Lundt, Emily S.

AbstractIntroductionThis study evaluated the diagnostic accuracy of the Cogstate Brief Battery (CBB) for mild cognitive impairment (MCI) and prodromal Alzheimer's disease (AD) in a population‐based sample.MethodsParticipants included adults ages 50+ classified as cognitively unimpaired (CU, n = 2866) or MCI (n = 226), and a subset with amyloid (A) and tau (T) positron emission tomography who were AD biomarker negative (A–T–) or had prodromal AD (A+T+).ResultsDiagnostic accuracy of the Learning/Working Memory Composite (Lrn/WM) for discriminating all CU and MCI was moderate (area under the curve [AUC] = 0.75), but improved when discriminating CU A–T– and MCI A+T+ (AUC = 0.93) and when differentiating MCI participants without AD biomarkers from those with prodromal AD (AUC = 0.86). Conventional cut‐offs yielded lower than expected sensitivity for both MCI (38%) and prodromal AD (73%).DiscussionClinical utility of the CBB for detecting MCI in a population‐based sample is lower than expected. Caution is needed when using currently available CBB normative data for clinical interpretation.

AbstractBackgroundPractice effects can obscure interpretation of longitudinal cognitive performance. Reliable change indices (RCIs) provide data for determining a significant change, typically for a single repeat assessment, but multiple follow‐up visits are common clinically and in research cohorts. Further, regression‐based or linear mixed effects models improve prediction of future cognitive decline and have higher correlations with neuroimaging biomarkers than RCI approaches. We present norms for change for the Auditory Verbal Learning Tests (AVLT) with conditional normative z‐scores for up to 7 repeat assessments, and demonstrate application of this method to individuals with preclinical Alzheimer’s disease (AD).MethodNormative Sample: Robust conditional norms were derived from 1001 adults ages 50‐90 from the Mayo Clinic Study of Aging (MCSA) who completed the AVLT across 4‐8 visits approximately 15 months apart and remained cognitively unimpaired (CU) across all available visits. Linear mixed effects models were used to compute a conditional normative z‐score for AVLT 30‐minute recall and sum of trials. Models included adjustment for baseline performance, number of prior test exposures, demographic factors (age, sex, education), and interactions (baseline*time; sex*time). Test Sample: We used a preclinical AD sample with positive amyloid and tau imaging (n= 27 CU A+T+; Jack et al. 2017) expected to have a higher rate of intra‐individual cognitive decline relative to CU A‐T‐ individuals (n = 268) to compare mean performances of conditional normative z‐scores to typical age‐corrected Mayo’s Older Americans Normative Studies (MOANS) norms. Participants had at least 1 and up to 4 follow‐up visits, with their most recent AT data used for classification.ResultAVLT performance based on typical norms did not differ across A+T+ and A‐T‐ groups. Specifically, across 2‐4 follow‐up visits, the typical norms mean z‐score was similar across groups (p=0.945; see Table 1). However, the conditional norms mean z‐score that accounts for practice effects and typical trajectories of AVLT performance was lower in the A+T+ relative to the A‐T‐ group for 30‐minute recall (p=0.055) and sum of trials (p=0.060).ConclusionConditional normative methods that account for practice effects are more sensitive to preclinical AD than typical norms, and show promise for identifying transitional cognitive decline.

AbstractBackgroundThe numeric clinical staging scheme described by the NIA‐AA workgroup proposes evidence of subtle decline on longitudinal cognitive testing as one option to define transitional cognitive decline for individuals in the Alzheimer’s continuum. Few studies have compared longitudinal and cross‐sectional definitions of subtle objective cognitive impairment (sOBJ). The study aim was to compare the diagnostic accuracy of cross‐sectional sOBJ and longitudinal objective cognitive decline (ΔOBJ) for preclinical Alzheimer’s disease (AD) based on Cogstate One Card Learning (OCL) performance.MethodWe included Mayo Clinic Study of Aging cognitively unimpaired (CU) participants who were A+T+ by amyloid and tau PET assessment (n=32) and A‐T‐ (n=211); all had at least two follow‐up visits. sOBJ was defined as performance ≤ ‐1SD on OCL accuracy using age‐corrected normative data. ΔOBJ was measured using two different methods: (1) within subjects’ standard deviation (WSD) using a ≤ ‐1 z‐score for change to define decline based on Cogstate’s normative change data, and (2) extracted subject‐specific slopes from a linear mixed effects model (LME) which can be interpreted as approximate annual change; decline was defined as slope < 10%ile among a reference sample of CU participants aged 50‐65 at baseline (N=732).ResultssOBJ and ΔOBJ‐WSD both showed low sensitivity in detection of A+T+ (9.4% and 12.5%, respectively). Total AUC values did not differ significantly (p=.31) across sOBJ (AUC = .64, CI = .53‐.75) and ΔOBJ‐WSD (AUC = .53, CI = .42‐.65) methods. Sensitivity of the ΔOBJ‐LME method to predict A+T+ was improved (37.5%) when using a conventional cutoff of <10%ile slope and was further improved (56%) when using an optimal derived cutoff equivalent to <17%ile slope within the reference group. Like the sOBJ method, the ΔOBJ‐LME method differentiated groups better than chance (AUC = .69, CI = .58‐.80). Despite increased sensitivity, total AUC values were not significantly different across sOBJ and ΔOBJ‐LME methods (p=.34). However, total AUC of ΔOBJ‐LME was significantly better than ΔOBJ‐WSD (p=.03).ConclusionsΔOBJ may be more sensitive to preclinical AD than sOBJ and may serve as a helpful method for identifying at risk CU individuals if advanced statistical methods are used for defining change.

