Associations between NIH Toolbox Cognition Battery and in vivo brain amyloid and tau pathology in non-demented older adults

Pittsburgh plasma p-tau217: classification accuracies for autosomal dominant and sporadic Alzheimer's disease in the community

INTRODUCTION

Most available p-tau217 immunoassays have similar performances. It is unclear if this is due to the use of the same antibody (the "ALZpath antibody"). We established and evaluated a novel p-tau217 assay that employs an alternative antibody, and benchmarked the results against ALZpath-p-tau217.

METHODS

Following development and analytical validation of the University of Pittsburgh ("Pitt-p-tau217") method, clinical verification was performed in three independent cohorts (n=363).

RESULTS

Pitt-p-tau217 demonstrated high between-run stability, linearity, and specificity. Clinically, Pitt-p-tau217 differentiated neuropathologically confirmed PSEN1 mutation carriers from controls with AUC=0.94, and Aβ-PET-positive from Aβ-PET-negative cognitively normal older adults with AUC up to 0.84, equivalent to ALZpath-p-tau217 results. Both Pitt-p-tau217 and ALZpath-p-tau217 were elevated in tau-PET-positive versus tau-PET-negative participants (P=0.06; AUC=0.71 for both). Between-assay correlations were up to 0.93.

DISCUSSION

The new Pitt-p-tau217 assay exhibits high and reproducible classification accuracies for identifying individuals with biological evidence of AD, equivalent to the widely used ALZpath-p-tau217.

Computerized cognitive testing to capture cognitive decline in Alzheimer's disease: Longitudinal findings from the ARMADA study

INTRODUCTION

Timely detection and tracking of Alzheimer's disease (AD) -related cognitive decline has become a public health priority. We investigated whether the NIH Toolbox for Assessment of Neurological and Behavioral Function-Cognition Battery (NIHTB-CB) detects AD-related cognitive decline.

METHODS

N = 171 participants (age 76.5 ± 8; 53% female, 34% Aβ-positive) from the ARMADA study completed the NIHTB-CB at baseline, 12 months, and 24 months. Linear mixed-effect models correcting for demographics were used to examine cross-sectional and longitudinal NIHTB-CB scores in individuals across the clinical AD spectrum.

RESULTS

Compared to Aβ-negative healthy controls, Aβ-positive individuals with amnestic MCI or mild AD performed worse on all NIHTB-CB measures and showed an accelerated decline in processing speed, working memory, and auditory word comprehension tests.

DISCUSSION

These findings support the use of the NIHTB-CB in early AD, but also imply that the optimal NIHTB-CB composite score to detect change over time may differ across clinical stages of AD. Future directions include replication of these findings in larger and more demographically diverse samples.

Highlights

We examined NIH Toolbox-Cognition Battery scores across the clinical AD spectrum.All NIH Toolbox tests detected cross-sectional cognitive impairment in MCI-to-mild AD.Three NIH Toolbox tests captured further decline over time in MCI-to-mild AD.The NIH Toolbox can facilitate timely detection of AD-related cognitive decline.

Multi-analyte proteomic analysis identifies blood-based neuroinflammation, cerebrovascular and synaptic biomarkers in preclinical Alzheimer's disease

BACKGROUND

Blood-based biomarkers are gaining grounds for the detection of Alzheimer's disease (AD) and related disorders (ADRDs). However, two key obstacles remain: the lack of methods for multi-analyte assessments and the need for biomarkers for related pathophysiological processes like neuroinflammation, vascular, and synaptic dysfunction. A novel proteomic method for pre-selected analytes, based on proximity extension technology, was recently introduced. Referred to as the NULISAseq CNS disease panel, the assay simultaneously measures ~ 120 analytes related to neurodegenerative diseases, including those linked to both core (i.e., tau and amyloid-beta (Aβ)) and non-core AD processes. This study aimed to evaluate the technical and clinical performance of this novel targeted proteomic panel.

METHODS

The NULISAseq CNS disease panel was applied to 176 plasma samples from 113 individuals in the MYHAT-NI cohort of predominantly cognitively normal participants from an economically underserved region in southwestern Pennsylvania, USA. Classical AD biomarkers, including p-tau181, p-tau217, p-tau231, GFAP, NEFL, Aβ40, and Aβ42, were independently measured using Single Molecule Array (Simoa) and correlations and diagnostic performances compared. Aβ pathology, tau pathology, and neurodegeneration (AT(N) statuses) were evaluated with [11C] PiB PET, [18F]AV-1451 PET, and an MRI-based AD-signature composite cortical thickness index, respectively. Linear mixed models were used to examine cross-sectional and Wilcoxon rank sum tests for longitudinal associations between NULISA and neuroimaging-determined AT(N) biomarkers.

