Harrison Benjamin R, Akey Joshua M, Snyder-Mackler Noah, Raftery Dan, Creevy Kate E, Promislow Daniel E L
Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA.
Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton 08540, USA.
bioRxiv. 2025 Aug 25:2025.08.20.671317. doi: 10.1101/2025.08.20.671317.
There is growing interest in the use of molecular features as predictors of age, age-related disease risk and age-related mortality. A major shortcoming of this field, however, is the lack of suitable translational research models to identify and understand the underlying mechanisms of these predictive biomarkers in human populations. In particular, we lack a system which, like humans, is genetically variable, lives in diverse environments, and experiences aging-related chronic conditions treated in the context of a sophisticated health care system. Here, we present results from our analysis of data from the Dog Aging Project, a long-term longitudinal study of aging in more than 50,000 companion dogs. In particular, using longitudinal survival models, we present the striking finding of a strong, highly significant positive correlation between the effect of individual metabolites on all-cause mortality in humans, and the association of those same metabolites on all-cause mortality in dogs. We also find that across these independent human studies, the biomarkers identified are also highly correlated, strongly suggesting a general signature of mortality within the plasma metabolome across humans, and now in dogs as well. Given the many similarities between dogs and humans with respect to genetics, environment, disease, and disease treatment, and the fact that dogs are so much shorter lived than humans, we argue that dogs represent an extremely valuable translational model in our ongoing effort to understand the underlying molecular causes and consequences of age-related morbidity and mortality in humans.
将分子特征用作年龄、与年龄相关疾病风险及与年龄相关死亡率预测指标的兴趣与日俱增。然而，该领域的一个主要缺点是缺乏合适的转化研究模型，以识别和理解这些预测性生物标志物在人群中的潜在机制。具体而言，我们缺乏一个像人类一样具有基因变异性、生活在多样环境中且经历在复杂医疗体系背景下治疗的与衰老相关慢性病的系统。在此，我们展示了对犬类衰老项目数据的分析结果，该项目是对5万多只宠物犬衰老情况进行的长期纵向研究。特别是，我们使用纵向生存模型，呈现了一个惊人发现：个体代谢物对人类全因死亡率的影响与这些相同代谢物对犬类全因死亡率的关联之间存在强烈、高度显著的正相关。我们还发现，在这些独立的人类研究中，所识别出的生物标志物也高度相关，这有力地表明在人类血浆代谢组中存在一个普遍的死亡率特征，现在在犬类中也是如此。鉴于犬类和人类在遗传学、环境、疾病及疾病治疗方面存在诸多相似之处，以及犬类寿命比人类短得多这一事实，我们认为犬类是我们在持续努力理解人类与年龄相关发病和死亡的潜在分子原因及后果过程中极具价值的转化模型。
