Association of Education and Intracranial Volume With Cognitive Trajectories and Mortality Rates Across the Alzheimer Disease Continuum

OBJECTIVE: To investigate relationships of education and intracranial volume (factors related to cognitive versus brain reserve, respectively) with cognitive trajectories and mortality in individuals with biomarker-defined Alzheimer's disease (AD). METHODS: We selected 1,298 amyloid-β-positive memory clinic patients with subjective cognitive decline (SCD, n=142), mild cognitive impairment (MCI, n=274) and AD dementia (n=882) from the Amsterdam Dementia Cohort. All participants underwent baseline MRI and neuropsychological assessment, and 68% received cognitive follow-up (median=2.3 years, interquartile range=2.4). Mortality data were collected from the Central Public Administration. In the total sample and stratified by disease stage (i.e., SCD/MCI versus dementia), we examined education and intracranial volume as predictors of baseline and longitudinal cognitive performance on five cognitive domains [memory, attention, executive, language and visuospatial functions] (linear mixed models) and time-to-death (Cox proportional hazard models). Analyses were adjusted for age, sex, whole-brain gray matter atrophy and MRI field strength. RESULTS: Education and intracranial volume showed consistent positive associations with baseline cognition across disease stages. Longitudinally, we observed a relationship between higher education and faster cognitive decline among dementia patients on global cognition, memory, executive function and language (range β=-0.06-[-0.13], all p<0.05). Furthermore, in the total sample, both higher education and intracranial volume related to lower mortality risk (hazard ratio=0.84 and 0.82, respectively, p<0.05). CONCLUSIONS: In this amyloid-β-positive memory clinic sample, both reserve factors were positively associated with baseline cognition, whereas only education related to longitudinal cognition (i.e., accelerated decline among higher-educated patients with dementia). Moreover, higher education and intracranial volume both moderately attenuated overall mortality risk in AD

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

Social cognition deficits and biometric signatures in the behavioural variant of Alzheimer’s disease

The behavioural variant of Alzheimer’s disease (bvAD) is characterized by early predominant behavioural changes, mimicking the behavioural variant of frontotemporal dementia (bvFTD), which is characterized by social cognition deficits and altered biometric responses to socioemotional cues. These functions remain understudied in bvAD. We investigated multiple social cognition components (i.e. emotion recognition, empathy, social norms and moral reasoning), using the Ekman 60 faces test, Interpersonal Reactivity Index, empathy eliciting videos, Social Norms Questionnaire and moral dilemmas, while measuring eye movements and galvanic skin response. We compared 12 patients with bvAD with patients with bvFTD (n = 14), typical Alzheimer’s disease (tAD, n = 13) and individuals with subjective cognitive decline (SCD, n = 13), using ANCOVAs and age- and sex-adjusted post hoc testing. Patients with bvAD (40.1 ± 8.6) showed lower scores on the Ekman 60 faces test compared to individuals with SCD (49.7 ± 5.0, P &lt; 0.001), and patients with tAD (46.2 ± 5.3, P = 0.05) and higher scores compared to patients with bvFTD (32.4 ± 7.3, P = 0.002). Eye-tracking during the Ekman 60 faces test revealed no differences in dwell time on the eyes (all P &gt; 0.05), but patients with bvAD (18.7 ± 9.5%) and bvFTD (19.4 ± 14.3%) spent significantly less dwell time on the mouth than individuals with SCD (30.7 ± 11.6%, P &lt; 0.01) and patients with tAD (32.7 ± 12.1%, P &lt; 0.01). Patients with bvAD (11.3 ± 4.6) exhibited lower scores on the Interpersonal Reactivity Index compared with individuals with SCD (15.6 ± 3.1, P = 0.05) and similar scores to patients with bvFTD (8.7 ± 5.6, P = 0.19) and tAD (13.0 ± 3.2, P = 0.43). The galvanic skin response to empathy eliciting videos did not differ between groups (all P &gt; 0.05). Patients with bvAD (16.0 ± 1.6) and bvFTD (15.2 ± 2.2) showed lower scores on the Social Norms Questionnaire than patients with tAD (17.8 ± 2.1, P &lt; 0.05) and individuals with SCD (18.3 ± 1.4, P &lt; 0.05). No group differences were observed in scores on moral dilemmas (all P &gt; 0.05), while only patients with bvFTD (0.9 ± 1.1) showed a lower galvanic skin response during personal dilemmas compared with SCD (3.4 ± 3.3 peaks per min, P = 0.01). Concluding, patients with bvAD showed a similar although milder social cognition profile and a similar eye-tracking signature to patients with bvFTD and greater social cognition impairments and divergent eye movement patterns compared with patients with tAD. Our results suggest reduced attention to salient facial features in these phenotypes, potentially contributing to their emotion recognition deficits.</p

