Jack, Clifford R.

AbstractBackgroundAmyloid‐related imaging abnormalities (ARIA), edema (E) or hemorrhagic (H) type, have been reported in trials of anti‐β‐amyloid passive immunotherapies in sporadic and dominantly inherited Alzheimer Disease (DIAD). However, beyond APOE‐ɛ4 the risk factors and clinical implications of ARIA are not well understood, especially in DIAD populations. Here we characterize ARIA, focusing on ARIA‐E in the DIAN‐TU‐001 trial evaluating gantenerumab and solanezumab in DIAD.MethodThe DIAN‐TU‐001 trial enrolled 194 participants, including 144 DIAD mutation‐carriers receiving gantenerumab (n=52), solanezumab (n=52), or a placebo (n=40). Clinical assessments included the Clinical Dementia Rating (CDR). Imaging assessments included PiB‐PET and safety MR, including T2‐FLAIR and T2*‐GRE. Treatment dosage and APOE‐ɛ4 status were also reported.ResultEleven participants developed a total of 14 ARIA‐E episodes (discovered on scheduled safety MR) and three had associated mild symptoms reported in retrospect (e.g. headache, imbalance disorder). Though one ARIA‐E case was observed in the solanezumab arm, the following results focus on the gantenerumab arm to prevent unblinding. Recipients of gantenerumab were more likely to develop ARIA‐E compared to placebo (odds ratio (OR)=9.29, 95% confidence interval (CI)=[1.1,75.9], p‐value<0.05). ARIA‐E participants were PiB‐PET+ and 60% were CDR>0. APOE‐ɛ4 tends to be associated with risk for developing ARIA‐E (OR=5.0, 95%CI=[1.0,30.4], p‐value=0.055). ARIA‐E were not observed at initial 225mg dose and were first observed after a titration step (within 4‐24 weeks, after 1‐6 injections, Table 1). Time‐to‐resolution of ARIA‐E was 10.4±6.2weeks. Seven of ten ARIA‐E patients paused/reduced dose escalation and three discontinued treatment. Overall, developing ARIA‐E did not increase the odds of trial discontinuation (OR=1.57, 95%CI=[0.34,7.33], p‐value=0.57). ARIA‐E occurred primarily in the occipital lobe (71%) with associated incident ARIA‐H (microhemorrhages or superficial siderosis) in 60% of ARIA‐E participants. ARIA‐E size was associated with microhemorrhage count (Spearman’s rho=0.72, p‐value<0.05), rate of change (rho=0.78, p‐value<0.01), and baseline PiB‐PET (rho=0.68, p‐value<0.05). Normalizing by baseline, PiB‐PET decreased similarly in ARIA‐E+ (‐0.21±0.20) and ARIA‐E‐ (‐0.16±0.20) participants.ConclusionIn DIAD, gantenerumab dose over 225mg increased ARIA‐E risk, possibly more for APOE‐ɛ4 carriers. ARIA‐E was reversible, generally asymptomatic, and without increased odds of trial discontinuation. These aspects of drug response give insights for managing ARIA‐E occurrence in future trials.

