Abstract Background Normal aging and preclinical Alzheimer’s Disease (AD) share common features, such as structural changes to medial temporal lobe regions and declining episodic memory. However, prior work suggests qualitative differences between AD‐related memory changes and those due to aging. Specifically, recollection‐based, or contextual, memory declines with both normal aging and AD. Alternatively, familiarity‐based, or item, memory is more specific to preclinical AD and atrophy in the perirhinal cortex. In the current analysis, we examined the relationship between these forms of memory with plasma biomarkers associated with AD and neurodegeneration. Method At the Penn Alzheimer’s Disease Research Center, 127 cognitively‐normal participants (age=73.12±6.62, 59% female, years of education=16.40±2.62, 80% Caucasian) completed an experimental memory paradigm assessing recollection and familiarity along with standard neuropsychological testing. In this paradigm, pictures of common objects were presented in 80 pairs at study and participants were told to pick the object they preferred. At test, 40 intact, 40 re‐arranged, and 40 novel object pairs were presented. Recollection was defined as the probability(intact)–probability(rearranged), while familiarity was defined as the probability(rearranged)/(1‐R). To account for differences in base rates of false alarms (‘‘old’’ responses to novel pairs), familiarity was calculated using a measure of discrimination (d’) derived from signal detection theory. Whole blood samples were collected in EDTA‐tubes, spun‐down, and stored at ‐80°C. Measures of glial fibrillary acidic protein (GFAP), neurofilament light chain (Nfl), and plasma tau (p‐Tau181) were generated with the Simoa HD‐X analyzer system. Result Familiarity correlated with GFAP (r(125) =‐0.24, p<0.05) (Figure 1) and NfL (r(125) =‐0.23, p<0.05) (Figure 2). Further, a partial correlation controlling for age and days between the experimental and plasma measure remained significant for GFAP (r(125)=‐0.25, p<0.05). Additionally, recollection correlated with Nfl (r(125) =‐0.25, p<0.05) (Figure 3). Correlations with standard neuropsychological tests revealed no significant results. Conclusion This study reveals that within the normal aging spectrum, familiarity‐based memory correlates with molecular measures that have been associated with amyloid (GFAP), while both measures correlated with a non‐specific measure of neurodegeneration (NfL). This supports the notion that familiarity may be sensitive to preclinical AD.
Abstract Background The medial temporal lobe's (MTL) early involvement in tau pathology makes it a key focus in the development of preclinical Alzheimer’s disease (AD) biomarkers. ROI analyses in prior studies reported significant MTL structural differences in cognitively normal individuals with and without ß‐amyloid (A+/‐CN). Pointwise analysis, offering spatial information of early neurodegeneration, has potential to pinpoint “signature regions” of pathological change, but has been underexplored in the MTL. This study employs a specialized pointwise analysis pipeline to examine the spatial pattern of MTL structural change in subgroups dichotomized by both ß‐amyloid and tau status in a large cohort of CN individuals. Methods A dataset of 3036 CN (A‐/A+: 1270/1558, Table 1) individuals from ADNI, HABS, A4 and ABC were analyzed. We extracted MTL regional thickness maps from MRI using tailored pipelines, ASHS‐T1 and CRASHS. For participants with prospective longitudinal MRI (five years follow‐up), regional maps of longitudinal atrophy rate were extracted using SkelDBM. Subjects with cross‐sectional tau PET available (N=563) were further divided into A and T subgroups by tracer uptake. General linear modeling was performed on each surface point to investigate cross‐sectional and longitudinal MTL structural group differences (detailed in Figure 1) and their correlation with MTL tau burden in All/A+/A‐ CN. Age and sex were covariates and cluster‐level multiple comparison correction was performed. Results A+CN demonstrated a significantly faster atrophy rate than A‐CN across the whole MTL, primarily driven by A+T+CN individuals (Figure 1‐b). Notably, A‐T+CN showed significantly faster atrophy rate in the entorhinal cortex (ERC) and Brodmann area 35 (BA35), the earliest sites of tau pathology (Figure 1‐b, second column). Figure 2‐b displays an MTL‐wise significant correlation between atrophy rate and tau in All/A+/A‐ CN. In both analyses, cross‐sectional effects are consistently weaker than longitudinal ones, but have some significant clusters in ERC and BA35. Conclusions Pointwise analysis revealed extensive tau‐associated accelerated neurodegeneration in the MTL in preclinical AD. Furthermore, accelerated atrophy was observed in early Braak regions in A‐CN with evidence of tau pathology, potentially driven by primary age‐related tauopathy (PART). These pointwise longitudinal MTL measures provide sensitive measures that may allow for disease monitoring in preclinical AD.