Measuring Resilience and Resistance in Aging and Alzheimer Disease Using Residual Methods: A Systematic Review and Meta-analysis

BACKGROUND AND OBJECTIVE: There is a lack of consensus on how to optimally define and measure resistance and resilience in brain and cognitive aging. Residual methods use residuals from regression analysis to quantify the capacity to avoid (resistance) or cope (resilience) "better or worse than expected" given a certain level of risk or cerebral damage. We reviewed the rapidly growing literature on residual methods in the context of aging and Alzheimer disease (AD) and performed meta-analyses to investigate associations of residual method-based resilience and resistance measures with longitudinal cognitive and clinical outcomes. METHODS: A systematic literature search of PubMed and Web of Science databases (consulted until March 2020) and subsequent screening led to 54 studies fulfilling eligibility criteria, including 10 studies suitable for the meta-analyses. RESULTS: We identified articles using residual methods aimed at quantifying resistance (n = 33), cognitive resilience (n = 23), and brain resilience (n = 2). Critical examination of the literature revealed that there is considerable methodologic variability in how the residual measures were derived and validated. Despite methodologic differences across studies, meta-analytic assessments showed significant associations of levels of resistance (hazard ratio [HR] [95% confidence interval (CI)] 1.12 [1.07-1.17]; p < 0.0001) and levels of resilience (HR [95% CI] 0.46 [0.32-0.68]; p < 0.001) with risk of progression to dementia/AD. Resilience was also associated with rate of cognitive decline (β [95% CI] 0.05 [0.01-0.08]; p < 0.01). DISCUSSION: This review and meta-analysis supports the usefulness of residual methods as appropriate measures of resilience and resistance, as they capture clinically meaningful information in aging and AD. More rigorous methodologic standardization is needed to increase comparability across studies and, ultimately, application in clinical practice

Association of Education and Intracranial Volume with Cognitive Trajectories and Mortality Rates Across the Alzheimer Disease Continuum

Objective: To investigate relationships of education and intracranial volume (ICV) (factors related to cognitive and brain reserve, respectively) with cognitive trajectories and mortality in individuals with biomarker-defined Alzheimer disease (AD).MethodsWe selected 1,298 β-amyloid-positive memory clinic patients with subjective cognitive decline (SCD, n = 142), mild cognitive impairment (MCI, n = 274), or AD dementia (n = 882) from the Amsterdam Dementia Cohort. All participants underwent baseline MRI and neuropsychological assessment, and 68% received cognitive follow-up (median 2.3 years, interquartile range 2.4). Mortality data were collected from the Central Public Administration. In the total sample and stratified by disease stage (i.e., SCD/MCI vs dementia), we examined education and ICV as predictors of baseline and longitudinal cognitive performance on 5 cognitive domains (memory, attention, executive, language, and visuospatial functions; linear mixed models) and time to death (Cox proportional hazard models). Analyses were adjusted for age, sex, whole brain gray matter atrophy, and MRI field strength.ResultsEducation and ICV showed consistent positive associations with baseline cognition across disease stages. Longitudinally, we observed a relationship between higher education and faster cognitive decline among patients with dementia on global cognition, memory, executive function, and language (range β = -0.06 to -0.13; all p < 0.05). Furthermore, in the total sample, both higher education and larger ICV were related to lower mortality risk (hazard ratio 0.84 and 0.82, respectively; p < 0.05).DiscussionIn this β-amyloid-positive memory clinic sample, both cognitive and brain reserve were positively associated with baseline cognition, whereas only education was related to longitudinal cognition (i.e., accelerated decline among more highly educated patients with dementia). Higher education and ICV both moderately attenuated overall mortality risk in AD

Issues and recommendations for the residual approach to quantifying cognitive resilience and reserve.