AbstractBackgroundEarly changes in white matter (WM) measured using diffusion tensor imaging (DTI) are sensitive markers of WM degeneration and predict future cognitive decline in mild cognitive impairment (MCI). We sought to examine whether changes in WM integrity differed among empirically derived subtypes of incident MCI.MethodParticipants included 66 individuals with incident MCI enrolled in the population‐based Mayo Clinic Study of Aging (MCSA) previously identified via cluster analysis as having one of four MCI subtypes: subtle cognitive impairment (SCI; n = 13, mean age 78; 15% women), amnestic (n = 24; mean age 79; 54% women), dysnomic (n = 8; mean age 79; 38% women), and dysexecutive (n = 21; mean age 82; 33% women). All participants completed 3T MRI at the time of the MCI diagnosis. We compared the MCI subtypes to 100 cognitively unimpaired (CU) participants (mean age 77; 49% women). We used tract‐based spatial statistics to examine voxel‐level differences in fractional anisotropy (FA). We also fit a linear regression model to regional FA data from the corpus callosum (CC), the major interhemispheric WM connection, to quantify the relative differences in WM damage.ResultAll MCI subtypes except the subtle cognitive impairment group had widespread decreased FA. Relative to CU, the amnestic cluster showed decreased FA in the CC (genu), cingulum, fornix and uncinate fasciculus (UF); the dysnomic cluster showed decreased FA in the CC (genu, splenium), fornix, UF, anterior thalamic radiation (ATR), and corticospinal tract (CST); and the dysexecutive group showed decreased FA in the CC (genu, body, splenium), cingulum, UF, ATR, CST, and superior longitudinal fasciculus. The dysexecutive cluster had the most severe bilateral involvement among all MCI subtypes. The regional analysis showed that the amnestic, dysnomic, and dysexecutive groups (but not the subtle cognitive impairment group) had significantly lower FA of the CC compared to CU (p<0.001; Figure 1).ConclusionWe found widespread WM degeneration in the commissural and long association fibers in amnestic, dysnomic, and dysexecutive incident MCI subtypes. The extent of CC damage seen in Figure 1. confirmed the voxel‐level results and suggests that interhemispheric WM disconnection is relevant to the development of MCI.

AbstractBackgroundOptimizing software to measure Flortaucipir (AV‐1451) tau PET SUVR change‐over‐time is crucial for longitudinal observational studies and potential trials of anti‐tau agents. Ideal measurements should have good repeatability (low noise), and should clearly separate clinical cognitive groups.MethodWe compared 456 software methods varying in their use of: two major packages, each with cross‐sectional and longitudinal variants (FreeSurfer and an in‐house pipeline using SPM12, MCALT, and ANTs); three temporal‐lobe target regions (each with/without adjacent WM); seven reference regions; five PVC methods; and two statistics (mean vs. median). We used linear mixed‐effects models to compare methods using scans from 88 Mayo Clinic participants (46 cognitively impaired, 42 impaired, excluding those with symptoms inconsistent with the AD pathology imaged by Flortaucipir), each with three visits with PET and MRI. From these models, we calculated two criteria for each pipeline: relative measurement error (residual from the linear mixed model), and the t‐statistic for testing differences in group‐wise rates of change (which has a Cohen’s d interpretation of effect size for longitudinal data). We plotted both criteria orthogonally, then ranked methods overall according to the average of their ranks on both individual criteria.ResultMethods using the entorhinal cortex target region performed poorly in both criteria (Figure 1). The top 10 methods by the combined criteria (top‐left in Figure 2) all used the Mayo SPM12‐based pipeline with an eroded supratentorial WM (eSWM) or composite (eSWM + pons + cerebellum) reference region. Among them, 9/10 used the longitudinal variant, 8/10 used 2‐compartment PVC, and 7/10 used median. Altogether, our results favored SUVR methods with a longitudinal design (simultaneously calculating all time‐points), a temporal‐lobe meta‐ROI including adjacent WM, a composite reference region, 2‐class voxel‐based (Meltzer) PVC, and median statistics. Methods using GTM‐Tau PVC (Baker et al., Data in Brief, 2017) had the highest group separation but relatively large measurement error, giving them ranks 197 and 199 out of 456 with the joint (average rank) criteria.ConclusionCompared with popular FreeSurfer‐based methods (ranks 176, 258; Figure 2), our top‐ranked approaches approximately halved error in SUVR measurements while maintaining or improving group separation.

