Knopman, David S.

AbstractINTRODUCTIONWe examined associations between plasma‐derived biomarkers of Alzheimer's disease (AD) and neuropsychiatric symptoms (NPS) in community‐dwelling older adults.METHODSCross‐sectional study involving 1005 persons ≥50 years of age (mean 74 years, 564 male, 118 cognitively impaired), who completed plasma‐derived biomarker (amyloid beta 42 [Aβ42]/Aβ40, phosphorylated tau 181 [p‐tau181], p‐tau217, total tau [t‐tau], neurofilament light [NfL]), and NPS assessment.RESULTSP‐tau181 (odds ratio [OR] 2.06, 95% confidence interval [CI] 1.41–3.00, p < 0.001), p‐tau217 (OR 1.70, 95% CI 1.10–2.61, p = 0.016), and t‐tau (OR 1.44, 95% CI 1.08–1.92, p = 0.012) were associated with appetite change. We also found that p‐tau181 and p‐tau217 were associated with increased symptoms of agitation (OR 1.93, 95% CI 1.20–3.11, p = 0.007 and OR 2.04, 95% CI 1.21–3.42, p = 0.007, respectively), and disinhibition (OR 2.39, 95% CI 1.45–3.93, p = 0.001 and OR 2.30, 95% CI 1.33–3.98, p = 0.003, respectively). Aβ42/Aβ40 and NfL were not associated with NPS.CONCLUSIONHigher plasma‐derived p‐tau181 and p‐tau217 levels are associated with increased symptoms of appetite change, agitation, and disinhibition. These findings may support the validity of plasma tau biomarkers for predicting behavioral symptoms that often accompany cognitive impairment.HIGHLIGHTS We studied 1005 community‐dwelling persons aged ≥ 50 years Higher plasma tau levels are associated with increased neuropsychiatric symptoms Aβ42/Aβ40 and NfL are not associated with neuropsychiatric symptoms Clinicians should treat neuropsychiatric symptoms in persons with high plasma‐derived tau

Abstract Background Hearing loss is a risk factor for dementia; whether the association is causal or due to a shared pathology is unknown. We estimated the association of brain β-amyloid with hearing, hypothesizing no association. As a positive control, we quantified the association of hearing loss with neurocognitive test performance. Methods Cross-sectional analysis of Atherosclerosis Risk in Communities-Positron Emission Tomography study data. Amyloid was measured using global cortical and temporal lobe standardized uptake value ratios (SUVRs) calculated from florbetapir-positron emission tomography scans. Composite global and domain-specific cognitive scores were created from 10 neurocognitive tests. Hearing was measured using an average of better-ear air conduction thresholds (0.5–4 kHz). Multivariable-adjusted linear regression estimated mean differences in hearing by amyloid and mean differences in cognitive scores by hearing, stratified by race. Results In 252 dementia-free adults (72–92 years, 37% Black race, and 61% female participants), cortical or temporal lobe SUVR was not associated with hearing (models adjusted for age, sex, education, and APOE ε4). Each 10 dB HL increase in hearing loss was associated with a 0.134 standard deviation lower mean global cognitive factor score (95% CI: −0.248, −0.019), after adjustment for demographic and cardiovascular factors. Observed hearing-cognition associations were stronger in Black versus White participants. Conclusions Amyloid is not associated with hearing, suggesting that pathways linking hearing and cognition are independent of this pathognomonic Alzheimer’s-related brain change. This is the first study to show that the impact of hearing loss on cognition may be stronger in Black versus White adults.

AbstractBackgroundHigher brain amyloid PET is associated with slower gait speed and has been hypothesized to play a role in age‐related mobility decline. With the development of blood‐based biomarkers of Alzheimer’s disease pathology, we examined whether plasma levels of amyloid‐beta (Aβ)40, Aβ42, the Aβ42/Aβ40 ratio, phosphorylated tau 181 (p‐tau181) and 217 (p‐tau217), total tau, and neurofilament light chain (NfL) were associated with gait speed.MethodThis study included 779 cognitively unimpaired participants (median age 75, 54.8% male, median follow‐up 6.8 years) in the Mayo Clinic Study of Aging with concurrent measurement of plasma biomarkers and gait speed. Individuals with chronic kidney disease or a history of stroke were excluded. The plasma markers (pg/mL) were measured on the Quanterix Simoa® HD‐1 analyzer (total tau, Aβ42, Aβ40, NfL) and the Meso Scale Discovery platform (p‐tau181, p‐tau217). Gait speed (m/s) was obtained by timing a self‐paced walk across 25 ft using a stopwatch. Linear mixed effects models, with subject‐specific intercepts and slopes for time since baseline, with z‐scored baseline plasma markers were used to predict cross‐sectional and longitudinal gait speed. All models adjusted for baseline age and sex.ResultAt baseline, higher Aβ42 [Beta = ‐0.019; 95%CI = (‐0.035, ‐0.004)], total‐tau [‐0.026; (‐0.041, ‐0.011)], and p‐tau181 [‐0.021; (‐0.036, ‐0.006)] were associated with slower gait speed. Gait speed decreased, on average, by about 0.015 m/s annually for those in this study. Each one standard deviation (SD) increase in baseline level of plasma Aβ40 [‐0.005; (‐0.007, ‐0.002)], NfL [‐0.006; (‐0.009, ‐0.004)], and p‐tau217 [‐0.004; (‐0.007, ‐0.001)] accelerated this decline over time. In contrast, each one SD increase in Aβ42/Aβ40 ratio [0.003; (0.001, 0.006)] mitigated decline. Additional analyses adjusting for Charlson comorbidity index, Beck Depression Inventory, body mass index, and APOE E4 allele status gave similar results.ConclusionBoth cross‐sectional and longitudinal associations of plasma markers of amyloid and tau pathology and neurodegeneration with gait speed among cognitively unimpaired individuals were present. Therefore, not only are these markers of cognitive changes, they are also related to motor changes such as those affecting gait speed.