BackgroundCognitive reserve and resilience are terms used to explain interindividual variability in maintenance of cognitive health in response to adverse factors, such as brain pathology in the context of aging or neurodegenerative disorders. There is substantial interest in identifying tractable substrates of resilience to potentially leverage this phenomenon into intervention strategies. One way of operationalizing cognitive resilience that has gained popularity is the residual method: regressing cognition on an adverse factor and using the residual as a measure of resilience. This method is attractive because it provides a statistical approach that is an intuitive match to the reserve/resilience conceptual framework. However, due to statistical properties of the regression equation, the residual approach has qualities that complicate its interpretation as an index of resilience and make it statistically inappropriate in certain circumstances.Methods and resultsWe describe statistical properties of the regression equation to illustrate why the residual is highly correlated with the cognitive score from which it was derived. Using both simulations and real data, we model common applications of the approach by creating a residual score (global cognition residualized for hippocampal volume) in individuals along the AD spectrum. We demonstrate that in most real-life scenarios, the residual measure of cognitive resilience is highly correlated with cognition, and the degree of this correlation depends on the initial relationship between the adverse factor and cognition. Subsequently, any association between this resilience metric and an external variable may actually be driven by cognition, rather than by an operationalized measure of resilience. We then assess several strategies proposed as potential solutions to this problem, such as including both the residual and original cognitive measure in a model. However, we conclude these solutions may be insufficient, and we instead recommend against "pre-regression" strategies altogether in favor of using statistical moderation (e.g., interactions) to quantify resilience.ConclusionsCaution should be taken in the use and interpretation of the residual-based method of cognitive resilience. Rather than identifying resilient individuals, we encourage building more complete models of cognition to better identify the specific adverse and protective factors that influence cognitive decline

Issues and recommendations for the residual approach to quantifying cognitive resilience and reserve

Background: Cognitive reserve and resilience are terms used to explain interindividual variability in maintenance of cognitive health in response to adverse factors, such as brain pathology in the context of aging or neurodegenerative disorders. There is substantial interest in identifying tractable substrates of resilience to potentially leverage this phenomenon into intervention strategies. One way of operationalizing cognitive resilience that has gained popularity is the residual method: regressing cognition on an adverse factor and using the residual as a measure of resilience. This method is attractive because it provides a statistical approach that is an intuitive match to the reserve/resilience conceptual framework. However, due to statistical properties of the regression equation, the residual approach has qualities that complicate its interpretation as an index of resilience and make it statistically inappropriate in certain circumstances. Methods and results: We describe statistical properties of the regression equation to illustrate why the residual is highly correlated with the cognitive score from which it was derived. Using both simulations and real data, we model common applications of the approach by creating a residual score (global cognition residualized for hippocampal volume) in individuals along the AD spectrum. We demonstrate that in most real-life scenarios, the residual measure of cognitive resilience is highly correlated with cognition, and the degree of this correlation depends on the initial relationship between the adverse factor and cognition. Subsequently, any association between this resilience metric and an external variable may actually be driven by cognition, rather than by an operationalized measure of resilience. We then assess several strategies proposed as potential solutions to this problem, such as including both the residual and original cognitive measure in a model. However, we conclude these solutions may be insufficient, and we instead recommend against “pre-regression” strategies altogether in favor of using statistical moderation (e.g., interactions) to quantify resilience. Conclusions: Caution should be taken in the use and interpretation of the residual-based method of cognitive resilience. Rather than identifying resilient individuals, we encourage building more complete models of cognition to better identify the specific adverse and protective factors that influence cognitive decline

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