Corinne Pettigrew’s research while affiliated with Johns Hopkins University and other places

Background: Early detection of Alzheimer's disease (AD) is crucial; however, standard neuropsychological tests often lack sensitivity. Process scores, such as proper name (PN) recall from Logical Memory (LM), may improve the detection of AD-related biomarker positivity. We examined whether baseline PN recall predicted future cerebrospinal fluid (CSF) amyloid (Aβ42/Aβ40) and tau (pTau181) status, and whether biomarker status predicted PN recall trajectories. Methods: We analyzed 271 cognitively unimpaired BIOCARD participants (mean age = 57.3, 60.3% female, mean follow-up = 15.5) using logistic regression and mixed-effects models to examine the associations between PN recall and CSF biomarkers. Results: Higher baseline PN recall predicted lower amyloid positivity (odds ratio [OR] = 0.72, p = 0.015). Amyloid and tau positivity have been linked to a faster decline in PN. Biomarker-positive participants in the biomarker-negative group lacked practice effects. Conclusions: PN recall predicts future AD biomarker positivity and may enhance early detection of AD-related cognitive decline.

Aging is associated with disruptions in circadian rhythms, lower brain white matter integrity, and cognitive changes. However, whether white matter integrity serves as a potential mechanism linking circadian dysfunction to age-related cognitive abilities in older adults is unclear. We investigated cross-sectional associations of actigraphic circadian rest/activity rhythms (RARs) with whole-brain white matter tract fractional anisotropy (FA) and executive function performance in 156 older adults without dementia from the BIOCARD study (mean age = 71.3 years, including 19 with mild cognitive impairment (MCI) and 137 cognitively unimpaired). We studied non-parametric metrics of RAR strength (relative amplitude [RA]), day-to-day stability (interdaily stability [IS]), and fragmentation (intradaily variability [IV]). After adjusting for age, sex, education, APOE-e4 genotype, vascular risk, and diagnostic group, we found that greater rhythm strength (higher RA) was associated with better executive function. Additionally, higher rhythm strength (RA) and stability (IS) was associated with greater whole-brain FA, reflecting better white matter integrity, whereas greater fragmentation (IV) was associated with lower FA. Greater white matter integrity was also associated with better executive function and statistically mediated the association of higher RA with better executive function performance. Findings underscore the relationships between RAR strength and cognitive health in older adults and suggest that white matter integrity may be a key mechanism underlying these associations.

Brain atrophy over time, as measured by magnetic resonance imaging (MRI), has been shown to predict subsequent cognitive impairment among individuals who were cognitively normal when first evaluated, indicating that subtle brain atrophy associated with Alzheimer's disease (AD) may begin years before clinical symptoms appear. Traditionally, atrophy has been quantified by differences in brain volume or thickness over a specified timeframe. Research indicates that the rate of atrophy varies across different brain regions, which themselves exhibit complex spatial and hierarchical organizations. These characteristics collectively emphasize the need for diverse summary measures that can effectively capture the multidimensional nature of degeneration. In this study, we explore the use of distance measurements to quantify brain volumetric changes using processed MRI data from the Preclinical Alzheimer's Disease Consortium (PAC). We conducted a series of analyses to predict future diagnostic status by modeling MRI trajectories for participants who were cognitively normal at baseline and either remained cognitively normal or progressed to mild cognitive impairment (MCI) over time, with adjustments for age, sex, education, and APOE genotype. We consider multiple distance measures and brain regions through a two‐step approach. First, we build base models by fitting individual mixed‐effect models for each distance metric and brain region pairing, using follow‐up diagnosis (normal vs. MCI) as the outcome and volumetric changes from the baseline, as summarized by a given distance measure, as predictors. The second step aggregates these individual region‐distance base models to derive an overall estimate of diagnostic status. Our analyses showed that the distance measures approach consistently outperformed the traditional direct volumetric approach in terms of predictive accuracy, both in individual base models and the aggregated models. This work highlights the potential advantage of using distance measures over the traditional direct volumetric approach to capture the multidimensional aspects of atrophy in the development of AD and related disorders.

BACKGROUND Alzheimer's disease (AD) is characterized by the abnormal accumulation of amyloid‐beta (Aβ) and tau that can be quantified in vivo through cerebrospinal fluid (CSF) sampling. Physical activity has emerged as a possible modifier of AD risk; however, its impact on CSF biomarkers and cognitive function is not yet fully understood. We examined whether higher levels of physical activity modifies associations between AD CSF biomarkers and cognitive function. METHODS One hundred and seventeen adults free of dementia from the BIOCARD study (mean age 72.2 ± 8.0 years, 70% women) wore a wrist accelerometer for 1 week, underwent lumbar puncture to collect CSF, and completed a comprehensive neuropsychological exam. Multivariable linear regression analyses were used to examine whether physical activity (total activity counts over the 10 most active hours of the day) moderates the association between AD CSF biomarkers [Aβ42/40, phosphorylated tau (p‐tau181), and total tau] and cognitive composite scores (episodic memory, executive function). RESULTS There were significant interactions between physical activity and p‐tau181 (p = 0.016) as well as between physical activity and total tau (p = 0.004) in relation to the executive function composite score. Among participants with higher levels of physical activity, the adverse relationship between CSF‐measured tau and executive function was diminished. In contrast, there were no significant interactions for episodic memory, and physical activity did not interact with Aβ42/40 (all interactions p > 0.05). CONCLUSION A physically active lifestyle may provide protection against AD‐related cognitive decline by reducing the impact of tau pathology. Highlights Older age was associated with lower levels of physical activity, worse CSF biomarker profiles, and poorer cognition. Physical activity moderates the impact of tau pathology on executive function but shows no significant effect on amyloid‐beta pathology. Physical activity may enhance cognitive reserve, thereby attenuating the influence of accumulating AD pathology on cognition.