Abstract Background Quantitative three‐dimensional maps of tau neurofibrillary tangles (NFT) burden derived from dense serial histology have potential application for in‐vivo biomarker studies. We constructed a group‐level NFT burden map from 15 medial temporal lobe (MTL) specimens, majority with P rimary A ge‐ R elated T auopathy (PART) or low‐level Alzheimer’s disease neuropathologic change, and showed relatively greater NFT burden in the anterior vs. posterior MTL. We investigated whether in‐vivo MRI and PET measures in ROIs derived from this map show meaningful biological relationships. Method Multimodal in‐vivo imaging data from 292 participants in the A ging B rain C ohort were used. The group‐level NFT burden map was mapped to each participant’s MRI to define an ROI mask, further divided into anterior (aMTL) and posterior (pMTL) ROIs. Cortical thickness (N=292) and 18 F‐Flortaucipir SUVR maps (N=86) were computed. Participants’ age was correlated with average thickness in the aMTL, pMTL, and anatomically defined MTL ROIs. 18 F‐Flortaucipir uptake was compared between aMTL and pMTL. The analyses were repeated in subsets of cognitive normal participants, and those with negative amyloid PET scans. Result Cortical thickness in the aMTL ROI showed stronger correlation with age than pMTL and anatomically defined MTL subregional thickness. A polynomial fit provided the best age regression, with older participants showing a parabolic decline in thickness around age 60, when substantial NFT accumulation begins in MTL. Further, tau tracer uptake in aMTL was slightly but significantly higher than in pMTL (SUVR 1.19 vs. 1.18, p=0.02). Conclusion We demonstrate the potential use of ex‐vivo NFT burden maps for in‐vivo image analysis. NFT deposition is particularly prominent in the anterior MTL in cases without or with low amyloid burden and at early Braak stage. Prior work suggests that even in the absence of amyloid, this tangle pathology may drive neurodegeneration in the aging population. Here we show that cortical thickness, a biormarker for neurodegeneration, when measured within a histopathologically‐defined region enriched for PART NFTs in the aMTL, is better correlated with age than when measured within anatomically defined subregions, suggesting that the relationship may be driven by PART. Greater tau tracer uptake in the aMTL ROI further supports this notion.
Abstract Background The medial temporal lobe's (MTL) early involvement in tau pathology makes it a key focus in the development of preclinical Alzheimer’s disease (AD) biomarkers. ROI analyses in prior studies reported significant MTL structural differences in cognitively normal individuals with and without β‐amyloid (A+/‐CN). Pointwise analysis, offering spatial information of early neurodegeneration, has potential to pinpoint “signature regions” of pathological change, but has been underexplored in the MTL. This study employs a specialized pointwise analysis pipeline to examine the spatial pattern of MTL structural change in subgroups dichotomized by both β‐amyloid and tau status in a large cohort of CN individuals. Methods A dataset of 3036 CN (A‐/A+: 1270/1558, Table 1) individuals from ADNI, HABS, A4 and ABC were analyzed. We extracted MTL regional thickness maps from MRI using tailored pipelines, ASHS‐T1 and CRASHS. For participants with prospective longitudinal MRI (five years follow‐up), regional maps of longitudinal atrophy rate were extracted using SkelDBM. Subjects with cross‐sectional tau PET available (N=563) were further divided into A and T subgroups by tracer uptake. General linear modeling was performed on each surface point to investigate cross‐sectional and longitudinal MTL structural group differences (detailed in Figure 1) and their correlation with MTL tau burden in All/A+/A‐ CN. Age and sex were covariates and cluster‐level multiple comparison correction was performed. Results A+CN demonstrated a significantly faster atrophy rate than A‐CN across the whole MTL, primarily driven by A+T+CN individuals (Figure 1‐b). Notably, A‐T+CN showed significantly faster atrophy rate in the entorhinal cortex (ERC) and Brodmann area 35 (BA35), the earliest sites of tau pathology (Figure 1‐b, second column). Figure 2‐b displays an MTL‐wise significant correlation between atrophy rate and tau in All/A+/A‐ CN. In both analyses, cross‐sectional effects are consistently weaker than longitudinal ones, but have some significant clusters in ERC and BA35. Conclusions Pointwise analysis revealed extensive tau‐associated accelerated neurodegeneration in the MTL in preclinical AD. Furthermore, accelerated atrophy was observed in early Braak regions in A‐CN with evidence of tau pathology, potentially driven by primary age‐related tauopathy (PART). These pointwise longitudinal MTL measures provide sensitive measures that may allow for disease monitoring in preclinical AD.
