Citations

AbstractBackgroundWe developed the Institute on Methods and Protocols for Advancement of Clinical Trials in ADRD (IMPACT‐AD) to address the shortage of qualified investigators with adequate training and expertise to conduct Alzheimer’s Disease (AD) and AD Related Dementias (ADRD) clinical trials.MethodWe describe the experience of the first two years of funding of the IMPACT‐AD course, specifically the rates of applications to the course, descriptive summaries of the accepted trainees, and the measures of participant satisfaction and learning.ResultOver the first two years of the course, we received 195 eligible applications to the course. Most (n = 121, 62%) applicants were female and nearly half self‐reported as being African American/Black, Asian, or Pacific Islander race and/or Hispanic/Latino ethnicity. Forty‐one applicants (21%) indicated that they were the first in their family to attend collegeOf 69 total trainees accepted to the course (36% acceptance rate), a majority (n = 44, 64%) were female. Twenty‐eight (41%) self‐reported as being African American/Black, Asian, or Pacific Islander race and eleven (16%) were of Hispanic ethnicity. Fourteen trainees (20%) identified as being the first person in their family to attend college. Among trainees, 24 (35%) were MDs, 30 (43%) were PhDs, and 9 (13%) held master’s degrees.Course lecture topics were rated, on average, as “essential” or “valuable” by 98% of trainees. Across lecture topics, on average, 48% of trainees rated their prior knowledge of topics as “very strong” or “strong,” and 11% of trainees rated their prior knowledge as “weak.” Overall, 52% of trainees evaluated their change in knowledge based on the lectures as “very much increased,” 46% as “somewhat” or “slightly” increased, and 2% as “no change.” Results were similar for the two tracks. Based on pre‐ and post‐course assessments, trainees improved their knowledge of covered content (from 62% to 79% correct responses on knowledge assessments).ConclusionThe IMPACT‐AD course is achieving its mission of educating and diversifying the next generation of ADRD trialists.We thank Dr. Laurie Ryan and Dr. Kristina McLinden from the National Institute on Aging for their key contributions in leadership and scientific guidance of IMPACT‐AD.

AbstractBackgroundSeveral hypotheses exist regarding the neurologic substrate underlying visual hallucinations (VH) in Dementia with Lewy Bodies (DLB). Studies have suggested an association with regional cerebral hypometabolism in the primary visual or visual association cortices on FDG‐PET. We compared regional cerebral glucose metabolism and posterior cingulate island sign (CIS) ratios in DLB and in Mild Cognitive Impairment with Lewy Bodies (MCI‐LB) participants with (VH+) and without (VH‐) VH.MethodParticipants with clinically probable DLB or MCI‐LB and an FDG‐PET scan were identified from the Mayo ADRC database. Responses on the Visual Hallucinations and Delusions Questionnaire and Neuropsychiatric Inventory were used to assess presence or absence of VH. Standardized uptake value ratios (SUVr) were used to calculate regional cerebral glucose hypometabolism in the primary visual cortex (PVC), lateral occipital cortex (LOC), and whole occipital cortex (WOC). The CIS ratio was defined as posterior cingulate divided by the sum of the precuneus plus cuneus FDG‐PET uptake ratio.ResultTwo cohorts were identified (27 DLB and 18 MCI‐LB, 87% male). Eighteen DLB participants were VH+ and 9 were VH‐, whereas 5 MCI‐LB were VH+ and 13 were VH‐. There were no statistically significant differences in demographic (age, sex, education) and clinical features (MoCA, CDR, presence of other core DLB features, and UPDRS) between VH+ vs VH‐ in those with DLB, and between VH+ vs VH‐ in those with MCI‐LB. Similarly, there were no statistically significant differences in DLB between VH+ vs VH‐ in PVC (1.55±0.14 vs 1.58±0.15), LOC (1.22±0.16 vs 1.28±0.12), WOC (1.29±0.15 vs 1.34±0.11), or CIS ratio (1.16±0.08 vs 1.14±0.10), nor in MCI‐LB between VH+ vs VH‐ in PVC (1.68±0.19 vs 1.58±0.14), LOC (1.40±0.21 vs 1.32±0.14), WOC (1.45±0.20 vs 1.37±0.14), or CIS ratio (1.17±0.08 vs 1.19±0.10) (P>0.05 for all comparisons).ConclusionThese findings do not support a direct correlation between regional cerebral glucose metabolism and VH in DLB or MCI‐LB. Further work in DLB and MCI‐LB with larger numbers is warranted. Other neurologic substrates and mechanisms, such as REM sleep intrusions during wakefulness, neurotransmitter dysfunction, and disruption of functional connectivity across brain regions should be explored as contributors to VH in DLB.