RESULTS

NULISA concurrently measured 116 plasma biomarkers with good technical performance (97.2 ± 13.9% targets gave signals above assay limits of detection), and significant correlation with Simoa assays for the classical biomarkers. Cross-sectionally, p-tau217 was the top hit to identify Aβ pathology, with age, sex, and APOE genotype-adjusted AUC of 0.930 (95%CI: 0.878-0.983). Fourteen markers were significantly decreased in Aβ-PET + participants, including TIMP3, BDNF, MDH1, and several cytokines. Longitudinally, FGF2, IL4, and IL9 exhibited Aβ PET-dependent yearly increases in Aβ-PET + participants. Novel plasma biomarkers with tau PET-dependent longitudinal changes included proteins associated with neuroinflammation, synaptic function, and cerebrovascular integrity, such as CHIT1, CHI3L1, NPTX1, PGF, PDGFRB, and VEGFA; all previously linked to AD but only reliable when measured in cerebrospinal fluid. The autophagosome cargo protein SQSTM1 exhibited significant association with neurodegeneration after adjusting age, sex, and APOE ε4 genotype.

CONCLUSIONS

Together, our results demonstrate the feasibility and potential of immunoassay-based multiplexing to provide a comprehensive view of AD-associated proteomic changes, consistent with the recently revised biological and diagnostic framework. Further validation of the identified inflammation, synaptic, and vascular markers will be important for establishing disease state markers in asymptomatic AD.

Unhealthy white matter connectivity, cognition, and racialization in older adults

INTRODUCTION

White matter hyperintensities (WMH) may promote clinical Alzheimer's disease (AD) disparities between Black American (BA) and non-Hispanic White (nHW) populations. Using a novel measurement, unhealthy white matter connectivity (UWMC), we interrogated racialized group differences in associations between WMH in AD pathology-affected regions and cognition.

METHODS

UWMC is the proportion of white matter fibers that pass through WMH for every pair of brain regions. Individual regression models tested associations of UWMC in beta-amyloid (Aβ) or tau pathology-affected regions with cognition overall, stratified by racialized group, and with a racialized group interaction.

RESULTS

In 201 older adults ranging from cognitively unimpaired to AD, BA participants exhibited greater UWMC and worse cognition than nHW participants. UWMC was negatively associated with cognition in 17 and 5 Aβ- and tau-affected regions, respectively. Racialization did not modify these relationships.

DISCUSSION

Differential UWMC burden, not differential UWMC-and-cognition associations, may drive clinical AD disparities between racialized groups.

HIGHLIGHTS

Unhealthy white matter connectivity (UWMC) in Alzheimer's disease (AD) pathology-affected brain regions is associated with cognition. Relationships between UWMC and cognition are similar between Black American (BA) and non-Hispanic White (nHW) individuals. More UWMC may partially drive higher clinical AD burden in BA versus nHW populations. UWMC risk factors, particularly social and environmental, should be identified.

Design and Feasibility Analysis of a Smartphone-Based Digital Cognitive Assessment Study in the Framingham Heart Study

BACKGROUND

Smartphone-based digital technology is increasingly being recognized as a cost-effective, scalable, and noninvasive method of collecting longitudinal cognitive and behavioral data. Accordingly, a state-of-the-art 3-year longitudinal project focused on collecting multimodal digital data for early detection of cognitive impairment was developed.

METHODS AND RESULTS

A smartphone application collected 2 modalities of cognitive data, digital voice and screen-based behaviors, from the FHS (Framingham Heart Study) multigenerational Generation 2 (Gen 2) and Generation 3 (Gen 3) cohorts. To understand the feasibility of conducting a smartphone-based study, participants completed a series of questions about their smartphone and app use, as well as sensory and environmental factors that they encountered while completing the tasks on the app. Baseline data collected to date were from 537 participants (mean age=66.6 years, SD=7.0; 58.47% female). Across the younger participants from the Gen 3 cohort (n=455; mean age=60.8 years, SD=8.2; 59.12% female) and older participants from the Gen 2 cohort (n=82; mean age=74.2 years, SD=5.8; 54.88% female), an average of 76% participants agreed or strongly agreed that they felt confident about using the app, 77% on average agreed or strongly agreed that they were able to use the app on their own, and 81% on average rated the app as easy to use.

