Machine learning methods have been applied to estimate measures of brain aging from neuroimages. However, only rarely have these measures been examined in the context of biologic age. Here, we investigated associations of an MRI-based measure of dementia risk, the Alzheimer’s disease pattern similarity (AD-PS) scores, with measures used to calculate biological age. Participants were those from visit 5 of the Atherosclerosis Risk in Communities Study with cognitive status adjudication, proteomic data, and AD-PS scores available. The AD-PS score estimation is based on previously reported machine learning methods. We evaluated associations of the AD-PS score with all-cause mortality. Sensitivity analyses using only cognitively normal (CN) individuals were performed treating CNS-related causes of death as competing risk. AD-PS score was examined in association with 32 proteins measured, using a Somalogic platform, previously reported to be associated with age. Finally, associations with a deficit accumulation index (DAI) based on a count of 38 health conditions were investigated. All analyses were adjusted for age, race, sex, education, smoking, hypertension, and diabetes. The AD-PS score was significantly associated with all-cause mortality and with levels of 9 of the 32 proteins. Growth/differentiation factor 15 (GDF-15) and pleiotrophin remained significant after accounting for multiple-testing and when restricting the analysis to CN participants. A linear regression model showed a significant association between DAI and AD-PS scores overall. While the AD-PS scores were created as a measure of dementia risk, our analyses suggest that they could also be capturing brain aging.

机器学习方法已被应用于根据神经图像来估计大脑衰老的测量结果。然而，这些措施很少在生物年龄的背景下进行检验。在这里，我们研究了基于 MRI 的痴呆风险测量、阿尔茨海默病模式相似性 (AD-PS) 评分与用于计算生物年龄的测量之间的关联。参与者是来自社区动脉粥样硬化风险研究第 5 次访问的参与者，具有认知状态判定、蛋白质组数据和 AD-PS 评分。 AD-PS 分数估计基于先前报道的机器学习方法。我们评估了 AD-PS 评分与全因死亡率的关联。仅使用认知正常 (CN) 个体进行敏感性分析，将 CNS 相关死亡原因视为竞争风险。 AD-PS 评分与使用 Somalogic 平台测量的 32 种蛋白质相关联进行了检查，此前报道称这些蛋白质与年龄相关。最后，根据 38 种健康状况的计数，调查了与赤字累积指数 (DAI) 的关联。所有分析均针对年龄、种族、性别、教育程度、吸烟、高血压和糖尿病进行了调整。 AD-PS 评分与全因死亡率以及 32 种蛋白质中 9 种的水平显着相关。在考虑多重测试并将分析限制于 CN 参与者后，生长/分化因子 15 (GDF-15) 和多效素仍然显着。线性回归模型显示 DAI 和 AD-PS 分数之间总体上存在显着关联。虽然 AD-PS 评分是为了衡量痴呆症风险而创建的，但我们的分析表明，它们也可以反映大脑的衰老情况。