Abstract Variability in the relationship of tau-based neurofibrillary tangles (T) and degree of neurodegeneration (N) in Alzheimer’s Disease (AD) is likely attributable to the non-specific nature of N, which is also modulated by such factors as other co-pathologies, age-related changes, and developmental differences. We studied this variability by partitioning patients within the Alzheimer’s continuum into data-driven groups based on their regional T-N dissociation, which reflects the residuals after the effect of tau pathology is “removed”. We found six groups displaying distinct spatial T-N mismatch and thickness patterns despite similar tau burden. Their T-N patterns resembled the neurodegeneration patterns of non-AD groups partitioned on the basis of z-scores of cortical thickness alone and were similarly associated with surrogates of non-AD factors. In an additional sample of individuals with antemortem imaging and autopsy, T-N mismatch was associated with TDP-43 co-pathology. Finally, T-N mismatch training was then applied to a separate cohort to determine the ability to classify individual patients within these groups. These findings suggest that T-N mismatch may provide a personalized approach for determining non-AD factors associated with resilience/vulnerability to Alzheimer’s disease.
Abstract Background The extent to which pathological processes in aging and Alzheimer’s disease (AD) relate to functional disruption of the medial temporal lobe (MTL)‐dependent brain networks is poorly understood. To address this knowledge gap, we examined functional connectivity (FC) alterations between anterior and posterior regions of the MTL and in MTL‐associated functional communities – the Anterior‐Temporal (AT) and Posterior‐Medial (PM) networks – in normal agers, individuals with preclinical AD, and patients with Mild Cognitive Impairment or mild dementia due to AD. Method In this cross‐sectional study, we analyzed data from 179 individuals from the Aging Brain Cohort study of the Penn ADRC. Detailed information about participants is provided in Table 1. For intra‐MTL FC comparisons, the MTL subregions were segmented using the automated segmentation of hippocampal subfields‐T1 (ASHS‐T1) pipeline (Fig. 1a). When modeling the MTL’s interactions with the rest of the cortex, we employed four MTL ROIs (left/right × anterior/posterior) derived from an ex vivo atlas of tau accumulation in the MTL. Our functional datasets were preprocessed using a customized fMRIprep pipeline. Sparse network estimations and modularity‐based consensus clustering were used to reconstruct the AT and PM network systems (Fig. 1b). Age effect analyses and group comparisons along the AD continuum were performed using the General Linear Model within the network‐based statistical framework. Results The preclinical stage of AD was characterized by increased FC between the perirhinal cortex and other regions of the MTL, as well as between the anterior MTL and its direct neighbors in the AT network (Fig. 1c‐d). This effect was not present in symptomatic AD. Instead, symptomatic patients displayed reduced hippocampal and intra‐PM connectivity. For normal aging, our results led to three main conclusions (for visuals, see Fig. 2). First, intra‐network connectivity of both the AT and PM networks decreases with age. Second, FC between the anterior and posterior segments of the MTL declines with age. Finally, within the MTL, we observed greater vulnerability of the posterior MTL subregions, particularly the parahippocampal cortex, to age‐associated FC decline. Conclusion Together, the current results provide evidence for aberrant connectivity in the preclinical stage of AD that may have implications for early AD pathophysiology.