INTRODUCTION We examined long‐term plasma biomarker trajectories among participants who were cognitively unimpaired and primarily middle aged at baseline and whether trajectories differed by Alzheimer's disease (AD) genetic risk and among those who developed cognitive impairment. METHODS Plasma amyloid beta (Aβ)42/Aβ40, phosphorylated tau (p‐tau)181, neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), soluble triggering receptor expressed on myeloid cells, and chitinase 3‐like protein 1 were measured longitudinally in 177 BIOCARD participants (M baseline age = 57.7 years; M follow‐up = 15.8 years), including 57 who developed cognitive impairment. Measures of AD genetic risk included apolipoprotein E (APOE) ε4 and an AD polygenic risk score (AD‐PRS). RESULTS Compared to non‐carriers, APOE ε4 carriers had lower Aβ42/Aβ40 and greater longitudinal increases in p‐tau181 and GFAP; in contrast, the AD‐PRS (excluding the APOE region) was associated with greater declines in Aβ42/Aβ40 among APOE ε4 non‐carriers. Rates of increase in p‐tau181, NfL, and GFAP were greater among those who later developed cognitive impairment. DISCUSSION Monitoring changes in plasma p‐tau181, NfL, and GFAP may be particularly informative during preclinical AD. Highlights We examined plasma biomarker changes in cognitively normal individuals over 15.8 years. Apolipoprotein E (APOE) ε4 was related to lower amyloid beta (Aβ)42/Aβ40 and greater increases in phosphorylated tau (p‐tau)181 and glial fibrillary acidic protein (GFAP). In APOE ε4 non‐carriers, higher Alzheimer's disease (AD) polygenic risk score was related to greater Aβ42/Aβ40 declines. P‐tau181, NfL, and GFAP increases were greater among those who progressed to mild cognitive impairment. Results highlight the predictive value of plasma biomarkers during preclinical AD.

Objective The objective of this study was to examine the association between religious practices, beliefs, and cognitive impairment among Black and White men with modest incomes in the 2016 Health and Retirement Study. Methods Data were drawn from Black and White men who reported annual incomes at or below $50,000 ( n = 926). The primary outcome was any cognitive impairment, a dichotomous variable derived from a modified version of the Telephone Interview for Cognitive Status. The religious variables were religious service attendance, private prayer frequency, and religious beliefs. Results Results from regression models indicated that religious service attendance was inversely related with cognitive impairment among White men (PR = 0.64, CI: 0.48–0.87). Private prayer (PR = 0.67, CI: 0.47–0.97) and religious beliefs (PR = 0.91, CI: 0.84–1.00) were inversely related to cognitive impairment among Black men. Discussion Our results suggest that religious practices and beliefs may contribute to cognitive preservation among Black and White men, but longitudinal studies are needed to examine these associations further.

Background and objectives: People living with dementia experience progressive functional decline and increased dependence on caregivers. This study examined the influence of caregivers' dementia health literacy on perceptions of medical care preferences and advanced care planning (ACP) in people living with dementia. Research design and methods: This analysis used data from a cross-sectional survey, "Care Planning for Individuals with Dementia", administered nationwide by Alzheimer's Disease Centers. We conducted binary, ordinal, and multinomial logistic regression. Results: On average, surveyed caregivers (n=431) were 78.3 years, had 16 years of education, and were mainly white (88.5%). Most lived with (76.8%) and were the designated healthcare proxy (95.1%), with high dementia knowledge scores (mean=8.4/10). As caregivers' dementia knowledge scores increased, they were 1.27 times more likely (p=0.02) to endorse comfort care. Caregivers with greater knowledge about severe dementia were less likely to need further treatment preference-related discussions (knowing a lot: OR=0.17, p<0.001; knowing some things: OR=0.37, p=0.006). Caregivers live apart from patients were 2.71 times more likely to know about such discussions (p<0.001). Caregivers of people in earlier stages endorsed greater needs for further conversations with clinicians (no impairment & MCI: OR=7.38, p=0.002; mild impairment: OR=5.32, p=0.005) and their care recipients (no impairment & MCI: OR=5.24, p=0.02). Discussion and implications: These findings highlight the role of dementia-specific education in ACP discussions among people living with dementia, caregivers, and healthcare clinicians. These findings are important since evidence suggests that ACP may promote quality of life, reduce iatrogenic harm, minimize healthcare overutilization, and alleviate care-related burdens.