CONCLUSIONS

Based on participant ratings, the study findings are promising. At baseline, the majority of participants are able to complete the app-related tasks, follow the instructions, and encounter minimal barriers to completing the tasks independently. These data provide evidence that designing and collecting smartphone application data in an unsupervised, remote, and naturalistic setting in a large, community-based population is feasible.

Predicting Brain Amyloid Status Using the National Institute of Health Toolbox (NIHTB) for Assessment of Neurological and Behavioral Function

BACKGROUND

Amyloid-beta (Aβ) plaque is a neuropathological hallmark of Alzheimer's disease (AD). As anti-amyloid monoclonal antibodies enter the market, predicting brain amyloid status is critical to determine treatment eligibility.

OBJECTIVE

To predict brain amyloid status utilizing machine learning approaches in the Advancing Reliable Measurement in Alzheimer's Disease and Cognitive Aging (ARMADA) study.

DESIGN

ARMADA is a multisite study that implemented the National Institute of Health Toolbox for Assessment of Neurological and Behavioral Function (NIHTB) in older adults with different cognitive ability levels (normal, mild cognitive impairment, early-stage dementia of the AD type).

SETTING

Participants across various sites were involved in the ARMADA study for validating the NIHTB.

PARTICIPANTS

199 ARMADA participants had either PET or CSF information (mean age 76.3 ± 7.7, 51.3% women, 42.3% some or complete college education, 50.3% graduate education, 88.9% White, 33.2% with positive AD biomarkers).

MEASUREMENTS

We used cognition, emotion, motor, sensation scores from NIHTB, and demographics to predict amyloid status measured by PET or CSF. We applied LASSO and random forest models and used the area under the receiver operating curve (AUROC) to evaluate the ability to identify amyloid positivity.

RESULTS

The random forest model reached AUROC of 0.74 with higher specificity than sensitivity (AUROC 95% CI:0.73 - 0.76, Sensitivity 0.50, Specificity 0.88) on the held-out test set; higher than the LASSO model (0.68 (95% CI:0.68 - 0.69)). The 10 features with the highest importance from the random forest model are: picture sequence memory, cognition total composite, cognition fluid composite, list sorting working memory, words-in-noise test (hearing), pattern comparison processing speed, odor identification, 2-minutes-walk endurance, 4-meter walk gait speed, and picture vocabulary. Overall, our model revealed the validity of measurements in cognition, motor, and sensation domains, in associating with AD biomarkers.

CONCLUSION

Our results support the utilization of the NIH toolbox as an efficient and standardizable AD biomarker measurement that is better at identifying amyloid negative (i.e., high specificity) than positive cases (i.e., low sensitivity).

Normative Reference Values for Crystallized-Fluid Discrepancy Scores for the NIH Toolbox Cognition Battery

INTRODUCTION

The purpose of this study was to translate NIH Toolbox Cognition Battery (NIHTB-CB) Crystallized-Fluid discrepancy scores into research and clinical practice with adults by providing normative data for discrepancy scores for both age-adjusted standard scores (SSs) and demographically adjusted T-scores.

METHOD

We included adult participants from the NIHTB-CB standardization sample who denied having neurodevelopmental, medical, psychiatric, or neurological conditions (n = 730; M = 47.4 years old, SD = 17.6, range: 18-85; 64.4% women; 63.1% White). Descriptive statistics were calculated for the Fluid and Crystallized composite scores and Crystallized-Fluid discrepancy score, along with correlations between the composite scores and reliability estimates of the discrepancy score. Percentiles were calculated for the discrepancy score, with stratifications by the gender, education, and Crystallized composite for the age-adjusted SSs and demographically adjusted T-scores (T).

RESULTS

Crystallized-Fluid discrepancy scores ranged from -40 to 44 (M = -0.63, SD = 14.89, Mdn = -1, interquartile range [IQR]: -11 to 10) for age-adjusted SSs and from -29 to 27 (M = -0.39, SD = 10.49, Mdn = -1, IQR = -8 to 7) for demographically adjusted T-scores. Crystallized-Fluid discrepancy scores of SS = 15 and T = 11 were at the 16th percentile (1 SD below the mean) and discrepancy scores of SS = 21 and T = 15 were at the 7th percentile (1.5 SD below the mean).

CONCLUSIONS

Crystallized-Fluid discrepancy scores may be, with future research, a useful within-person interpretive approach for detecting a decline from pre-injury or pre-disease levels of cognitive functioning. These normative reference values assist clinicians and researchers in determining the frequency at which given Crystallized-Fluid discrepancy scores occurred among healthy adults in the normative sample.