Abstract Background Previous work suggests functional abnormalities in the human brain in preclinical Alzheimer’s disease. However, little has been explored about the relationship between BOLD fMRI signal amplitude/energy over time and AD pathology. In this work we analyzed the effects of AD progression on amplitude of low‐frequency fluctuations (ALFF) during resting‐state fMRI scans both at the whole‐brain level and at a more granular level, focused on regions of the medial temporal lobe (MTL) that are most vulnerable to AD pathology. Method In this cross‐sectional study, we analyzed data from 224 individuals from the Penn ADRC cohort (Table 1). All participants underwent structural and functional MRI on a Siemens 3T Prisma system, and 18 F‐Florbetaben or 18 F‐Florbetapir amyloid‐PET imaging. 125 participants also underwent 18 F‐Flortaucipir tau‐PET scans. Functional images were preprocessed using a custom implementation of fMRIprep and ALFF was extracted using Conn software. In the whole‐brain analyses we performed voxelwise GLMs with age and sex as covariates. Results We observed reduced ALFF in both preclinical AD (Amyloid‐positive (Aβ+) cognitively unimpaired, CU) and Aβ+ cognitively impaired (CI) individuals. Relative to Aβ‐ controls, individuals with preclinical AD displayed lower ALFF in frontal, parietal and temporal association cortices (Figure 1, top left). CI individuals displayed lower ALFF in most of the brain, except in inferior temporal cortex, temporal pole, and MTL. The effect of AD progression on ALFF was characterized by a progressive reduction primarily in frontal and parietal regions that roughly align with the anatomy of the default mode network. In contrast, transentorhinal tau pathology was negatively associated with ALFF in frontal and anterior temporal lobes, as well as insula and MTL (Figure 1 bottom right). Negative association between tau burden and MTL ALFF was observed in all main MTL subregions, and strongest in the transetorhinal cortex (Figure 2). Conclusion We conclude that: (1) ALFF might be a promising biomarker for studying functional abnormalities in preclinical AD, and (2) based on the spatial topography of amyloid and tau effects on ALFF (Figure 1 bottom), there is likely a differential effect of of the two on ALFF that needs to be further explored.
Abstract Background The extent to which pathological processes in aging and Alzheimer’s disease (AD) relate to functional alterations in the medial temporal lobe (MTL)‐dependent brain networks is poorly understood. Here, we examined the relationship between tau accumulation in the (trans)entorhinal cortex and functional connectivity (FC) in two MTL‐affiliated brain networks — the Anterior‐Temporal (AT) and Posterior‐Medial (PM) — in normal agers, individuals with preclinical AD, and patients with symptomatic AD. Method In this cross‐sectional study, we analyzed data from 125 individuals from the Penn ADRC (Table 1). All participants underwent structural and functional MRI on a Siemens 3 T Prisma system, as well as 18 F‐Florbetaben and 18 F‐Flortaucipir (FTP) PET imaging. We used the AT/PM network architecture from our previous work (Figure 1; PMID37767219) and analyzed the effects of (trans)entorhinal tau accumulation on the AT/PM FC as a function of distance to the MTL (Figure 1). Guided by our previous findings of an inverted U‐shaped FC pattern in the AT network over the course of the disease, we performed separate analyses of the AT FC in cognitively normal and symptomatic individuals. Results FC between the anterior MTL and its direct neighbors in the AT network was positively correlated with tau accumulation in the MTL (r = 0.201, p = 0.031; Figure 2a). Associations with tau were not present in other MTL‐AT connections (Figures 2b‐c) or in individuals with symptomatic AD. In contrast, the PM FC was broadly affected by tau pathology with both direct MTL‐PM and more distant connections showing a negative relationship to (trans)entorhinal tau (Figure 2d‐e). Excluding amyloid‐negative controls, the relationship between MTL tau and AT/PM FC remained statistically significant in the PM [one‐hop connections: r = ‐0.323, p = 0.0479; distant connections: r = ‐0.324, p = 0.047] but not the AT network. Conclusions Together, the current results implicate functional abnormalities in the AT network during the preclinical stage, while those in the PM network are closely related to disease severity. This dissociation likely represents distinct pathophysiology in AD and has potential implications for FC‐based metrics as a surrogate measure for assessing functional response to disease‐modifying immunotherapies.
