Is intracranial volume a suitable proxy for brain reserve? Rik Ossenkoppele

Background: Brain reserve is a concept introduced to explain why Alzheimer's disease (AD) patients with a greater brain volume prior to onset of pathology generally have better clinical outcomes. In this review, we provide a historical background of the emergence of brain reserve and discuss several aspects that need further clarification, including the dynamic or static nature of the concept and its underlying mechanisms and clinical effect. We then describe how brain reserve has been operationalized over the years, and critically evaluate the use of intracranial volume (ICV) as the most widely used proxy for brain reserve. Furthermore, we perform a meta-analysis showing that ICV is associated with higher cognitive performance after adjusting for the presence and amount of pathology. Although we acknowledge its imperfections, we conclude that the use of ICV as a proxy for brain reserve is currently warranted. However, further development of more optimal measures of brain reserve as well as a more clearly defined theoretical framework is essential

Cognitive reserve and clinical progression in Alzheimer disease: A paradoxical relationship

OBJECTIVE: To investigate the relationship between cognitive reserve (CR) and clinical progression across the Alzheimer disease (AD) spectrum. METHODS: We selected 839 β-amyloid (Aβ)-positive participants with normal cognition (NC, n = 175), mild cognitive impairment (MCI, n = 437), or AD dementia (n = 227) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). CR was quantified using standardized residuals (W scores) from a (covariate-adjusted) linear regression with global cognition (13-item Alzheimer's Disease Assessment Scale-cognitive subscale) as an independent variable of interest, and either gray matter volumes or white matter hyperintensity volume as dependent variables. These W scores, reflecting whether an individual's degree of cerebral damage is lower or higher than clinically expected, were tested as predictors of diagnostic conversion (i.e., NC to MCI/AD dementia, or MCI to AD dementia) and longitudinal changes in memory (ADNI-MEM) and executive functions (ADNI-EF). RESULTS: The median follow-up period was 24 months (interquartile range 6-42). Corrected for age, sex, APOE4 status, and baseline cerebral damage, higher gray matter volume-based W scores (i.e., greater CR) were associated with a lower diagnostic conversion risk (hazard ratio [HR] 0.22, p < 0.001) and slower decline in memory (β = 0.48, p < 0.001) and executive function (β = 0.67, p < 0.001). Stratified by disease stage, we found similar results for NC (diagnostic conversion: HR 0.30, p = 0.038; ADNI-MEM: β = 0.52, p = 0.028; ADNI-EF: β = 0.42, p = 0.077) and MCI (diagnostic conversion: HR 0.21, p < 0.001; ADNI-MEM: β = 0.43, p = 0.003; ADNI-EF: β = 0.59, p < 0.001), but opposite findings (i.e., more rapid decline) for AD dementia (ADNI-MEM: β = -0.91, p = 0.002; ADNI-EF: β = -0.77, p = 0.081). CONCLUSIONS: Among Aβ-positive individuals, greater CR related to attenuated clinical progression in predementia stages of AD, but accelerated cognitive decline after the onset of dementia

Determinants of cognitive and brain resilience to tau pathology: a longitudinal analysis

