Several concepts, which in the aggregate get might be used to account for "resilience" against age- and disease-related changes, have been the subject of much research. These include brain reserve, cognitive reserve, and brain maintenance. However, different investigators have use these terms in different ways, and there has never been an attempt to arrive at consensus on the definition of these concepts. Furthermore, there has been confusion regarding the measurement of these constructs and the appropriate ways to apply them to research. Therefore the reserve, resilience, and protective factors professional interest area, established under the auspices of the Alzheimer's Association, established a whitepaper workgroup to develop consensus definitions for cognitive reserve, brain reserve, and brain maintenance. The workgroup also evaluated measures that have been used to implement these concepts in research settings and developed guidelines for research that explores or utilizes these concepts. The workgroup hopes that this whitepaper will form a reference point for researchers in this area and facilitate research by supplying a common language.

See Derry and Kent (doi:10.1093/awx167) for a scientific commentary on this article.The large variance in cognitive deterioration in subjects who test positive for amyloid-β by positron emission tomography indicates that convergent pathologies, such as iron accumulation, might combine with amyloid-β to accelerate Alzheimer's disease progression. Here, we applied quantitative susceptibility mapping, a relatively new magnetic resonance imaging method sensitive to tissue iron, to assess the relationship between iron, amyloid-β load, and cognitive decline in 117 subjects who underwent baseline magnetic resonance imaging and amyloid-β positron emission tomography from the Australian Imaging, Biomarkers and Lifestyle study (AIBL). Cognitive function data were collected every 18 months for up to 6 years from 100 volunteers who were either cognitively normal (n = 64) or diagnosed with mild cognitive impairment (n = 17) or Alzheimer's disease (n = 19). Among participants with amyloid pathology (n = 45), higher hippocampal quantitative susceptibility mapping levels predicted accelerated deterioration in composite cognition tests for episodic memory [β(standard error) = -0.169 (0.034), P = 9.2 × 10-7], executive function [β(standard error) = -0.139 (0.048), P = 0.004), and attention [β(standard error) = -0.074 (0.029), P = 0.012]. Deteriorating performance in a composite of language tests was predicted by higher quantitative susceptibility mapping levels in temporal lobe [β(standard error) = -0.104 (0.05), P = 0.036] and frontal lobe [β(standard error) = -0.154 (0.055), P = 0.006]. These findings indicate that brain iron might combine with amyloid-β to accelerate clinical progression and that quantitative susceptibility mapping could be used in combination with amyloid-β positron emission tomography to stratify individuals at risk of decline.

BackgroundPrevious studies have demonstrated the utility and sensitivity of the CogState Brief Battery (CBB) in detecting cognitive impairment in Alzheimer’s disease (AD) and mild cognitive impairment (MCI) and in assessing cognitive changes in the preclinical stages of AD. Thus, the CBB may be a useful screening tool to assist in the management of cognitive function in clinical settings. In this study, we aimed to determine the utility of the CBB in identifying the nature and magnitude of cognitive impairments in MCI and AD.MethodsHealthy adults (n = 653) adults with amnestic MCI (n = 107), and adults with AD (n = 44) who completed the CBB participated in this study. Composite Psychomotor/Attention and Learning/Working Memory scores were computed from the individual CBB tests. Differences in composite scores were then examined between the three groups; and sensitivity and specificity analyses were conducted to determine cut scores for the composite scores that were optimal in identifying MCI- and AD-related cognitive impairment.ResultsLarge magnitude impairments in MCI (g = 2.2) and AD (g = 3.3) were identified for the learning/working memory composite, and smaller impairments were observed for the attention/psychomotor composite (g’s = 0.5 and 1, respectively). The cut-score associated with optimal sensitivity and specificity in identifying MCI-related cognitive impairment on the learning/working memory composite was -1SD, and in the AD group, this optimal value was -1.7SD. Both composite scores showed high test-retest reliability (r = 0.95) over four months. Poorer performance on the memory composite was also associated with worse performance on the Mini Mental State Exam and increasing severity on the Clinical Dementia Rating Scale sum of boxes score.ConclusionsResults of this study suggest that the CogState learning/working memory composite score is reduced significantly in CI and AD, correlate well with measures of disease classification and are useful in identifying memory impairment related to MCI- and AD.