Background Cerebral metabolic rate of oxygen (CMRO2) denotes the amount of O2 that the brain consumes. Changes in CMRO2 during aging and neurodegeneration have not been fully characterized. Using a non‐invasive, non‐contrast MRI CMRO2 technique, the present study reports CMRO2 changes in older adults from a total of 526 measurements, the largest CMRO2 dataset to date. Method Experimental procedure: Analyses included 227 participants from the Biomarkers‐for‐Older‐Controls‐at‐Risk‐for‐Dementia (BIOCARD) cohort. Figure 1 shows the demographic information. Participants were categorized into 3 diagnostic categories: cognitively normal individuals who remained cognitively normal (n=187), individuals who progressed from normal cognition to Mild Cognitive Impairment (MCI) or dementia during follow‐up (n=13), and individuals with MCI/dementia at baseline (n=27). Participants were scanned on a 3T MRI (Philips) in a longitudinal study design. On average, participants had 2 scans (range = 1‐4) collected over 3.1 years of follow‐up. CMRO2 was estimated from the arterio‐venous difference in oxygen content, using a non‐invasive MRI technique. Data analysis: Linear mixed effect models were used to examine longitudinal changes in CMRO2 over time, as well as the effect of impairment (MCI/dementia) on CMRO2. Result In individuals who remained cognitively normal during follow‐up (Figure 2), there was an increase in CMRO2 over time (p<0.001), suggesting that the brain is “working harder” to compensate for its lower efficiency. However, the rate of increase in CMRO2 was attenuated among individuals with higher baseline ages (p=0.039). There were also main effects of baseline age (p=0.001) and sex (p=0.014), indicating lower CMRO2 levels among older than younger adults and among men than women. Next, we included participants who were cognitively impaired and those who progressed from normal cognition to cognitive impairment (Figure 3A). CMRO2 was lower among progressors and impaired participants than those who remained normal (p=0.001). There was an interaction effect between time and diagnosis category (p=0.044), indicating that participants who were impaired at baseline or progressed to impairment showed a different pattern of CMRO2 change over time compared to those who remained normal (Figure 3B). Conclusion CMRO2 revealed a non‐monotonic change in aging and cognitive impairment, suggesting a multi‐factorial and/or multi‐phase alteration of brain metabolism.

Background Blood‐based biomarkers of amyloid and tau have been shown to predict AD‐dementia risk. Much less is known about their ability to predict risk of Mild Cognitive Impairment (MCI) among cognitively normal individuals. It is also unclear how AD non‐specific blood markers of neurodegeneration and neuroinflammation predict MCI and whether they add predictive power above and beyond AD biomarkers. The current study examined whether levels of blood biomarkers of amyloid (Ab42/Ab40), tau (p‐tau181), neurodegeneration (NfL), and neuroinflammation (GFAP, YKL40, sTREM2) collected when participants were cognitively normal predict the time to onset of MCI, both alone and in combination. Method The plasma assays were based on the NeuroToolKit (cobas Elecsys assays, Roche Diagnostics) and obtained from 271 cognitively unimpaired BIOCARD Study participants at their initial baseline evaluation (mean age=57.5y, including 82 who progressed to MCI/dementia). A second ‘baseline’ specimen (collected using different procedures) was evaluated for a subset of participants who were cognitively normal ∼7 years later (N=202) (mean age = 64.5y), including 31 who later developed MCI/dementia, Table 1). Mean clinical follow‐up was 15.5 years for Baseline 1 and 9.9 years for ‘Baseline 2’. Cox regression models tested the association of biomarker levels with time to MCI symptom onset, separately for both baselines. Results For both baselines, lower levels of Ab42/Ab40, higher GFAP, and a higher ratio of p‐tau181/Ab42/Ab40were each associated with an earlier time to MCI symptom onset (p’s<=0.034, Table 2). For baseline 2, higher p‐tau181 (p=0.009) was also associated with earlier MCI symptom onset (p=0.009), and higher NfL was associated with earlier MCI symptom onset for progression within 7 years (p=0.05). When combining biomarkers, Ab42/Ab40 and p‐tau181 independently predicted progression (p’s <0.03), but neither GFAP nor NFL added predictive value after accounting for Ab42/Ab40 and p‐tau181. YKL40 and sTREM2 were not associated with MCI onset in any analyses. Conclusion This indicate that during preclinical AD, more abnormal blood biomarker levels of amyloid (Ab42/Ab40), tau (p‐tau181), neurodegeneration (NfL), and neuroinflammation (GFAP) individually predict progression from normal cognition to MCI, but that AD non‐specific neurodegeneration and inflammation do not improve prediction after accounting for amyloid and p‐tau levels.