Mapping the multicausality of Alzheimer's disease through group model building
SourceGeroScience, 43, 2, (2021), pp. 829-843
Article / Letter to editor
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PI Group Memory & Emotion
Subject130 000 Cognitive Neurology & Memory; Institute for Management Research; Radboudumc 13: Stress-related disorders DCMN: Donders Center for Medical Neuroscience; Radboudumc 16: Vascular damage RIHS: Radboud Institute for Health Sciences; Radboudumc 18: Healthcare improvement science RIHS: Radboud Institute for Health Sciences; Radboudumc 1: Alzheimer`s disease DCMN: Donders Center for Medical Neuroscience; Radboudumc 3: Disorders of movement DCMN: Donders Center for Medical Neuroscience
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.
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