The molecular changes that occur with aging are not well understood^1,2,3,4. Here, we performed longitudinal and deep multiomics profiling of 106 healthy individuals from 29 to 75 years of age and examined how different types of ‘omic’ measurements, including transcripts, proteins, metabolites, cytokines, microbes and clinical laboratory values, correlate with age. We identified both known and new markers that associated with age, as well as distinct molecular patterns of aging in insulin-resistant as compared to insulin-sensitive individuals. In a longitudinal setting, we identified personal aging markers whose levels changed over a short time frame of 2–3 years. Further, we defined different types of aging patterns in different individuals, termed ‘ageotypes’, on the basis of the types of molecular pathways that changed over time in a given individual. Ageotypes may provide a molecular assessment of personal aging, reflective of personal lifestyle and medical history, that may ultimately be useful in monitoring and intervening in the aging process.

随着衰老而发生的分子变化尚不清楚^1,2,3,4. 在这里，我们对 106 名 29 至 75 岁的健康个体进行了纵向和深度多组学分析，并检查了不同类型的“组学”测量，包括转录本、蛋白质、代谢物、细胞因子、微生物和临床实验室值如何与年龄相关。我们确定了与年龄相关的已知和新标志物，以及与胰岛素敏感个体相比，胰岛素抵抗个体衰老的不同分子模式。在纵向环境中，我们确定了水平在 2-3 年的短时间内发生变化的个人衰老标志物。此外，我们根据特定个体中随时间变化的分子途径类型，定义了不同个体中不同类型的衰老模式，称为“年龄型”。年龄型可以提供个人衰老的分子评估，