Statistical Models and Mechanisms Linking Biomarkers of Aging to Cognitive-Physical Decline and Dementia

痴呆症影响全球超过4400万成年人，阿尔茨海默病（AD）和相关痴呆症 ADRD占老年人所有病例的60%-80%。身体残疾往往是最后的 死亡前的痴呆症三分之一的痴呆症病例可能归因于可改变的因素， 由于AD治疗的益处尚不清楚，因此需要确定预防痴呆症的干预目标 和身体残疾。由于这两种情况都可能在认知和身体表现不佳之前发生， 十多年来，双重认知-身体衰退的共同生物决定因素影响了神经系统和 肌肉骨骼系统可以为治疗目标提供信息，以预防痴呆和身体残疾。的 老年科学假说认为，针对衰老的生物学可能会更好地影响人类健康，包括 预防痴呆症和身体残疾，而不是针对特定疾病。事实上， 对认知和身体终点的研究表明， 与认知和身体衰退有关。这项工作包括炎症的生物标志物， 衰老的标志如细胞衰老、细胞通讯改变、表观遗传变化、端粒磨损， 营养信号和蛋白质稳态的丧失。然而，流行病学研究尚未严格调查 衰老的生物学机制是否影响认知和身体衰退之间的关系和动态 或痴呆和身体残疾发作。因此，识别生物衰老机制的早期生物标志物 与最初健康的老年人的双重认知-身体衰退和关节痴呆-残疾发作有关 是迈向老年科学指导的预防试验的关键一步。然而，对纵向认知和 物理终点易受生存偏倚和未测量混杂因素的影响。现有统计数据的局限性 方法是准确识别可能影响人类健康的共有生物学机制的生物标志物的关键障碍。 或预测认知和身体终点。因此，需要新的计算模型来克服这些问题。 隔栏.该建议的具体目的是：1）测试衰老生物标志物与纵向双重 认知-身体衰退; 2）测试衰老生物标志物与发生关节痴呆-残疾时间的关系 发病;和3）开发/验证衰老风险评分的生物标志物以预测关节痴呆-残疾。为此， 我们提出了一个生物老化指数和新的计算模型，多变量纵向和时间， 事件结果，并将其应用于来自8项队列研究的> 11，000名社区居民的协调数据 至少65岁的成年人，测量生物标志物。我们假设衰老的生物标志物预测和 部分解释了认知和身体终点之间的关系，而不是已知的风险因素。新电脑- 作为共同研究认知和身体终点的重要工具而开发的模型将与 科学界。该项目的最终公共卫生影响是新的模型和新的生物标志物 为老年科学指导的新战略提供信息，以预防老年人的ADRD和身体残疾。

Dementia affects over 44 million adults worldwide, and Alzheimer’s disease (AD) and related dementias (ADRD) account for 60%-80% of all cases among older adults. Physical disability is often the final consequence of dementia before death. One-third of dementia cases may be attributable to modifiable factors, and due to unclear benefit of AD treatments, there is a need to identify intervention targets to prevent dementia and physical disability. Since both conditions may be preceded by poor cognitive and physical performance by over a decade, shared biological determinants of dual cognitive-physical decline that impact neurological and musculoskeletal systems may inform therapeutic targets to prevent dementia and physical disability. The geroscience hypothesis posits that targeting the biology of aging may better impact human health, including prevention of dementia and physical disability, than targeting specific diseases. Indeed, separate lines of research on cognitive and physical endpoints indicate that biomarkers reflecting the underlying biology of aging are related to both cognitive and physical decline. This work includes biomarkers of inflammation and hallmarks of aging such as cell senescence, altered cell communication, epigenetic changes, telomere attrition, nutrient signaling, and loss of proteostasis. However, epidemiologic studies have not rigorously investigated whether biological mechanisms of aging affect relations and dynamics between cognitive and physical decline or dementia and physical disability onset. Thus, identifying early biomarkers of biological aging mechanisms that are related to dual cognitive-physical decline and joint dementia-disability onset in initially health older adults is a key step toward geroscience-guided prevention trials. However, studies of longitudinal cognitive and physical endpoints are vulnerable to survival bias and unmeasured confounding. Limitations of extant statistical methods are a key barrier to accurately identifying biomarkers of shared biological mechanisms that may affect or predict cognitive and physical endpoints. Thus, new computational models are needed to overcome these barriers. Specific aims of this proposal are to: 1) test relations of biomarkers of aging with longitudinal dual cognitive-physical decline; 2) test relations of biomarkers of aging with time to incident joint dementia-disability onset; and 3) develop/validate a biomarker of aging risk score to predict joint dementia-disability. To this end, we propose a biological aging index and novel computational models for multivariate longitudinal and time-to- event outcomes and to apply them to harmonized data from 8 cohort studies of >11,000 community-dwelling adults aged at least 65 years with measured biomarkers. We hypothesize that biomarkers of aging predict and explain, in part, relations between cognitive and physical endpoints beyond known risk factors. New computa- tional models developed as essential tools to jointly study cognitive and physical endpoints will be shared with the scientific community. The ultimate public health impact of this project is new models and novel biomarkers of aging to inform new geroscience-guided strategies to prevent ADRD and physical disability in older adults.