AbstractBackgroundPrior evidence has suggested associations between hearing loss and smaller brain volumes particularly in the temporal lobe where the primary auditory cortex is located, probably due to changes in cortical organization associated with reduced auditory stimulation. Evidence regarding associations of central auditory processing with brain volumes is relatively limited. The study aims to investigate cross‐sectional associations of central auditory processing with brain volumes in older adults.MethodWe studied 587 cognitively normal (Mini‐Mental State Exam ≥23 if high school degree or less and ≥25 if above high school degree) older adults (mean age: 77±4 years, 56% female, 17% black), including 426 with hearing loss from the Aging and Cognitive Health Evaluation in Elders (ACHIEVE) baseline (2018‐19), which is an ancillary randomized controlled trial of the Atherosclerosis Risk in Communities (ARIC) Study and 161 with normal hearing, comparable age and cognitive status from the ARIC Visit 6/7 (2016‐17/2018‐19). Brain volumes were measured by magnetic resonance imaging (MRI) scans and were transformed to z‐scores. Central auditory processing was measured by the Quick Speech‐in‐Noise (QuickSIN) test. Total scores range from 0 to 30 with lower scores indicating worse speech‐in‐noise performance. Multivariable‐adjusted linear regression was used to estimate cross‐sectional differences in standardized brain volumes associated with differences in QuickSIN score. Models adjusted for age, sex, race, education, cohort, body mass index, smoking, hypertension, diabetes, stroke, intracranial volume, and pure‐tone average.ResultEvery 5‐point decrease in QuickSIN score (worse performance) was associated with smaller volumes of the temporal lobe (‐0.07SD, 95% CI: ‐0.13, ‐0.01). QuickSIN score was also associated with subregions of the temporal lobe related to auditory processing, memory and emotion, including amygdala (‐0.13SD, 95% CI: ‐0.21, ‐0.04), middle (‐0.08SD, 95% CI: ‐0.15, ‐0.00) and superior temporal gyri (‐0.08SD, 95% CI: ‐0.15, ‐0.01).ConclusionPoorer central auditory processing was associated with smaller temporal lobe volumes, including but not limited to subregions important for auditory processing. The ongoing collection of ACHIEVE data with longitudinal MRI data will facilitate understanding of association between hearing loss and brain atrophy as well as the potential promising effects of hearing treatment in mitigating brain aging.

Abstract We investigated the cross-sectional associations of speech-in-noise performance with magnetic resonance imaging brain volumes among 588 cognitively normal participants (77±4 years, 56% female) from the Aging and Cognitive Health Evaluation in Elders Study (randomized trial embedded in the Atherosclerosis Risk in Communities (ARIC) Study) baseline in 2018-19 (N=427, with hearing loss) and ARIC (N=161, normal hearing) Visit 6/7 in 2016-17/2018-19. Central auditory processing was measured by Quick Speech-in-Noise (QuickSIN) test; range: 0 to 30, lower scores=worse performance. In models adjusted for demographic and disease covariates, every 5-point decrease in QuickSIN score was associated with smaller volumes of the temporal lobe overall (-0.07SD, 95% CI:-0.13,-0.01) as well as subregions including but not limited to those important for auditory processing (amygdala:-0.13SD, 95% CI:-0.21,-0.04; middle temporal gyrus:-0.08SD, 95% CI:-0.15,-0.00; superior temporal gyrus:-0.08SD, 95% CI:-0.15,-0.01). Further research is needed to understand the mechanisms underlying these observed associations.

AbstractAimWe investigate if periodontal disease is prospectively associated with cerebrovascular and neurodegenerative markers of dementia and Alzheimer's pathology.Materials and MethodsN = 1306 participants (Visit 5 mean age = 76.5 [standard deviation = 5.4] years) in the Atherosclerosis Risk in Communities study with completed dental exams at Visit 4 underwent brain magnetic resonance imaging scans at Visit 5 while N = 248 underwent positron emission tomography scans. Participants were classified as edentulous or, among the dentate, by the modified Periodontal Profile Class. Brain volumes were regressed on periodontal status in linear regressions. Cerebrovascular measures and β‐amyloid positivity were regressed on periodontal status in logistic regressions.ResultsPeriodontal disease was not associated with brain volumes, microhaemorrhages, or elevated β‐amyloid. Compared with periodontally healthy individuals, odds ratios [95% confidence interval] for all‐type infarcts were 0.37 [0.20, 0.65] for severe tooth loss and 0.56 [0.31, 0.99] for edentulous participants.ConclusionsWithin the limitations of this study, periodontal disease was not associated with altered brain volumes, microhaemorrhages, or β‐amyloid positivity. Tooth loss was associated with lower odds of cerebral infarcts.

