Ojakäär Triin, Koychev Ivan
Sharp Therapeutics Ltd., London, United Kingdom.
Department of Psychiatry, University of Oxford, Oxford, United Kingdom.
Front Neurol. 2021 Nov 15;12:772836. doi: 10.3389/fneur.2021.772836. eCollection 2021.
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that is the most common cause of dementia. Over a third of dementia cases are estimated to be due to potentially modifiable risk factors, thus offering opportunities for both identification of those most likely to be in early disease as well as secondary prevention. Diabetes, hypertension and chronic kidney failure have all been linked to increased risk for AD and dementia and through their high prevalence are particularly apt targets for initiatives to reduce burden of AD. This can take place through targeted interventions of cardiovascular risk factors (shown to improve cognitive outcomes) or novel disease modifying treatments in people with confirmed AD pathology. The success of this approach to secondary prevention depends on the availability of inexpensive and scalable methods for detecting preclinical and prodromal dementia states. Developments in blood-based biomarkers for Alzheimer's disease are rapidly becoming a viable such method for monitoring large at-risk groups. In addition, digital technologies for remote monitoring of cognitive and behavioral changes can add clinically relevant data to further improve personalisation of prevention strategies. This review sets the scene for this approach to secondary care of dementia through a review of the evidence for cardiovascular risk factors (diabetes, hypertension and chronic kidney disease) as major risk factors for AD. We then summarize the developments in blood-based and cognitive biomarkers that allow the detection of pathological states at the earliest possible stage. We propose that at-risk cohorts should be created based on the interaction between cardiovascular and constitutional risk factors. These cohorts can then be monitored effectively using a combination of blood-based biomarkers and digital technologies. We argue that this strategy allows for both risk factor reduction-based prevention programmes as well as for optimisation of any benefits offered by current and future disease modifying treatment through rapid identification of individuals most likely to benefit from them.
阿尔茨海默病（AD）是一种进行性神经退行性疾病，是痴呆最常见的病因。据估计，超过三分之一的痴呆病例归因于潜在可改变的风险因素，因此为识别最可能处于疾病早期阶段的人群以及二级预防提供了机会。糖尿病、高血压和慢性肾衰竭都与AD和痴呆风险增加有关，且因其高患病率，它们特别适合作为减轻AD负担倡议的目标。这可以通过对心血管危险因素的针对性干预（已证明可改善认知结果）或对确诊有AD病理改变的人群采用新型疾病修饰治疗来实现。这种二级预防方法的成功取决于是否有廉价且可扩展的方法来检测临床前和前驱痴呆状态。基于血液的阿尔茨海默病生物标志物的发展正迅速成为一种可行的监测大量高危人群的方法。此外，用于远程监测认知和行为变化的数字技术可以添加临床相关数据，以进一步改善预防策略的个性化。本综述通过回顾心血管危险因素（糖尿病、高血压和慢性肾病）作为AD主要危险因素的证据，为这种痴呆二级护理方法奠定基础。然后，我们总结基于血液和认知生物标志物的发展，这些标志物能够在尽可能早的阶段检测到病理状态。我们建议应基于心血管和体质危险因素之间的相互作用建立高危队列。然后可以使用基于血液的生物标志物和数字技术相结合的方法对这些队列进行有效监测。我们认为，这种策略既允许基于降低危险因素的预防计划，也允许通过快速识别最可能从当前和未来疾病修饰治疗中获益的个体来优化这些治疗所带来的任何益处。