AbstractBackgroundREM Sleep Behavior Disorder (RBD) is a prodromal marker of α‐synucleinopathies with no standardized tool for assessing severity in clinical or research practice. RBD severity may have implications in measuring risk of phenoconversion, monitoring response to treatment and clinical trial design. This study assessed the validity of the RBD symptom severity scale (RBDSSS) and its correlation to the clinical global impression of severity (CGI‐S) in a cohort of participants enrolled in the North American Prodromal Synucleinopathy (NAPS) Consortium.MethodParticipants and their bedpartners enrolled in the NAPS cohort filled out an 8‐item questionnaire, developed by the International RBD Study Group, assessing frequency and severity of dreams, vocalizations, movements, and injuries associated with RBD, with higher scores indicating more severe symptoms. The CGI‐S is a 7‐point scale ranging from normal (1) to most severely ill (7) and was completed by a clinician based on an independent interview with the participant ± their bedpartners. Total scores for participant (RBDSSS‐PT) and bed partner (RBDSSS‐BP) questionnaires were derived by multiplying frequency and severity scores for each feature, then summing the products for possible maximum scores of 54 and 38 respectively.ResultThis cohort (n = 212) was predominantly male (82.5%) with a mean ± SE age of 65.16 ± 1.46 years. The median (interquartile range) for RBDSSS‐PT, RBDSSS‐BP and CGI‐S was 11 (4‐17), 8 (4‐14.3) and 3 (3‐4), respectively. Spearman’s rank correlation coefficients (rs) were as follows: RBDSSS‐PT vs. RBDSSS‐BP, rs = 0.579; RBDSSS‐PT vs. CGI‐S, rs = 0.642; RBDSSS‐BP vs. CGI‐S, rs = 0.487 (all P<0.0001). RBDSSS‐BP scores were significantly lower in women (6 vs. 9, Chi‐Square p = 0.009) while there were no differences in RBDSSS‐PT scores by sex. (9 vs. 11, p = 0.473).ConclusionA moderate correlation was observed between RBDSSS‐PT and RBDSSS‐BP suggesting good construct validity for the scale. CGI‐S correlated most with RBDSSS‐PT and had a weaker association with RBDSSS‐BP. Women had lower severity scores as reported by bed partners unlike their self‐reported scores, indicating possible sex differences in perceived RBD severity.

AbstractBackgroundMayo Test Drive (MTD): Test Development through Rapid Iteration, Validation and Expansion, is a web‐based platform optimized for remote self‐administered assessment that includes a computer adaptive word list memory test (Stricker Learning Span; SLS) and a measure of processing speed (Symbols Test). Study aims were to determine 1) convergent validity of MTD through correlations with in‐person neuropsychological measures and 2) criterion validity of MTD by qualitatively comparing the ability of Mayo Test Drive and in‐person administered neuropsychological measures to differentiate biomarker‐defined groups, independent of clinical diagnosis.MethodsMayo Clinic Study of Aging participants (N = 282) completed a brief remote cognitive assessment (mean age = 74, SD = 12; 262 CU and 20 MCI per consensus conference diagnosis; see Table 1). A subset of participants had brain amyloid and/or brain tau PET scans available within 3 years; overlapping groups were formed for 1) those on the Alzheimer’s disease (AD) continuum (A+, n = 31) or not (A‐, n = 57) and for 2) those with biological AD (A+T+, n = 19) or without any AD biomarkers (A‐T‐, n = 47). Primary outcome variables were SLS sum of trials, AVLT sum of trials, SYM Correct Trials response time, Digit Symbol Coding, MTD composite and Mayo‐PACC (AVLT sum of trials, Trails B, animals). Bivariate correlations were performed across all participants. Linear model ANOVAs were used to investigate biomarker subgroup differences; Hedge’s g effect sizes are reported.ResultsConvergent validity was supported through significant correlation (p’s < .001) of SLS and AVLT (r = .63), SYM and Coding (r = ‐.64), and MTD composite with Mayo‐PACC (r = .67); see Table 2. MTD subtests showed expected relationships with age and education (p’s < .05; Table 3). All MTD performances were significantly lower for A+ and A+T+ participants relative to A‐ or A‐T‐ (p’s<.001; Table 4). All MTD outcome measures showed a similar or greater group difference effect size relative to traditional in‐person administered neuropsychological measures for separating A+ vs. A‐ and A+T+ vs. A‐T‐ groups. See Figure 1 and Table 4.ConclusionsMTD subtests show evidence of convergent validity through strong correlations with traditional in‐person cognitive measures. Preliminary analyses suggest MTD has promise for differentiating PET biomarker groups.

