No moderating influence of education on the association between changes in hippocampus volume and memory performance in aging

APOE genotype, hippocampal volume, and cognitive reserve predict improvement by cognitive training in older adults without dementia: a randomized controlled trial

Cognitive training (CT) programs aim to improve cognitive performance and impede its decline. Thus, defining the characteristics of individuals who can benefit from these interventions is essential. Our objectives were to assess if the cognitive reserve (CR), APOE genotype (e4 carriers/non-carriers) and/or hippocampal volume might predict the effectiveness of a CT program. Participants were older adults without dementia (n = 226), randomized into parallel experimental and control groups. The assessment consisted of a neuropsychological protocol and additional data regarding total intracranial, gray matter, left/right hippocampus volume; APOE genotype; and Cognitive Reserve (CR). The intervention involved multifactorial CT (30 sessions, 90 min each), with an evaluation pre- and post-training (at six months); the control group simply following the center's routine activities. The primary outcome measures were the change in cognitive performance and the predictors of change. The results show that APOE-e4 non-carriers (79.1%) with a larger left hippocampal volume achieved better gains in semantic verbal fluency (R2 = .19). Subjects with a larger CR and a greater gray matter volume better improved their processing speed (R2 = .18). Age was correlated with the improvement in executive functions, such that older age predicts less improvement (R2 = .07). Subjects with a larger left hippocampal volume achieved more significant gains in general cognitive performance (R2 = .087). In conclusion, besides the program itself, the effectiveness of CT depends on age, biological factors like genotype and brain volume, and CR. Thus, to achieve better results through a CT, it is essential to consider the different characteristics of the participants, including genetic factors.Trial registration: Trial retrospectively registered on January 29th, 2020-(ClinicalTrials.gov -NCT04245579).

Aging Brain from a Lifespan Perspective

Research during the last two decades has shown that the brain undergoes continuous changes throughout life, with substantial heterogeneity in age trajectories between regions. Especially, temporal and prefrontal cortices show large changes, and these correlate modestly with changes in the corresponding cognitive abilities such as episodic memory and executive function. Changes seen in normal aging overlap with changes seen in neurodegenerative conditions such as Alzheimer's disease; differences between what reflects normal aging vs. a disease-related change are often blurry. This calls for a dimensional view on cognitive decline in aging, where clear-cut distinctions between normality and pathology cannot be always drawn. Although much progress has been made in describing typical patterns of age-related changes in the brain, identifying risk and protective factors, and mapping cognitive correlates, there are still limits to our knowledge that should be addressed by future research. We need more longitudinal studies following the same participants over longer time intervals with cognitive testing and brain imaging, and an increased focus on the representativeness vs. selection bias in neuroimaging research of aging.

Cognitive aging and the life course: A new look at the Scaffolding theory

Our understanding of human neurocognitive aging, its developmental roots, and life course influences has been transformed by brain imaging technologies, increasing availability of longitudinal data sets, and analytic advances. The Scaffolding Theory of Aging and Cognition is a life course model, proposed originally in 2009, featuring adaptivity and compensatory potential as lifelong mechanisms for meeting neurocognitive challenges posed by the environment and by developing or declining brain circuitry. Here, we review the scaffolding theory in relation to new evidence addressing when during the life course potentially enriching and depleting factors exert their effects on brain health and scaffolding, and we consider the implications for separable, and potentially reciprocal, influences on the level of cognitive function and the rate of decline in later life.

Subtypes of brain change in aging and their associations with cognition and Alzheimer's disease biomarkers

Structural brain changes underly cognitive changes in older age and contribute to inter-individual variability in cognition. Here, we assessed how changes in cortical thickness, surface area, and subcortical volume, are related to cognitive change in cognitively unimpaired older adults using structural magnetic resonance imaging (MRI) data-driven clustering. Specifically, we tested (1) which brain structural changes over time predict cognitive change in older age (2) whether these are associated with core cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarkers phosphorylated tau (p-tau) and amyloid-β (Aβ42), and (3) the degree of overlap between clusters derived from different structural features. In total 1899 cognitively healthy older adults (50 - 93 years) were followed up to 16 years with neuropsychological and structural MRI assessments, a subsample of which (n = 612) had CSF p-tau and Aβ42 measurements. We applied Monte-Carlo Reference-based Consensus clustering to identify subgroups of older adults based on structural brain change patterns over time. Four clusters for each brain feature were identified, representing the degree of longitudinal brain decline. Each brain feature provided a unique contribution to brain aging as clusters were largely independent across modalities. Cognitive change and baseline cognition were best predicted by cortical area change, whereas higher levels of p-tau and Aβ42 were associated with changes in subcortical volume. These results provide insights into the link between changes in brain morphology and cognition, which may translate to a better understanding of different aging trajectories.