A guide for researchers seeking training in retrospective data harmonization for population neuroscience studies of Alzheimer's disease and related dementias

Due to needs surrounding rigor and reproducibility, subgroup specific disease knowledge, and questions of external validity, data harmonization is an essential tool in population neuroscience of Alzheimer's disease and related dementias (ADRD). Systematic harmonization of data elements is necessary to pool information from heterogeneous samples, and such pooling allows more expansive evaluations of health disparities, more precise effect estimates, and more opportunities to discover effective prevention or treatment strategies. The key goal of this Tutorial in Population Neuroimaging Curriculum, Instruction, and Pedagogy article is to guide researchers in creating a customized population neuroscience of ADRD harmonization training plan to fit their needs or those of their mentees. We provide brief guidance for retrospective data harmonization of multiple data types in this area, including: (1) clinical and demographic, (2) neuropsychological, and (3) neuroimaging data. Core competencies and skills are reviewed, and resources are provided to fill gaps in training as well as data needs. We close with an example study in which harmonization is a critical tool. While several aspects of this tutorial focus specifically on ADRD, the concepts and resources are likely to benefit population neuroscientists working in a range of research areas.

Construct validity of the NIH toolbox cognitive domains: A comparison with conventional neuropsychological assessments

OBJECTIVE

Previous studies have assessed the construct validity of individual subtests in the National Institutes of Health (NIH) Toolbox Cognition Battery (NIHTB-CB), though none have examined the construct validity of the cognitive domains. Importantly, the original NIHTB-CB validation studies were administered on a desktop computer, though the NIHTB-CB is now solely administered via an iPad. We examined the construct validity of each cognitive domain assessed in the NIHTB-CB, including a motor dexterity domain using the iPad application compared to a neuropsychological battery in a sample of healthy adults.

METHOD

Eighty-three adults aged 20-66 years (M = 44.35 ± 13.41 years) completed the NIHTB-CB and a comprehensive neuropsychological assessment. Domain scores for each of six cognitive domains (attention and executive function, episodic memory, working memory, processing speed, language, and motor dexterity) and the fluid composite were computed for both batteries. We then assessed the construct validity using Pearson correlations and intraclass correlation coefficients (ICCs) for both demographically corrected and uncorrected domains.

RESULTS

We found the attention and executive function, episodic memory, and processing speed domains had poor-to-adequate construct validity (ICCConsistency = -0.029 to 0.517), the working memory and motor dexterity domains and the fluid composite had poor-to-good construct validity (ICCConsistency = 0.215-0.801), and the language domain had adequate-to-good construct validity (ICCConsistency = 0.408-0.829).

CONCLUSION

The NIHTB-CB cognitive domains have poor-to-good construct validity, thus researchers should be aware that some tests representing cognitive constructs may not fully reflect the cognitive domain of interest. Future investigation of the construct validity and reliability of the NIHTB-CB administered using the iPad is recommended. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Visuospatial memory impairment as a potential neurocognitive marker to predict tau pathology in Alzheimer's continuum

BACKGROUND

Given that tau accumulation, not amyloid-β (Aβ) burden, is more closely connected with cognitive impairment in Alzheimer's disease (AD), a detailed understanding of the tau-related characteristics of cognitive function is critical in both clinical and research settings. We investigated the association between phosphorylated tau (p-Tau) level and cognitive impairment across the AD continuum and the mediating role of medial temporal lobe (MTL) atrophy. We also developed a prediction model for abnormal tau accumulation.

METHODS

We included participants from the Gwangju Alzheimer's Disease and Related Dementia Cohort in Korea, who completed cerebrospinal fluid analysis and clinical evaluation, and corresponded to one of three groups according to the biomarkers of A and T profiles based on the National Institute on Aging and Alzheimer's Association research framework. Multiple linear and logistic regression analyses were performed to examine the association between p-Tau and cognition and to develop prediction models. Receiver operating characteristic curve analysis was performed to examine the discrimination ability of the models.

RESULTS

Among 185 participants, 93 were classified as A-T-, 23 as A+T-, and 69 as A+T+. There was an association between decreased visuospatial delayed memory performance and p-Tau level (B = - 0.754, β = - 0.363, p < 0.001), independent of other relevant variables (e.g., Aβ). MTL neurodegeneration was found to mediate the association between the two. Prediction models with visuospatial delayed memory alone (area under the curve [AUC] = 0.872) and visuospatial delayed memory and entorhinal thickness (AUC = 0.921) for abnormal tau accumulation were suggested and they were validated in an independent sample (AUC = 0.879 and 0.891, respectively).