AbstractBackgroundRemote assessment tools offer significant promise for aiding early detection of cognitive impairment. Mayo Test Drive (MTD): Test Development through Rapid Iteration, Validation and Expansion, is a web‐based platform for remote self‐administered assessment that includes a computer adaptive word list memory test (Stricker Learning Span; SLS) and a measure of processing speed (Symbols Test). We examined the diagnostic accuracy of the SLS and a MTD composite (SLS max span, SLS trials 1–5 total correct, SLS delay correct, [Symbols correct item response time*‐1]) for amnestic mild cognitive impairment (aMCI). We also explored diagnostic accuracy for a broader group that included individuals with possible MCI (pMCI; see Figure 1).MethodsParticipants were recruited from the Mayo Clinic Study of Aging for this ancillary remote study. 226 were cognitively unimpaired (CU; concordant CU diagnosis by 3 independent raters). Fifty‐six participants had possible MCI (at least 1 of 3 raters indicated MCI) and 16 had a consensus diagnosis of aMCI. Primary outcome variables were SLS sum of trials, AVLT sum of trials, Symbols correct items response time, and MTD composite. Mean difference analyses used linear model ANOVAs (alpha = .05). Receiver operating characteristic (ROC) curves were applied; we derived optimal cutoff scores based on the Youden index method.ResultsBoth aMCI and possible MCI groups showed significantly lower performance than the CU group on SLS (Hedge’s g aMCI = ‐1.72, pMCI = ‐1.04), Symbols (Hedge’s g aMCI = 1.38, pMCI = 0.64), and MTD composite (Hedge’s g aMCI = ‐1.89, pMCI = ‐1.09); see Tables 1 and 2 (all p‘s<.01 even when additionally covarying age, education, sex). Total area under the curve was high for differentiating of CU vs. aMCI (MTD Composite = 0.91, SLS = 0.91) and acceptable for CU vs. pMCI (MTD Composite = 0.77, SLS = 0.77); see Table 2. Consistent with our flexible platform, a variety of device types were used to complete remote testing (32% smartphone, 12% tablet, 56% PC).ConclusionsMTD and the SLS show high diagnostic accuracy for aMCI. MTD is a flexible, brief, and easy‐to‐use remote cognitive assessment tool with great potential for scalable use in future studies seeking to maximize inclusion of individuals with aMCI in clinical trials or for cognitive screening in clinical settings.

AbstractBackgroundMayo Test Drive (MTD): Test Development through Rapid Iteration, Validation and Expansion, is a web‐based platform for self‐administered assessment for novel (Stricker Learning Span) and open access (Symbols Test) cognitive measures with previously demonstrated validity and reliability. Our study aim was to examine the usability of MTD, defined as the extent to which MTD was used to achieve the desired study goal of completing a testing session among participants willing to engage in an all‐remote study.Methods248 Mayo Clinic Study of Aging and Mayo Alzheimer’s Disease Research Center participants were invited to participate in this ancillary, uncompensated remote pilot study via email. To examine 1) willingness to participate in a remote cognitive assessment study and 2) usability of MTD, the initiation and completion rates of MTD were examined by cognitively unimpaired (CU; n = 142) and cognitively impaired (CI; n = 106) groups (see Figure 1). These rates and other factors associated with MTD feasibility were further explored across age in CU (i.e., 50–69, 70–79, and 80+ years) and specific diagnostic groups in CI (i.e., individuals with dementia, mild cognitive impairment (MCI), and possible MCI).ResultsSession completion rate (usability) was 98% across all participants who chose to participate, and, surprisingly, completion rates did not vary by age or diagnostic groups (p = .69; see Table 1). As expected, more individuals chose to participate in the CU (77%) versus CI (52%) group (p < .001). In terms of feasibility, individuals over 80 and with CI were more likely to have some contact with the study coordinator. Use of smartphones decreased with age, with most CU individuals over 70 using a personal computer (69‐73%; Table 2).ConclusionsThough the CI group was less likely to choose to participate than the CU group, out of those that did choose to participate the rate of completion was 98%. This demonstrates high usability of MTD. Study coordinator support and a flexible testing platform is critical for facilitating participation in remote testing across the aging population, and more supports and incentives may be needed for individuals with cognitive impairment to improve participation rates.

