Pudumjee, Shehroo B.

Background: Conventional normative samples include individuals with undetected Alzheimer’s disease neuropathology, lowering test sensitivity for cognitive impairment. Objective: We developed Mayo Normative Studies (MNS) norms limited to individuals without elevated amyloid or neurodegeneration (A–N–) for Rey’s Auditory Verbal Learning Test (AVLT). We compared these MNS A–N– norms in female, male, and total samples to conventional MNS norms with varying levels of demographic adjustments. Methods: The A–N– sample included 1,059 Mayo Clinic Study of Aging cognitively unimpaired (CU) participants living in Olmsted County, MN, who are predominantly non-Hispanic White. Using a regression-based approach correcting for age, sex, and education, we derived fully-adjusted T-score formulas for AVLT variables. We validated these A–N– norms in two independent samples of CU ( n = 261) and mild cognitive impairment (MCI)/dementia participants ( n = 392) > 55 years of age. Results: Variability associated with age decreased by almost half in the A–N– norm sample relative to the conventional norm sample. Fully-adjusted MNS A–N– norms showed approximately 7– 9% higher sensitivity to MCI/dementia compared to fully-adjusted MNS conventional norms for trials 1– 5 total and sum of trials. Among women, sensitivity to MCI/dementia increased with each normative data refinement. In contrast, age-adjusted conventional MNS norms showed greatest sensitivity to MCI/dementia in men. Conclusions: A–N– norms show some benefits over conventional normative approaches to MCI/dementia sensitivity, especially for women. We recommend using these MNS A–N– norms alongside MNS conventional norms. Future work is needed to determine if normative samples that are not well characterized clinically show greater benefit from biomarker-refined approaches.

AbstractBackgroundLogopenic progressive aphasia (LPA) and posterior cortical atrophy (PCA) have distinct patterns of hypometabolism and atrophy. However, these clinical syndromes overlap: visuospatial impairment has been documented in LPA and aphasia in PCA. Rey‐Osterrieth Complex Figure – Copy (Rey‐O Copy) performance is correlated with parietal‐occipital atrophy in LPA. We explore visuospatial impairment on the Rey‐O Copy in LPA and PCA with the Mayo Older Americans Normative Studies (MOANS; which uses Meyers & Meyers criteria) and the Boston Qualitative Scoring System (BQSS). We also examine the proportion of visuospatial impairment in LPA, an under‐appreciated phenomenon, compared to PCA wherein it is fundamental.MethodPatients with LPA (n=25) or PCA (n=23) were recruited by the Neurodegenerative Research Group. Patients underwent comprehensive neuropsychological testing (including Rey‐O Copy) at baseline visit. Cut‐offs of T‐score=40 (BQSS) or scaled score=7 (MOANS) were used based on normative data. Proportions of patients with low performance were examined across LPA and PCA groups. Individual logistic regressions and AUROC analyses were then conducted to quantify differences in visuospatial impairment in LPA and PCA with both scoring systems. Identical analyses were conducted using raw scores corrected for age and sex, to avoid confounds of adjustments in normative data.ResultLPA and PCA groups were comparable on age, sex, and disease duration (LPA Median = 2.7 years, IQR=1.9‐3.5; PCA Median = 3.6 years, IQR=1.5‐4.9); p=.823). Surprisingly, 52‐72% of LPA participants demonstrated impaired performance across scoring systems, relative to 96% of the PCA group identified by both scoring systems. Odds ratios (OR) for the Rey‐O Copy MOANS (OR = 1.59; p=.008) and BQSS Copy Presence and Accuracy index (CPA; OR = 1.13, p=.002) were significant, persisting for age‐ and sex‐ controlled raw scores, suggesting the odds of a PCA diagnosis increased with decrement on Rey‐O Copy. AUROC values ranged from 0.77 to 0.88 across these indices.ConclusionA substantial number of LPA participants showed visuospatial impairment, despite initial primary language complaints. Differentiation of diagnostic groups by the Rey‐O is likely underscored by relatively uniform, profound, visuospatial impairment in PCA with more variability in LPA. However, the degree of visuospatial impairment overlaps remarkably across diagnoses.

Background: Longitudinal, but not cross-sectional, cognitive testing is one option proposed to define transitional cognitive decline for individuals on the Alzheimer’s disease continuum. Objective: Compare diagnostic accuracy of cross-sectional subtle objective cognitive impairment (sOBJ) and longitudinal objective decline (ΔOBJ) over 30 months for identifying 1) cognitively unimpaired participants with preclinical Alzheimer’s disease defined by elevated brain amyloid and tau (A+T+) and 2) incident mild cognitive impairment (MCI) based on Cogstate One Card Learning (OCL) accuracy performance. Methods: Mayo Clinic Study of Aging cognitively unimpaired participants aged 50 + with amyloid and tau PET scans (n = 311) comprised the biomarker-defined sample. A case-control sample of participants aged 65 + remaining cognitively unimpaired for at least 30 months included 64 who subsequently developed MCI (incident MCI cases) and 184 controls, risk-set matched by age, sex, education, and visit number. sOBJ was assessed by OCL z-scores. ΔOBJ was assessed using within subjects’ standard deviation and annualized change from linear regression or linear mixed effects (LME) models. Concordance measures Area Under the ROC Curve (AUC) or C-statistic and odds ratios (OR) from conditional logistic regression models were derived. sOBJ and ΔOBJ were modeled jointly to compare methods. Results: sOBJ and ΔOBJ-LME methods differentiated A+T+ from A-T- (AUC = 0.64, 0.69) and controls from incident MCI (C-statistic = 0.59, 0.69) better than chance; other ΔOBJ methods did not. ΔOBJ-LME improved prediction of future MCI over baseline sOBJ (p = 0.003) but not over 30-month sOBJ (p = 0.09). Conclusion: Longitudinal decline did not offer substantial benefit over cross-sectional assessment in detecting preclinical Alzheimer’s disease or incident MCI.

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.

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.