Alzheimer’s disease (AD) is a complex, multicausal disorder involving several spatiotemporal scales and scientific domains. While many studies focus on specific parts of this system, the complexity of AD is rarely studied as a whole. In this work, we apply systems thinking to map out known causal mechanisms and risk factors ranging from intracellular to psychosocial scales in sporadic AD. We report on the first systemic causal loop diagram (CLD) for AD, which is the result of an interdisciplinary group model building (GMB) process. The GMB was based on the input of experts from multiple domains and all proposed mechanisms were supported by scientific literature. The CLD elucidates interaction and feedback mechanisms that contribute to cognitive decline from midlife onward as described by the experts. As an immediate outcome, we observed several non-trivial reinforcing feedback loops involving factors at multiple spatial scales, which are rarely considered within the same theoretical framework. We also observed high centrality for modifiable risk factors such as social relationships and physical activity, which suggests they may be promising leverage points for interventions. This illustrates how a CLD from an interdisciplinary GMB process may lead to novel insights into complex disorders. Furthermore, the CLD is the first step in the development of a computational model for simulating the effects of risk factors on AD.

阿尔茨海默病 (AD) 是一种复杂的、多原因的疾病，涉及多个时空尺度和科学领域。虽然许多研究集中于该系统的特定部分，但很少对 AD 的复杂性进行整体研究。在这项工作中，我们应用系统思维来绘制散发性 AD 的已知因果机制和风险因素，范围从细胞内到心理社会尺度。我们报告了第一个 AD 系统因果循环图 (CLD)，这是跨学科小组模型构建 (GMB) 过程的结果。GMB 基于多个领域专家的意见，所有提出的机制均得到科学文献的支持。CLD 阐明了专家所描述的导致中年以后认知能力下降的相互作用和反馈机制。作为直接结果，我们观察到了几个涉及多个空间尺度因素的重要强化反馈循环，这些因素很少在同一理论框架内考虑。我们还观察到可改变的风险因素（例如社会关系和身体活动）的高度中心性，这表明它们可能是干预措施的有希望的杠杆点。这说明了跨学科 GMB 过程中的 CLD 如何可能带来对复杂疾病的新见解。此外，CLD 是开发模拟风险因素对 AD 影响的计算模型的第一步。