AbstractBackgroundDyadic (self and study partner) subjective reports of an individual’s recent cognitive and functional decline are an efficient approach to facilitate identification of older adults with, and at risk for, Mild Cognitive Impairment (MCI). Such methods can be easily adapted for remote administration, but few studies have investigated the ability of remotely‐collected, unsupervised dyadic subjective reports to accurately detect MCI and cognitive decline.MethodsIn 289 older adults enrolled in the Brain health Registry (BHR), with clinically‐confirmed diagnoses of Cognitively‐unimpaired (CU) or MCI, we identified the optimal combination of remote measures to accurately distinguish CU from MCI. We then externally validated our predictive model in 217 participants enrolled in a separate cohort, Validation of Online Methods to Predict Cognitive Decline (eVAL). Predictors included Cogstate Brief Battery One Card Learning (OCL) accuracy; self‐ and study partner‐reported memory concern (SMCs); performance on online adaptations of Everyday Cognition Scale (ECog, self‐ and study partner‐report versions), Geriatric Depression Scale Short Form (GDS); family history of AD, age, gender, and education. We calculated 10‐fold cross validated area under the ROC curves (cvAUC), 95% confidence intervals (CI), and the percentage of participants correctly classified (accuracy) for all models. Likelihood ratio (LR) tests were used to compare model fits.ResultsIn the BHR cohort, models including dyad‐report ECog, family history of AD, GDS, and Cogstate OCL scores distinguished CU from MCI with the highest accuracy (cvAUC = 0.90; 95% CI = 0.83, 0.92; accuracy = 85.5%). Models excluding study partner‐report ECog distinguished diagnostic groups with moderate accuracy (cvAUC = 0.83; 95% CI = 0.78, 0.85; accuracy = 75.9%) When applied to the validation cohort, the optimal training model including dyadic report performed with moderate accuracy ( Table 2 ). In the validation cohort, inclusion of study partner (but not self) report SMC, in addition to dyadic‐report ECog, improved model fit (LR test p<0.01).ConclusionsRemotely‐collected dyadic subjective measures, along with other remote measures, accurately distinguish CU from MCI. Subjective cognitive and functional decline and concerns about memory problems independently contribute to diagnostic discrimination. Results support future utilization of remote dyadic subjective measures to efficiently identify older adults with MCI for prodromal AD clinical trials, and in clinical care settings.

AbstractBackgroundSlow walking speed is associated with numerous negative health outcomes including global cognitive decline.1 More detailed gait analysis can differentiate among different dementia subtypes,10 but the predictive power of baseline gait metrics for domain‐specific cognitive decline needs further characterization.MethodWe conducted a follow up study on 534 participants of the Mayo Clinic Study of Aging who underwent evaluations every 15 months (median follow‐up = 5.4 years). We analyzed quantitative gait metrics, acquired with a pressure‐sensing walkway (GAITRite® instrument), and cognitive scores using a linear mixed effects model to identify correlations between z‐scored baseline gait metrics (cadence, swing time, stance time, velocity, double support time (DST), stride length, stride length standard deviation (SD), stride time SD, swing time SD, stance time SD, DST SD) and cognitive domain z‐scores (memory, attention, language, visuospatial, global) at baseline and over time. Models controlled for age, sex, and probable REM sleep behavior disorder at baseline.ResultThe table includes both baseline associations and difference in slopes (Δ), relative to the average person, in cognitive domains. These slopes ranged from about ‐0.05 for visuospatial to ‐0.12 for attention.ConclusionIncreased gait velocity and stride length are associated with less severe domain‐specific and global cognitive decline while increased swing time SD and DST are associated with more severe rates of decline in some domains. These findings suggest that baseline gait characteristics could be a helpful predictor of future cognitive changes.References:1. Savica R, Wennberg AMV, Hagen C, et al. Comparison of Gait Parameters for Predicting Cognitive Decline: The Mayo Clinic Study of Aging. Journal of Alzheimer's disease : JAD. 2017;55(2):559. doi:10.3233/JAD‐1606972. Mc Ardle R, del Din S, Galna B, Thomas A, Rochester L. Differentiating dementia disease subtypes with gait analysis: feasibility of wearable sensors? Gait & Posture. 2020;76:372–376. doi:10.1016/j.gaitpost.2019.12.028