Abstract Introduction We investigated the longitudinal relationship between cortical amyloid deposition, anxiety, and depression and the risk of incident mild cognitive impairment (MCI). Methods We followed 1440 community‐dwelling, cognitively unimpaired individuals aged ≥ 50 years for a median of 5.5 years. Clinical anxiety and depression were assessed using Beck Anxiety and Depression Inventories (BAI, BDI‐II). Cortical amyloid beta (Aβ) was measured by Pittsburgh compound B positron emission tomography (PiB‐PET) and elevated deposition (PiB+) was defined as standardized uptake value ratio ≥ 1.48. We calculated Cox proportional hazards models with age as the time scale, adjusted for sex, education, and medical comorbidity. Results Cortical Aβ deposition (PiB+) independent of anxiety (BAI ≥ 10) or depression (BDI‐II ≥ 13) increased the risk of MCI. There was a significant additive interaction between PiB+ and anxiety (joint effect hazard ratio 6.77; 95% confidence interval 3.58–12.79; P = .031) that is, being PiB+ and having anxiety further amplified the risk of MCI. Discussion Anxiety modified the association between PiB+ and incident MCI.

AbstractIntroductionMotoric cognitive risk (MCR), a clinical syndrome characterized by slow gait speed and subjective cognitive complaints, has been associated with dementia risk. The neuropathological features underlying MCR remain poorly understood.MethodsThe Atherosclerosis Risk in Communities (ARIC) community‐based cohort study classified participants using standardized criteria as MCR+/– and mild cognitive impairment (MCI)+/– at study baseline (2011–2013). We examined the 5‐year dementia risk and baseline brain structural/molecular abnormalities associated with MCR+ and MCI+ status.ResultsOf 5023 nondemented participants included, 204 were MCR+ and 1030 were MCI+. Both MCR+ and MCI+ participants demonstrated increased dementia risk. The pattern of structural brain abnormalities associated with MCR+ differed from that of MCI+. Whereas MCI+ was associated with comparatively smaller volumes in brain regions vulnerable to Alzheimer's disease pathology, MCR+ status was associated with smaller volumes in frontoparietal regions and greater white matter abnormalities.DiscussionMCR may represent a predementia syndrome characterized by prominent white matter abnormalities and frontoparietal atrophy.

AbstractWe aimed to evaluate the value of ATN biomarker classification system (amyloid beta [A], pathologic tau [T], and neurodegeneration [N]) for predicting conversion from mild cognitive impairment (MCI) to dementia. In a sample of people with MCI (n = 415) we assessed predictive performance of ATN classification using empirical knowledge‐based cut‐offs for each component of ATN and compared it to two data‐driven approaches, logistic regression and RUSBoost machine learning classifiers, which used continuous clinical or biomarker scores. In data‐driven approaches, we identified ATN features that distinguish normals from individuals with dementia and used them to classify persons with MCI into dementia‐like and normal groups. Both data‐driven classification methods performed better than the empirical cut‐offs for ATN biomarkers in predicting conversion to dementia. Classifiers that used clinical features performed as well as classifiers that used ATN biomarkers for prediction of progression to dementia. We discuss that data‐driven modeling approaches can improve our ability to predict disease progression and might have implications in future clinical trials.

We present the case of a cognitively unimpaired 77-year-old man with elevated, asymmetric, and longitudinally increasing Flortaucipir tau PET despite normal (visually negative) amyloid PET. His atypical tau PET signal persisted and globally increased in a follow-up scan five years later. Across eight years of observations, temporoparietal atrophy was observed consistent with tau PET patterns, but he retained the cognitively unimpaired classification. Altogether, his atypical tau PET signal is not explained by any known risk factors or alternative pathologies, and other imaging findings were not remarkable. He remains enrolled for further observation.