McKenzie Cathryn, Bucks Romola S, Weinborn Michael, Bourgeat Pierrick, Salvado Olivier, Gavett Brandon E
School of Psychological Science, The University of Western Australia, Perth, WA, Australia.
Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO) Health and Biosecurity, Brisbane, QLD, Australia.
Front Aging Neurosci. 2022 Aug 12;14:943823. doi: 10.3389/fnagi.2022.943823. eCollection 2022.
The residual approach to measuring cognitive reserve (using the residual reserve index) aims to capture cognitive resilience conferred by cognitive reserve, but may be confounded by factors representing brain resilience. We sought to distinguish between brain and cognitive resilience by comparing interactions between the residual reserve index and amyloid, tau, and neurodegeneration ["AT(N)"] biomarkers when predicting executive function. We hypothesized that the residual reserve index would moderate at least one path from an AT(N) biomarker to executive function (consistent with cognitive resilience), as opposed to moderating a path between two AT(N) biomarkers (suggestive of brain resilience).
Participants ( = 332) were from the Alzheimer's Disease Neuroimaging Initiative. The residual reserve index represented the difference between observed and predicted memory performance (a positive residual reserve index suggests higher cognitive reserve). AT(N) biomarkers were: CSF β-amyloid/β-amyloid (A), plasma phosphorylated tau-181 (T), and FDG metabolism in AD-specific regions ([N]). AT(N) biomarkers (measured at consecutive time points) were entered in a sequential mediation model testing the indirect effects from baseline amyloid to executive function intercept (third annual follow-up) and slope (baseline to seventh follow-up), via tau and/or FDG metabolism. The baseline residual reserve index was entered as a moderator of paths between AT(N) biomarkers (e.g., amyloid-tau), and paths between AT(N) biomarkers and executive function.
The residual reserve index interacted with amyloid pathology when predicting FDG metabolism: the indirect effect of amyloid → FDG metabolism → executive function intercept and slope varied as a function of the residual reserve index. With lower amyloid pathology, executive function performance was comparable at different levels of the residual reserve index, but a higher residual reserve index was associated with lower FDG metabolism. With higher amyloid pathology, a higher residual reserve index predicted better executive function via higher FDG metabolism.
The effect of the residual reserve index on executive function performance via FDG metabolism was consistent with cognitive resilience. This suggests the residual reserve index captures variation in cognitive reserve; specifically, neural efficiency, and neural capacity to upregulate metabolism to enhance cognitive resilience in the face of greater amyloid pathology. Implications for future research include the potential bidirectionality between neural efficiency and amyloid accumulation.
测量认知储备的残差法（使用残差储备指数）旨在捕捉认知储备赋予的认知恢复力，但可能会受到代表大脑恢复力的因素的混淆。我们试图通过比较残差储备指数与淀粉样蛋白、tau蛋白和神经退行性变 ["AT(N)"] 生物标志物在预测执行功能时的相互作用，来区分大脑恢复力和认知恢复力。我们假设残差储备指数将调节至少一条从AT(N)生物标志物到执行功能的路径（与认知恢复力一致），而不是调节两个AT(N)生物标志物之间的路径（提示大脑恢复力）。
参与者（n = 332）来自阿尔茨海默病神经影像学计划。残差储备指数代表观察到的和预测的记忆表现之间的差异（正的残差储备指数表明更高的认知储备）。AT(N)生物标志物为：脑脊液β-淀粉样蛋白/β-淀粉样蛋白（A）、血浆磷酸化tau-181（T）以及AD特异性区域的氟代脱氧葡萄糖代谢（[N]）。AT(N)生物标志物（在连续时间点测量）被纳入一个顺序中介模型，测试从基线淀粉样蛋白到执行功能截距（第三次年度随访）和斜率（基线到第七次随访）的间接效应，通过tau蛋白和/或氟代脱氧葡萄糖代谢。基线残差储备指数被作为AT(N)生物标志物之间路径（例如，淀粉样蛋白-tau蛋白）以及AT(N)生物标志物与执行功能之间路径的调节因素。
在预测氟代脱氧葡萄糖代谢时，残差储备指数与淀粉样蛋白病理相互作用：淀粉样蛋白→氟代脱氧葡萄糖代谢→执行功能截距和斜率的间接效应随残差储备指数而变化。淀粉样蛋白病理较低时，在不同残差储备指数水平下执行功能表现相当，但较高的残差储备指数与较低的氟代脱氧葡萄糖代谢相关。淀粉样蛋白病理较高时，较高的残差储备指数通过较高的氟代脱氧葡萄糖代谢预测更好的执行功能。
残差储备指数通过氟代脱氧葡萄糖代谢对执行功能表现的影响与认知恢复力一致。这表明残差储备指数捕捉了认知储备的变化；具体而言，是神经效率以及面对更大淀粉样蛋白病理时上调代谢以增强认知恢复力的神经能力。对未来研究的启示包括神经效率与淀粉样蛋白积累之间可能的双向性。