AbstractBackgroundWe previously demonstrated that Alzheimer’s disease (AD) patients ≥70 y/o tend to have smaller medial temporal volumes in the presence of relatively less medial temporal 18F‐flortaucipir‐PET uptake compared to young AD patients. TAR DNA‐binding protein 43 (TDP‐43) is frequently found in the brains of AD patients and is associated with old age and medial temporal atrophy. In this study, we aimed to determine whether TDP‐43 could be contributing to the mismatch between medial temporal volumes and flortaucipir‐PET uptake in older AD patients.MethodWe identified 77 participants (median age at death 79 years [range: 51‐99]) who had been enrolled into the Mayo Clinic Alzheimer’s Disease Research Center or Neurodegenerative Research Group (NRG), had undergone flortaucipir‐PET and volumetric MRI scans close to death, and autopsy confirmed AD neuropathological changes, as well as TDP‐43 assessments. Grey matter volumes and flortaucipir standard uptake value ratios (SUVRs) were calculated for hippocampus, amygdala, entorhinal, inferior temporal, and midfrontal cortices. We used bivariate‐response linear regression modelling, adjusting for Braak neurofibrillary tangle stage, to estimate the effect of TDP‐43 and age on gray matter volume and flortaucipir uptake, and tested whether TDP‐43 effect sizes varied according to age.ResultAfter accounting for Braak stage, older individuals tended to have significantly lower flortaucipir uptake across regions and lower hippocampal and entorhinal cortex (ERC) volumes. TDP‐43 was associated with reduced hippocampus and ERC volumes but was unrelated to flortaucipir SUVRs (Figure 1). Notably, the TDP‐43 effect size for the hippocampus and ERC was largely consistent across age, i.e., at any age, TDP‐43‐positive participants had significantly smaller hippocampal (∼12% decrease) and ERC (13% decrease) volumes than TDP‐43‐negative participants. However, at older ages, the mean volumes in the whole cohort and, more evidently, in those with dementia moved closer towards the mean of those with TDP‐43 (Figure 1), likely attributable to the increasing frequency of TDP‐43 with age.ConclusionTDP‐43 is a major contributor to the mismatch between flortaucipir uptake and medial temporal lobe volumes in older AD patients where lower medial temporal regional volumes are observed in the presence of less flortaucipir uptake.

AbstractBackgroundTDP‐43 is a nuclear RNA‐binding protein involved in various neurodegenerative diseases, including Alzheimer’s Disease (AD), and normal aging. It strongly affects cognition and memory loss in AD. Concomitant TDP‐43 pathology increases the likelihood of being cognitively impaired at death.MethodMayo Clinic has amassed a large database with 1072 study participants with known TDP‐43 pathology status, who were prospectively recruited and followed in the Mayo Clinic Alzheimer’s Disease Research Center, Mayo Clinic Study of Aging, and Neurodegenerative Research Group. All underwent neurologic, genetic, and neuropathologic evaluations. Amygdala sections immunostained with antibodies against TDP‐43 were screened for TDP‐43‐immunoreactive inclusions and successively staged using the Josephs staging scheme. The frequency of TDP‐43 pathology by age at death was estimated using logistic regression with age modelled using a restricted cubic spline. Models were fit for all cases including the subset of 581 cases with dementia.ResultOur cohort was predominantly White (99%) with median age at death of 87 years (IQR: 80‐92) and relatively even sex distribution (52% female). About 55% had Braak stage V‐VI and 61% had Thal amyloid phase ≥3. Fifty‐two percent met criteria for intermediate‐high probability AD. TDP‐43‐immunoreactivity (TDP‐43+) was detected in 44% with median TDP‐43 stage of 3 (IQR: 1‐5), and in 54% with a median stage of 3 (IQR: 2‐5) in those with dementia. TDP‐43+ frequency increased approximately linearly with age at death. At 70 years at death, an estimated 30% (95% CI: 25–35) of the cohort was TDP‐43+ versus 33% (CI: 27–40) of those with dementia. By 90 years at death, 49% (CI: 45–52) of the overall cohort and 68% (CI:62‐73) of those with dementia were TDP‐43+.ConclusionThe results from our large cohort confirm that TDP‐43 pathology frequency increases in elderly White study participants with age of death, independent of cognitive status. Furthermore, TDP‐43 pathology frequency increases to a greater degree with age in those with dementia. Given the clear links between TDP‐43 and impaired cognition, the contribution of TDP‐43 to an individual’s cognitive impairment is likely to increase with age; a dynamic with significant public health consequences given our aging population.