AbstractBackgroundWhite matter changes and Alzheimer’s disease pathology frequently co‐exist in the population. Recently we empirically derived subtypes of incident mild cognitive impairment (MCI) and found that there was significant heterogeneity not only in cognitive impairment profiles but also gray matter atrophy suggesting that multiple etiologies may contribute to cognitive impairment in these subtypes. The aim of this study was to examine differences in white matter hyperintensity (WMH) volume in these same MCI subtypes and investigate amyloid deposition in a smaller subset.MethodWe analyzed data from 188 participants with incident MCI enrolled in the population‐based Mayo Clinic Study of Aging (MCSA) identified as having one of four MCI subtypes: subtle cognitive impairment (SCI), amnestic, dysnomic, and dysexecutive. All participants completed 3T imaging at the time of the MCI diagnosis. Using WMH volume scaled by TIV and PIB SUVR, we compared each MCI subtype to 344 cognitively impaired (CU) participants (mean age 78; 46% women) and each other.ResultThe amnestic (n = 83; mean age 80; 43% women), dysnomic (n = 30; mean age 84; 47% women) and dysexecutive subtypes (n = 49; mean age 83; 35% women) had significantly higher WMH volumes compared to CU (p < .02) while the SCI subtype (n = 26; mean age 80; 23% women) did not differ from CU (p = .76). Amongst the MCI subtypes, the amnestic (p = .04) and dysexecutive subtypes (p = .01) had significantly higher WMH volumes than the SCI subtype [Figure 1]. In a smaller subset of individuals who also completed PiB‐PET (17/26 SCI; 39/83 amnestic; 10/30 dysnomic, 28/49 dysexecutive), we found evidence for higher amyloid load in all MCI subgroups except the SCI group (p<0.05) in comparison to CU.ConclusionWe found significantly elevated levels of WMH and amyloid burden in amnestic, dysnomic, and dysexecutive subtypes of incident MCI supporting the notion that both vascular changes and amyloid contribute to the development of clinical symptoms. Surprisingly, WMH and amyloid positivity were not high in SCI suggesting that the pathophysiology in this group needs further investigation.

AbstractIntroductionWe examined differences in cortical thickness in empirically derived mild cognitive impairment (MCI) subtypes in the Mayo Clinic Study of Aging.MethodsWe compared cortical thickness of four incident MCI subtypes (n = 192) to 1257 cognitive unimpaired individuals.ResultsThe subtle cognitive impairment cluster had atrophy in the entorhinal and parahippocampal cortex. The amnestic, dysnomic, and dysexecutive clusters also demonstrated entorhinal cortex atrophy as well as thinning in temporal, parietal, and frontal isocortex in somewhat different patterns.DiscussionWe found patterns of atrophy in each of the incident MCI clusters that corresponded to their patterns of cognitive impairment. The identification of MCI subtypes based on cognitive and structural features may allow for more efficient trial and study designs. Given individuals in the subtle cognitive impairment cluster have less structural changes and cognitive decline and may represent the earliest group, this could be a unique group to target with early interventions.

AbstractIntroductionComparison of tau (flortaucipir) positron emission tomography (FTP‐PET) to autopsy is important to demonstrate the relationship of FTP‐PET to neuropathologic findings.MethodsAutopsies were performed on 26 participants who had antemortem FTP‐PET. FTP‐PET standardized uptake value ratios (SUVRs) were compared to autopsy diagnoses and Braak tangle stage. Quantitative tau burden was compared to regional FTP‐PET signal.ResultsParticipants with Braak stages of IV or greater had elevated FTP‐PET signal. FTP‐PET was elevated in participants with Alzheimer's disease. An FTP‐PET SUVR cut point of 1.29 was determined to be optimal. Quantitative measurements of hippocampal and temporal lobe tau burden were highly correlated to FTP‐PET signal (rho's from 0.61 to 0.70, P ≤ .02).DiscussionElevated FTP‐PET reflects Braak IV or greater neuropathology. Participants with primary age‐related tauopathy and hippocampal sclerosis did not show elevated FTP‐PET signal. Secondary neuropathologic diagnoses of Alzheimer's disease neuropathologic change can lead to borderline elevated FTP‐PET signal.