Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, 211166, China.
Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and International Joint Research Center on Environment and Human Health, Nanjing Medical University, Nanjing, 211166, China.
J Transl Med. 2023 Jul 15;21(1):471. doi: 10.1186/s12967-023-04334-w.
Blood biomarkers for multiple pathways, such as inflammatory response, lipid metabolism, and hormonal regulation, have been suggested to influence the risk of mortality. However, few studies have systematically evaluated the combined predictive ability of blood biomarkers for mortality risk.
We included 267,239 participants from the UK Biobank who had measurements of 28 blood biomarkers and were free of cardiovascular disease (CVD) and cancer at baseline (2006-2010). We developed sex-specific blood biomarker scores for predicting all-cause mortality risk in a training set of 247,503 participants from England and Wales, and validated the results in 19,736 participants from Scotland. Cox and LASSO regression analyses were performed to identify independent predictors for men and women separately. Discrimination and calibration were evaluated by C-index and calibration plots, respectively. We also assessed mediating effects of the biomarkers on the association between traditional risk factors (current smoking, obesity, physical inactivity, hypertension, diabetes) and mortality.
A total of 13 independent predictive biomarkers for men and 17 for women were identified and included in the score development. Compared to the lowest tertile of the score, the highest tertile showed a hazard ratio of 5.36 (95% confidence interval [CI] 5.04-5.71) in men and 4.23 (95% CI 3.87-4.62) in women for all-cause mortality. In the validation set, the score yielded a C-index of 0.73 (95% CI 0.72-0.75) in men and 0.70 (95% CI 0.68-0.73) in women for all-cause mortality; it was also predictive of CVD (C-index of 0.76 in men and 0.79 in women) and cancer (C-index of 0.70 in men and 0.67 in women) mortality. Moreover, the association between traditional risk factors and all-cause mortality was largely mediated by cystatin C, C-reactive protein, 25-hydroxyvitamin D, and hemoglobin A1c.
We established sex-specific blood biomarker scores for predicting all-cause and cause-specific mortality in the general population, which hold the potential to identify high-risk individuals and improve targeted prevention of premature death.
多项通路的血液生物标志物，如炎症反应、脂质代谢和激素调节，已被证明会影响死亡率。然而，很少有研究系统地评估血液生物标志物对死亡风险的综合预测能力。
我们纳入了来自英国生物库的 267239 名参与者，他们在基线时（2006-2010 年）没有心血管疾病（CVD）和癌症，并测量了 28 种血液生物标志物。我们在英格兰和威尔士的 247503 名参与者的训练集中为预测全因死亡率开发了性别特异性血液生物标志物评分，并在来自苏格兰的 19736 名参与者中进行了验证。我们分别使用 Cox 和 LASSO 回归分析来识别男性和女性的独立预测因子。通过 C 指数和校准图分别评估了区分度和校准。我们还评估了生物标志物对传统危险因素（当前吸烟、肥胖、身体活动不足、高血压、糖尿病）与死亡率之间关联的中介作用。
确定了 13 个独立的男性预测生物标志物和 17 个女性预测生物标志物，并将其纳入评分开发中。与评分最低的三分位相比，最高三分位的男性全因死亡率的危险比为 5.36（95%置信区间[CI]5.04-5.71），女性为 4.23（95%CI 3.87-4.62）。在验证集中，该评分在男性中用于全因死亡率的 C 指数为 0.73（95%CI 0.72-0.75），女性为 0.70（95%CI 0.68-0.73）；它也可预测 CVD（男性的 C 指数为 0.76，女性为 0.79）和癌症（男性的 C 指数为 0.70，女性为 0.67）死亡率。此外，传统危险因素与全因死亡率之间的关联在很大程度上由胱抑素 C、C 反应蛋白、25-羟维生素 D 和血红蛋白 A1c 介导。
我们建立了用于预测一般人群全因和特定原因死亡率的性别特异性血液生物标志物评分，这有可能识别高风险个体并改善针对过早死亡的针对性预防。
