Biomarkers of biological aging predict health outcomes more accurately than chronological age. This study examines the relationship between aging biomarkers, immune function, and kidney health using the Future of Families and Child Wellbeing Study Biomarker Dataset. Using Wave 5 (year 9) and Wave 6 (year 15), we examined biomarker data from a total of 4898 individuals. The panel of aging biomarkers, comprised of epigenetic clocks (GrimAge, Horvath), immune function markers (CD8 + T cells, plasmablasts), and metabolic indicators (GDF-15, leptin), was evaluated in depth. We used principal component analysis (PCA) and K-means clustering for subtype identification. A random forest regressor was employed to predict kidney function using Cystatin C levels, and the importance of features was assessed. Three clusters with unique biological age and immune function profiles were identified. Cluster 1 had younger biological age markers. In Cluster 2, both GrimAge and GDF-15 levels were significantly increased, indicating an elevated risk for age-related diseases. According to predictive modeling, GrimAge, Pack Years, and immune function markers had the strongest influence on Cystatin C levels (R² = 0.856). The incorporation of immune aging markers enhanced the predictive power, emphasizing the importance of immunosenescence in renal health. Aging biomarkers and immune function significantly impact kidney health prediction. The study results call for the utilization of extensive biomarker tests for individualized elderly care and early recognition of kidney deterioration. Clinical practice can be improved by incorporating biological age assessments for the prevention and management of age-related diseases.

生物衰老的生物标志物比实际年龄更准确地预测健康结果。本研究使用 Future of Families and Child Wellbeing Study Biomarker 数据集检查了衰老生物标志物、免疫功能和肾脏健康之间的关系。使用第 5 波（第 9 年）和第 6 波（第 15 年），我们检查了总共 4898 人的生物标志物数据。对由表观遗传时钟 （GrimAge、Horvath）、免疫功能标志物 （CD8 + T 细胞、浆母细胞） 和代谢指标 （GDF-15、瘦素） 组成的衰老生物标志物组进行了深入评估。我们使用主成分分析 （PCA） 和 K-means 聚类进行亚型鉴定。采用随机森林回归器使用胱抑素 C 水平预测肾功能，并评估特征的重要性。确定了三个具有独特生物年龄和免疫功能特征的集群。第 1 组具有更年轻的生物年龄标记。在集群 2 中，GrimAge 和 GDF-15 水平均显著升高，表明患年龄相关疾病的风险升高。根据预测模型，GrimAge 、 Pack Years 和免疫功能标志物对胱抑素 C 水平的影响最强 （R² = 0.856）。免疫衰老标志物的掺入增强了预测能力，强调了免疫衰老在肾脏健康中的重要性。衰老生物标志物和免疫功能显着影响肾脏健康的预测。研究结果呼吁利用广泛的生物标志物测试进行个体化老年护理和早期识别肾脏恶化。通过结合生物年龄评估来预防和管理与年龄相关的疾病，可以改善临床实践。