AbstractBackgroundTwo pathways that help explain cognitive health are 1) brain maintenance – referring to the relative absence of brain changes over time; 2) cognitive reserve – a property of the brain that allows for sustained cognitive ability in the presence of brain pathology. Both pathways influence cognitive aging and are best understood using longitudinal data. Our goal was to assess the effect of modifiable vascular/metabolic and lifestyle enrichment factors on these pathways using longitudinal brain changes measured on structural magnetic resonance imaging (MRI) and longitudinal cognitive decline. Lastly, we combined these pathways and their relationships in the same model.MethodWe identified 1250 participants from a well‐characterized sample of older adults from the Mayo Clinic Study of Aging with both longitudinal MRI and cognitive data. Linear mixed models were performed to assess the impact of modifiable factors on brain maintenance and cognitive reserve. Latent growth curve models (SEM) were used to assess the impact of brain structure and cognitive reserve on longitudinal cognition.ResultThe mean age of our sample was 78.8 years, with 45.4% female, and 27.1% APOE4 carriers. Mean follow‐up time was 4.0 years with a mean of 3.2 MRI scans per participant. Linear mixed models showed that poorer vascular/metabolic health (presence of vascular/metabolic conditions) was associated with lower cross‐sectional temporal region cortical thickness (‐0.014 (0.003), p<0.001) and lower global cognition (‐0.042 (0.018), p = 0.024). Higher estimated cognitive reserve at baseline as assessed by education/occupation composite (0.103 (0.01), p<0.001) was associated with higher global cognition. Unexpectedly, late‐life physical activities were related to lower global cognition (‐0.05 (0.007), p = 0.004). Our final latent growth curve SEM fit the data well showing temporal associations between unmodifiable characteristics, cognitive reserve, and brain structural pathways, as well as the influence of modifiable vascular/metabolic factors.ConclusionWe found that brain maintenance and cognitive reserve pathways were related to better cognition over time. We further showed that vascular/metabolic health impacts long‐term cognitive outcomes (i.e. cognitive aging) primarily through the brain maintenance pathway. These data provide a modeling scheme for future studies and can aid in assessing the pathways by which individual factors may influence cognitive aging.

AbstractBackgroundPreclinical Alzheimer’s cognitive composites (PACC) are designed to detect subtle cognitive changes in clinical trials. PACCs often include measures of memory, attention, and semantic fluency, with variations based on available measures. We created a Mayo Clinic PACC (Mayo‐PACC) to address limitations of existing PACCs by prioritizing parsimony, non‐proprietary measures, clinical applicability, and psychometric properties. We developed a Mayo‐PACC and examined sensitivity to detecting longitudinal cognitive change in amyloid positive (A+) older adults relative to the Preclinical Alzheimer’s Cognitive Composite‐Revised (PACC‐R). Exploratory analyses included comparison to other composites.MethodParticipants included 614 individuals in the Mayo Clinic Study of Aging (428 A‐ and 186 A+) age 65‐85 who were cognitively unimpaired at baseline with 7 years mean follow‐up. A+ was defined as PiB‐PET meta‐ROI SUVR ≥ 1.48 (centiloid 22). The Mayo‐PACC included the AVLT sum of trials (trials 1‐5, short delay, long delay), Trails B and Animal fluency. Measures included in the PACC‐R and other comparison composites are listed in Table 1. We calculated study‐specific z‐scores and examined psychometric properties of component measures including test‐retest reliability, practice effects, and distributional properties (ceiling/floor effects, skew, kurtosis). We examined sensitivity to preclinical cognitive change using slope estimates (difference in annualized change across A+ and A‐ groups) from linear mixed models (LMMs) for each composite. A jackknife procedure was used to calculate the standard error and subsequent confidence intervals of differences in rates of change (A+>A‐ indicating more significant decline in A+). Significance was determined based on whether the 95% Confidence Interval (CI) contained 0 (alpha = .05).ResultAll composites showed sensitivity to amyloid‐related longitudinal cognitive decline (A+>A‐ annualized change p<.05; see Table 2). Jack‐knife comparisons revealed comparable utility of Mayo‐PACC and PACC‐R (CI contained 0, see Table 3). Exploratory analyses revealed Mayo‐PACC performed similarly to an adaptation of the ADCS‐PACC, Global‐z, Memory‐z and Attention‐z. The Mayo‐PACC performed better than a 2‐measure Mayo‐PACC‐remote and a single memory measure.ConclusionThe Mayo‐PACC provides a parsimonious composite score that has comparable utility for detecting A+>A‐ cognitive decline compared to the PACC‐R and other composites and can be widely used in both research and clinical settings.

