Contribution of Global Amyloid-PET Imaging for Predicting Future Cognition in the MEMENTO Cohort.

BACKGROUND AND OBJECTIVES: Global amyloid-PET is associated with cognition and cognitive decline, but most research on this association does not account for past cognitive information. We assessed the prognostic benefit of amyloid-PET measures for future cognition when prior cognitive assessments are available, evaluating the added value of amyloid measures beyond information on multiple past cognitive assessments. METHODS: The French MEMENTO cohort (a cohort of outpatients from French research memory centers to improve knowledge on Alzheimer disease and related disorders) includes older outpatients with incipient cognitive changes, but no dementia diagnosis at inclusion. Global amyloid burden was assessed using positron emission tomography (amyloid-PET) for a subset of participants; semiannual cognitive testing was subsequently performed. We predicted mini-mental state examination (MMSE) scores using demographic characteristics (age, sex, marital status, and education) alone or in combination with information on prior cognitive measures. The added value of amyloid burden as a predictor in these models was evaluated with percent reduction of the mean squared error (MSE). All models were conducted separately for evaluating the added value of dichotomous amyloid positivity status compared with a continuous amyloid-standardized uptake-value ratio. RESULTS: Our analytic sample comprised 510 individuals who underwent amyloid-PET scans with at least 4 MMSE assessments. The mean age at the PET scan was 71.6 (standard deviation 7.4) years; 60.7% were female. The median follow-up was 4.6 years (interquartile range: 0.9 years). Adding amyloid burden when adjusting for only demographic characteristics reduced the MSE of predictions by 5.08% (95% CI 0.97%-10.86%) and 12.64% (95% CI 3.35%-25.28%) for binary and continuous amyloid, respectively. If the model included 1 past MMSE measure, the MSE improvement was 3.51% (95% CI 1.01%-7.28%) when adding binary amyloid and 8.83% (95% CI 2.63%-16.37%) when adding continuous amyloid. Improvements in model fit were smaller with the addition of amyloid burden when more than 1 past cognitive assessment was included. For all models incorporating past cognitive assessments, differences in predictions amounted to a fraction of 1 MMSE point on average. DISCUSSION: In a clinical setting, global amyloid burden did not appreciably improve cognitive predictions when past cognitive assessments were available. TRIAL REGISTRATION INFORMATION: ClinicalTrials.gov Identifier: NCT02164643.

Association between cancer and dementia risk in the UK Biobank: evidence of diagnostic bias.

Epidemiological studies have identified an inverse association between cancer and dementia. Underlying methodological biases have been postulated, yet no studies have systematically investigated the potential for each source of bias within a single dataset. We used the UK Biobank to compare estimates for the cancer-dementia association using different analytical specifications designed to sequentially address multiple sources of bias, including competing risk of death, selective survival, confounding bias, and diagnostic bias. We included 140,959 UK Biobank participants aged ≥ 55 without dementia before enrollment and with linked primary care data. We used cancer registry data to identify cancer cases prevalent before UK Biobank enrollment and incident cancer diagnosed after enrollment. We used Cox models to evaluate associations of prevalent and incident cancer with all-cause dementia, Alzheimer's disease (AD), and vascular dementia. We used time-varying models to evaluate diagnostic bias. Over a median follow-up of 12.3 years, 3,310 dementia cases were diagnosed. All-site incident cancer was positively associated with all-cause dementia incidence (hazard ratio [HR] = 1.14, 95% CI: 1.02-1.29), but prevalent cancer was not (HR = 1.04, 95% CI: 0.92-1.17). Results were similar for vascular dementia. AD was not associated with prevalent or incident cancer. Dementia diagnosis was substantially elevated in the first year after cancer diagnosis (HR = 1.83, 95% CI: 1.42-2.36), after which the association attenuated to null, suggesting diagnostic bias. Following a cancer diagnosis, health care utilization or cognitive consequences of diagnosis or treatment may increase chance of receiving a dementia diagnosis, creating potential diagnostic bias in electronic health records-based studies.

Pragmatic approaches to handling practice effects in longitudinal cognitive aging research.

INTRODUCTION: The challenge of accounting for practice effects (PEs) when modeling cognitive change was amplified by the COVID-19 pandemic, which introduced period and mode effects that may bias the estimation of cognitive trajectory. METHODS: In three Kaiser Permanente Northern California prospective cohorts, we compared predicted cognitive trajectories and the association of grip strength with cognitive decline using three approaches: (1) no acknowledgment of PE, (2) inclusion of a wave indicator, and (3) constraining PE based on a preliminary model (APM) fit using a subset of the data. RESULTS: APM-based correction for PEs based on balanced, pre-pandemic data, and with current age as the timescale produced the smallest discrepancy between within-person and between-person estimated age effects. Estimated associations between grip strength and cognitive decline were not sensitive to the approach used. DISCUSSION: Constraining PEs based on a preliminary model is a flexible, pragmatic approach allowing for meaningful interpretation of cognitive change. HIGHLIGHTS: The magnitude of practice effects (PEs) varied widely by study. When PEs were present, the three PE approaches resulted in divergent estimated age-related cognitive trajectories. Estimated age-related cognitive trajectories were sometimes implausible in models that did not account for PEs. The associations between grip strength and cognitive decline did not differ by the PE approach used. Constraining PEs based on estimates from a preliminary model allows for a meaningful interpretation of cognitive change.

