡率（每 PCA 单位的风险比（95% CI）：1.33（ 1.16-1.53​​）和 0.87（分别为 0.76-0.98））和多种慢性疾病，但方向相反。对于基线慢性病和死亡率，这两个轴都比任何单个标记更具预测性。这些结果表明，PCA 可以揭示炎症标志物之间关系的新生物结构，并且该结构的关键轴在慢性疾病中发挥重要作用。但在相反的方向。对于基线慢性病和死亡率，这两个轴都比任何单个标记更具预测性。这些结果表明，PCA 可以揭示炎症标志物之间关系的新生物结构，并且该结构的关键轴在慢性疾病中发挥重要作用。但在相反的方向。对于基线慢性病和死亡率，这两个轴都比任何单个标记更具预测性。这些结果表明，PCA 可以揭示炎症标志物之间关系的新生物结构，并且该结构的关键轴在慢性疾病中发挥重要作用。