Abstract Background The extent to which pathological processes in aging and Alzheimer’s disease (AD) relate to functional alterations in the medial temporal lobe (MTL)‐dependent brain networks is poorly understood. Here, we examined the relationship between tau accumulation in the (trans)entorhinal cortex and functional connectivity (FC) in two MTL‐affiliated brain networks — the Anterior‐Temporal (AT) and Posterior‐Medial (PM) — in normal agers, individuals with preclinical AD, and patients with symptomatic AD. Method In this cross‐sectional study, we analyzed data from 125 individuals from the Penn ADRC (Table 1). All participants underwent structural and functional MRI on a Siemens 3 T Prisma system, as well as 18F‐Florbetaben and 18F‐Flortaucipir (FTP) PET imaging. We used the AT/PM network architecture from our previous work (Fig. 1; PMID37767219) and analyzed the effects of (trans)entorhinal tau accumulation on the AT/PM FC as a function of distance to the MTL (Fig. 1). Guided by our previous findings of an inverted U‐shaped FC pattern in the AT network over the course of the disease, we performed separate analyses of the AT FC in cognitively normal and symptomatic individuals. Results FC between the anterior MTL and its direct neighbors in the AT network was positively correlated with tau accumulation in the MTL (r = 0.201, p = 0.031; Fig. 2a). Associations with tau were not present in other MTL‐AT connections (Figs. 2b‐c) or in individuals with symptomatic AD. In contrast, the PM FC was broadly affected by tau pathology with both direct MTL‐PM and more distant connections showing a negative relationship to (trans)entorhinal tau (Fig. 2d‐e). Excluding amyloid‐negative controls, the relationship between MTL tau and AT/PM FC remained statistically significant in the PM [one‐hop connections: r = ‐0.323, p = 0.0479; distant connections: r = ‐0.324, p = 0.047] but not the AT network. Conclusions Together, the current results implicate functional abnormalities in the AT network during the preclinical stage, while those in the PM network are closely related to disease severity. This dissociation likely represents distinct pathophysiology in AD and has potential implications for FC‐based metrics as a surrogate measure for assessing functional response to disease‐modifying immunotherapies.
Objective: Mobile, valid, and engaging cognitive assessments are essential for detecting and tracking change in research participants and patients at risk for Alzheimer’s Disease and Related Dementias (ADRDs). This pilot study aims to determine the feasibility and performance of app-based memory and executive functioning tasks included in the mobile cognitive app performance platform (mCAPP), to remotely detect cognitive changes associated with aging and preclinical Alzheimer’s Disease (AD). Participants and Methods: The mCAPP includes three gamified tasks: (1) a memory task that includes learning and matching hidden card pairs and incorporates increasing memory load, pattern separation features (lure vs. non-lure), and spatial memory (2) a stroop-like task (“brick drop”) with speeded word and color identification and response inhibition components and (3) a digit-symbol coding-like task (“space imposters”) with increasing pairs and incidental learning components. The cohort completed the NACC UDS3 neuropsychological battery, selected NIH Toolbox tasks, and additional cognitive testing sensitive to pre-clinical AD, within six months of the mCAPP testing. Participants included thirty-seven older adults (60% female; age=72±4.4, years of education=17±2.5; 67% Caucasian, 30% Black/AA, 3% Multiracial) with normal cognition who are enrolled in the Penn Alzheimer’s Disease Research Center (ADRC) cohort. Participants completed one in-person session and two weeks of at-home testing, with eight scheduled sessions, four in the morning and four in the afternoon. Participants also completed questionnaires and an interview about technology use and wore activity trackers to collect daily step and sleep data and answered questions about mood, anxiety, and fatigue throughout the two weeks of at-home data collection. Results: The participants completed an average of 11 at-home sessions, with the majority choosing to play extra sessions. Participants reported high usability ratings for all tasks and the majority rated the task difficulty as acceptable. On all mCAPP tasks, participant performance declined in accuracy and speed with increasing memory load and task complexity. mCAPP tasks correlated significantly with paper and pencil measures and several NIH Toolbox tasks (p<0.05). Examination of performance trends over multiple sessions indicates stabilization of performance within 4-6 sessions on memory mCAPP measures and 5-7 sessions on executive functioning mCAPP measures. Preliminary analyses indicate differences in mCAPP measures and imaging biomarkers. Conclusions: Participants were willing and able to complete at-home cognitive testing and most chose to complete more than the assigned sessions. Remote data collection is feasible and well-tolerated. We show preliminary construct validity with the UDS3 and NIH Toolbox and test-retest reliability following a period of task learning and performance improvement and stabilization. This work will help to advance remote detection and monitoring of early cognitive changes associated with preclinical AD. Future directions will include further evaluation of the relationships between mCAPP performance, behavioral states, and neuroimaging biomarkers as well as the utility of detection of practice effects in identifying longitudinal change and risk for ADRD-related cognitive decline.
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