The impact of attending historically Black colleges and universities on cognitive decline in Black adults: A longitudinal analysis in the KHANDLE and STAR cohorts.

INTRODUCTION: Black students attending predominantly White institutions (PWIs) versus historically Black colleges and universities (HBCUs) report more harmful discrimination and develop worse mental health outcomes, potentially offsetting the established benefits of college for lowering dementia incidence. METHODS: Black participants in two cohorts (the Kaiser Healthy Aging and Diverse Life Experiences [KHANDLE] and the Study of Healthy Aging in African Americans [STAR]) who had attended college (N = 716) self-reported the college name (classified as HBCU vs. PWI) and completed three waves of executive function (EF) and verbal episodic memory (VEM) assessments. HBCU effects on cognitive level and decline were estimated using adjusted linear mixed-effects models. RESULTS: HBCU (vs. PWI) attendees averaged better EF (ß = 0.05 [-0.22, 0.32]) and VEM (ß = 0.21 [-0.06, 0.46]) at age 70 though neither association was statistically significant. HBCU attendance was associated with slightly faster VEM decline (ß = -0.03 [-0.05, 0.00]). DISCUSSION: Harmonized analyses with larger studies are needed to estimate important effects of HBCU attendance. HIGHLIGHTS: Higher education is robustly linked to lower dementia risk, yet Black-White inequities persist among college-educated adults. Black students attending predominantly White institutions (PWIs) versus historically Black colleges and universities (HBCUs) report more harmful discrimination and develop worse mental health outcomes, which may offset the established benefits of college for lowering dementia incidence. HBCU (vs. non-HBCU) attendees averaged better executive function and verbal episodic memory (VEM) at average age 70, though confidence intervals were wide and associations were not statistically significant, and averaged slightly faster decline in VEM. Harmonized analyses using larger nationally representative studies are likely needed to avoid underestimating the health effects of HBCU attendance.

Evaluating interpersonal discrimination and depressive symptoms as partial mediators of the effects of education on cognition: Evidence from the Study of Healthy Aging in African Americans (STAR).

INTRODUCTION: Education is correlated with positive health outcomes, but associations are sometimes weaker among African Americans. The extent to which exposure to discrimination and depressive symptoms attenuates the education-cognition link has not been investigated. METHODS: Study of Healthy Aging in African Americans (STAR) participants (n = 764; average age 69 years) completed the Spanish and English Neuropsychological Assessment Scales. We assessed everyday and major lifetime discrimination and depressive symptoms as mediators of education effects on cognition using G-estimation with measurement error corrections. RESULTS: Education was correlated with greater major lifetime and everyday discrimination but lower depressive symptoms. Accounting for discrimination and depressive symptoms slightly reduced the estimated effect of education on cognition. The estimated total effect of graduate education (vs 

Postsecondary Education and Late-life Cognitive Outcomes Among Black and White Participants in the Project Talent Aging Study: Can Early-life Cognitive Skills Account for Educational Differences in Late-life Cognition?

BACKGROUND: Higher education consistently predicts improved late-life cognition. Racial differences in educational attainment likely contribute to inequities in dementia risk. However, few studies of education and cognition have controlled for prospectively measured early-life confounders or evaluated whether the education late-life cognition association is modified by race/ethnicity. METHODS: Among 2343 Black and White Project Talent Aging Study participants who completed telephone cognitive assessments, we evaluated whether the association between years of education and cognition (verbal fluency, memory/recall, attention, and a composite cognitive measure) differed by race, and whether these differences persisted when adjusting for childhood factors, including the cognitive ability. RESULTS: In fully adjusted linear regression models, each additional year of education was associated with higher composite cognitive scores for Black [ß=0.137; 95% confidence interval (CI)=0.068, 0.206] and White respondents (ß=0.056; CI=0.034, 0.078) with an interaction with race ( P =0.03). Associations between education and memory/recall among Black adults (ß=0.036; CI=-0.037, 0.109) and attention among White adults (ß=0.022; CI=-0.002, 0.046) were nonsignificant. However, there were significant race-education interactions for the composite ( P =0.03) and attention measures ( P <0.001) but not verbal fluency ( P =0.61) or memory/recall ( P =0.95). CONCLUSION: Education predicted better overall cognition for both Black and White adults, even with stringent control for prospectively measured early-life confounders.

Association of Genetic Variants Linked to Late-Onset Alzheimer Disease With Cognitive Test Performance by Midlife.