e24089 Background: Little is known about risk and protective factors for dementia in cancer survivors. With increasing longevity due to improved cancer therapy, it’s prudent to study factors contributing to cognitive impairment in this patient population. Methods: We performed multivariable cox regression analyses to assess established risk factors for all-cause dementia (age, education, APOE4-status, social and physical activity engagement) in breast and prostate cancer survivors. Patients 50+ years old with pathology-confirmed cancer diagnosis at Mayo Clinic were identified from a longitudinal, population-based cohort – Mayo Clinic Study of Aging. Analyses were controlled for age, APOE4-status, education, and cancer treatment. Results: We included a total of 209 patients with breast cancer (mean age 75.4 years, 24% APOE4-positive, median follow-up 6.8 years) and 352 with prostate cancer (mean age 77 years, 26% APOE4-positive, median follow-up 6.4 years). 31 patients with breast cancer (15%) and 66 patients with prostate cancer (20%) were diagnosed with dementia at last follow-up. Older age was associated with increased risk for dementia (5-year increase – breast: hazard ratio (HR) 1.9 [95%CI 1.3-2.7, p = 0.001]; prostate: HR 2.4 [95%CI 1.8-3.2, p < 0.0001]). APOE4-positivity was associated with increased dementia risk in breast (HR 3.6 [95%CI 1.6-7.8, p < 0.002]), but not prostate cancer (HR 1.2 [95%CI 0.7-2.0, p = 0.5]). More education was associated with lower dementia risk in prostate cancer (education year: HR 0.91 [95%CI 0.84-0.98, p < 0.02]; education years > 12: HR 0.26 [95%CI 0.1-0.6, p < 0.001]). Physical activity engagement in mid-life was associated with lower dementia risk (prostate: HR 0.56 [95%CI 0.4-0.8, p < 0.005]; breast: HR 0.48 [95%CI 0.3-0.9, p < 0.02]). Conclusions: In this longitudinal, population-based study we found that some risk and protective factors for dementia in cancer survivors vary by cancer type. While advanced age is an expected dementia risk factor, there were mixed results for APOE4-positivity (increased risk only in breast cancer) and education (only protective in prostate cancer). Our results support further study into factors influencing dementia risk by cancer type in hopes of identifying preventative strategies.

Abstract Blood-based biomarkers offer strong potential to revolutionize diagnosis, trial enrolment and treatment monitoring in Alzheimer’s disease (AD). However, further advances are needed before these biomarkers can achieve wider deployment beyond selective research studies and specialty memory clinics, including the development of frameworks for optimal interpretation of biomarker profiles. We hypothesized that integrating Alzheimer’s disease genetic risk score (AD-GRS) data would enhance the diagnostic value of plasma AD biomarkers by better capturing extant disease heterogeneity. Analysing 962 individuals from a population-based sample, we observed that an AD-GRS was independently associated with amyloid PET levels (an early marker of AD pathophysiology) over and above APOE ε4 or plasma p-tau181, amyloid-β42/40, glial fibrillary acidic protein or neurofilament light chain. Among individuals with a high or moderately high plasma p-tau181, integrating AD-GRS data significantly improved classification accuracy of amyloid PET positivity, including the finding that the combination of a high AD-GRS and high plasma p-tau181 outperformed p-tau181 alone in classifying amyloid PET positivity (88% versus 68%; P = 0.001). A machine learning approach incorporating plasma biomarkers, demographics and the AD-GRS was highly accurate in predicting amyloid PET levels (90% training set; 89% test set) and Shapley value analyses (an explainer method based in cooperative game theory) indicated that the AD-GRS and plasma biomarkers had differential importance in explaining amyloid deposition across individuals. Polygenic risk for AD dementia appears to account for a unique portion of disease heterogeneity, which could non-invasively enhance the interpretation of blood-based AD biomarker profiles in the population.