Mechanisms of resilience against tau pathology in individuals across the Alzheimer’s disease spectrum are insufficiently understood. Longitudinal data are necessary to reveal which factors relate to preserved cognition (i.e. cognitive resilience) and brain structure (i.e. brain resilience) despite abundant tau pathology, and to clarify whether these associations are cross-sectional or longitudinal. We employed a longitudinal study design to investigate the role of several demographic, biological and brain structural factors in yielding cognitive and brain resilience to tau pathology as measured with PET.In this multicenter study, we included 366 amyloid-β-positive individuals with mild cognitive impairment or Alzheimer’s disease-dementia with baseline [18F]flortaucipir-PET and longitudinal cognitive assessments. A subset (n = 200) additionally underwent longitudinal structural MRI. We used linear mixed-effects models with global cognition and cortical thickness as dependent variables to investigate determinants of cognitive resilience and brain resilience, respectively. Models assessed whether age, sex, years of education, APOE-ε4 status, intracranial volume (and cortical thickness for cognitive resilience models) modified the association of tau pathology with cognitive decline or cortical thinning.We found that the association between higher baseline tau-PET levels (quantified in a temporal meta-region of interest) and rate of cognitive decline (measured with repeated Mini-Mental State Examination) was adversely modified by older age (Stβinteraction = -0.062, P = 0.032), higher education level (Stβinteraction = -0.072, P = 0.011) and higher intracranial volume (Stβinteraction = -0.07, P = 0.016). Younger age, higher education and greater cortical thickness were associated with better cognitive performance at baseline. Greater cortical thickness was furthermore associated with slower cognitive decline independent of tau burden. Higher education also modified the negative impact of tau-PET on cortical thinning, while older age was associated with higher baseline cortical thickness and slower rate of cortical thinning independent of tau. Our analyses revealed no (cross-sectional or longitudinal) associations for sex and APOE-ε4 status on cognition and cortical thickness.In this longitudinal study of clinically impaired individuals with underlying Alzheimer’s disease neuropathological changes, we identified education as the most robust determinant of both cognitive and brain resilience against tau pathology. The observed interaction with tau burden on cognitive decline suggests that education may be protective against cognitive decline and brain atrophy at lower levels of tau pathology, with a potential depletion of resilience resources with advancing pathology. Finally, we did not find major contributions of sex to brain nor cognitive resilience, suggesting that previous links between sex and resilience might be mainly driven by cross-sectional differences

Differential patterns of gray matter volumes and associated gene expression profiles in cognitively-defined Alzheimer's disease subgroups

The clinical presentation of Alzheimer's disease (AD) varies widely across individuals but the neurobiological mechanisms underlying this heterogeneity are largely unknown. Here, we compared regional gray matter (GM) volumes and associated gene expression profiles between cognitively-defined subgroups of amyloid-β positive individuals clinically diagnosed with AD dementia (age: 66 ± 7, 47% male, MMSE: 21 ± 5). All participants underwent neuropsychological assessment with tests covering memory, executive-functioning, language and visuospatial-functioning domains. Subgroup classification was achieved using a psychometric framework that assesses which cognitive domain shows substantial relative impairment compared to the intra-individual average across domains, which yielded the following subgroups in our sample; AD-Memory (n = 41), AD-Executive (n = 117), AD-Language (n = 33), AD-Visuospatial (n = 171). We performed voxel-wise contrasts of GM volumes derived from 3Tesla structural MRI between subgroups and controls (n = 127, age 58 ± 9, 42% male, MMSE 29 ± 1), and observed that differences in regional GM volumes compared to controls closely matched the respective cognitive profiles. Specifically, we detected lower medial temporal lobe GM volumes in AD-Memory, lower fronto-parietal GM volumes in AD-Executive, asymmetric GM volumes in the temporal lobe (left < right) in AD-Language, and lower GM volumes in posterior areas in AD-Visuospatial. In order to examine possible biological drivers of these differences in regional GM volumes, we correlated subgroup-specific regional GM volumes to brain-wide gene expression profiles based on a stereotactic characterization of the transcriptional architecture of the human brain as provided by the Allen human brain atlas. Gene-set enrichment analyses revealed that variations in regional expression of genes involved in processes like mitochondrial respiration and metabolism of proteins were associated with patterns of regional GM volume across multiple subgroups. Other gene expression vs GM volume-associations were only detected in particular subgroups, e.g., genes involved in the cell cycle for AD-Memory, specific sets of genes related to protein metabolism in AD-Language, and genes associated with modification of gene expression in AD-Visuospatial. We conclude that cognitively-defined AD subgroups show neurobiological differences, and distinct biological pathways may be involved in the emergence of these differences