Importance: Identifying the youngest age when Alzheimer disease (AD) influences cognition and the earliest affected cognitive domains will improve understanding of the natural history of AD and approaches to early diagnosis. Objective: To evaluate the age at which cognitive differences between individuals with higher compared with lower genetic risk of AD are first apparent and which cognitive assessments show the earliest difference. Design, Setting, and Participants: This cross-sectional study used data from UK Biobank participants of European genetic ancestry, aged 40 years or older, who contributed genotypic and cognitive test data from January 1, 2006, to December 31, 2015. Data analysis was performed from March 10, 2020, to January 4, 2022. Exposure: The AD genetic risk score (GRS), which is a weighted sum of 23 single-nucleotide variations. Main Outcomes and Measures: Seven cognitive tests were administered via touchscreen at in-person visits or online. Cognitive domains assessed included fluid intelligence, episodic memory, processing speed, executive functioning, and prospective memory. Multiple cognitive measures were derived from some tests, yielding 32 separate measures. Interactions between age and AD-GRS for each of the 32 cognitive measures were tested with linear regression using a Bonferroni-corrected P value threshold. For cognitive measures with significant evidence of age by AD-GRS interaction, the youngest age of interaction was assessed with new regression models, with nonlinear specification of age terms. Models with youngest age of interaction from 40 to 70 years, in 1-year increments, were compared, and the best-fitting model for each cognitive measure was chosen. Results across cognitive measures were compared to determine which cognitive indicators showed earliest AD-related change. Results: A total of 405 050 participants (mean [SD] age, 57.1 [7.9] years; 54.1% female) were included. Sample sizes differed across cognitive tests (from 12 455 to 404 682 participants). The AD-GRS significantly modified the association with age on 13 measures derived from the pairs matching (range in difference in mean cognition per decade increase in age for 1-SD higher AD-GRS, 2.5%-11.5%), symbol digit substitution (range in difference in mean cognition per decade increase in age for 1-SD higher AD-GRS, 2.0%-5.8%), and numeric memory tests (difference in mean cognition per decade increase in age for 1-SD higher AD-GRS, 8.8%) (P = 1.56 × 10-3). Best-fitting models suggested that cognitive scores of individuals with a high vs low AD-GRS began to diverge by 56 years of age for all 13 measures and by 47 years of age for 9 measures. Conclusions and Relevance: In this cross-sectional study, by early midlife, subtle differences in memory and attention were detectable among individuals with higher genetic risk of AD.

Association of Social Integration with Cognitive Status in a Multi-Ethnic Cohort: Results From the Kaiser Healthy Aging and Diverse Life Experiences Study.

We evaluated overall and race-specific relationships between social integration and cognition in older adults. Kaiser Healthy Aging and Diverse Life Experiences (KHANDLE) cohort participants included 1343 Asian, Black, Latino, or non-Latino White Kaiser Permanente Northern California members. We estimated the effect of social integration on verbal episodic memory, semantic memory, and executive function derived from the Spanish and English Neuropsychological Assessment (SENAS) Scales. Social integration scores included marital status; volunteer activity; and contact with children, relatives, friends, and confidants. We estimated covariate-adjusted linear mixed-effects models for baseline and 17-month follow-up cognition. Social integration was associated with higher baseline cognitive scores (average  ß = 0.066 (95% confidence interval: 0.040, 0.092)) overall and in each racial/ethnic group. The association did not vary by race/ethnicity. Social integration was not associated with the estimated rate of cognitive change. In this cohort, more social integration was similarly associated with better late-life cognition across racial/ethnic groups.

Explaining the Variance in Cardiovascular Disease Risk Factors: A Comparison of Demographic, Socioeconomic, and Genetic Predictors.

BACKGROUND: Efforts to explain the burden of cardiovascular disease (CVD) often focus on genetic factors or social determinants of health. There is little evidence on the comparative predictive value of each, which could guide clinical and public health investments in measuring genetic versus social information. We compared the variance in CVD-related outcomes explained by genetic versus socioeconomic predictors. METHODS: Data were drawn from the Health and Retirement Study (N = 8,720). We examined self-reported diabetes, heart disease, depression, smoking, and body mass index, and objectively measured total and high-density lipoprotein cholesterol. For each outcome, we compared the variance explained by demographic characteristics, socioeconomic position (SEP), and genetic characteristics including a polygenic score for each outcome and principal components (PCs) for genetic ancestry. We used R-squared values derived from race-stratified multivariable linear regressions to evaluate the variance explained. RESULTS: The variance explained by models including all predictors ranged from 3.7% to 14.3%. Demographic characteristics explained more than half this variance for most outcomes. SEP explained comparable or greater variance relative to the combination of the polygenic score and PCs for most conditions among both white and Black participants. The combination of SEP, polygenic score, and PCs performed substantially better, suggesting that each set of characteristics may independently contribute to the prediction of CVD-related outcomes. Philip R. Lee Institute for Health Policy Studies, Department of Family & Community Medicine, UCSF. CONCLUSIONS: Focusing on genetic inputs into personalized medicine predictive models, without considering measures of social context that have clear predictive value, needlessly ignores relevant information that is more feasible and affordable to collect on patients in clinical settings. See video abstract at, http://links.lww.com/EDE/B879.