CONCLUSION

It is crucial to identify sensitive cognitive measures that capture subtle cognitive impairment associated with underlying pathological changes. Preliminary findings from the current study might suggest that abnormal tau accumulation underlies episodic memory impairment, particularly visuospatial modality, in the AD continuum. Suggested models are potentially useful in predicting tau pathology, and might be utilized practically in the field.

Unsupervised mobile cognitive testing for use in preclinical Alzheimer's disease

INTRODUCTION

Unsupervised digital cognitive testing is an appealing means to capture subtle cognitive decline in preclinical Alzheimer's disease (AD). Here, we describe development, feasibility, and validity of the Boston Remote Assessment for Neurocognitive Health (BRANCH) against in-person cognitive testing and amyloid/tau burden.

METHODS

BRANCH is web-based, self-guided, and assesses memory processes vulnerable in AD. Clinically normal participants (n = 234; aged 50-89) completed BRANCH; a subset underwent in-person cognitive testing and positron emission tomography imaging. Mean accuracy across BRANCH tests (Categories, Face-Name-Occupation, Groceries, Signs) was calculated.

RESULTS

BRANCH was feasible to complete on participants' own devices (primarily smartphones). Technical difficulties and invalid/unusable data were infrequent. BRANCH psychometric properties were sound, including good retest reliability. BRANCH was correlated with in-person cognitive testing (r = 0.617, P < .001). Lower BRANCH score was associated with greater amyloid (r = -0.205, P = .007) and entorhinal tau (r = -0.178, P = .026).

DISCUSSION

BRANCH reliably captures meaningful cognitive information remotely, suggesting promise as a digital cognitive marker sensitive early in the AD trajectory.

Comparing Pathological Risk Factors for Dementia between Cognitively Normal Japanese and Americans

The Alzheimer's Disease Neuroimaging Initiative showed that Japanese had significantly lower brain Aβ burden than Americans among a cognitively normal population. This cross-sectional study aimed to compare vascular disease burden, Aβ burden, and neurodegeneration between cognitively normal elderly Japanese and Americans. Japanese and American participants were matched for age (±4-year-old), sex, and Apolipoprotein E (APOE) genotype. Brain vascular disease burden and brain Aβ burden were measured using white matter lesions (WMLs) and 11C-labeled Pittsburgh Compound B (PiB) retention, respectively. Neurodegeneration was measured using hippocampal volumes and cortical thickness. A total of 95 Japanese and 95 Americans were recruited (50.5% men, mean age = 82). Compared to Americans, Japanese participants had larger WMLs, and a similar global Aβ standardized uptake value ratio (SUVR), cortical thickness and hippocampal volumes. Japanese had significantly lower regional Aβ SUVR in the anterior ventral striatum, posterior cingulate cortex, and precuneus. Cognitively normal elderly Japanese and Americans had different profiles regarding vascular disease and Aβ burden. This suggests that multiple risk factors are likely to be involved in the development of dementia. Additionally, Japanese might have a lower risk of dementia due to lower Aβ burden than Americans. Longitudinal follow-up of these cohorts is warranted to ascertain the predictive accuracy of these findings.

Characterization of point-spread function specification error on Geometric Transfer Matrix partial volume correction in [11C]PiB amyloid imaging

Purpose

Partial-volume correction (PVC) using the Geometric Transfer Matrix (GTM) method is used in positron emission tomography (PET) to compensate for the effects of spatial resolution on quantitation. We evaluate the effect of misspecification of scanner point-spread function (PSF) on GTM results in amyloid imaging, including the effect on amyloid status classification (positive or negative).

Methods

Twenty-nine subjects with Pittsburgh Compound B ([¹¹C]PiB) PET and structural T1 MR imaging were analyzed. FreeSurfer 5.3 (FS) was used to parcellate MR images into regions-of-interest (ROIs) that were used to extract radioactivity concentration values from the PET images. GTM PVC was performed using our “standard” PSF parameterization [3D Gaussian, full-width at half-maximum (w) of approximately 5 mm]. Additional GTM PVC was performed with “incorrect” parameterizations, taken around the correct value. The result is a set of regional activity values for each of the GTM applications. For each case, activity values from various ROIs were combined and normalized to produce standardized uptake value ratios (SUVRs) for nine standard [¹¹C]PiB quantitation ROIs and a global region. GTM operating-point characteristics were determined from the slope of apparent SUVR versus w curves.

Results

Errors in specification of w on the order of 1 mm (3D) mainly produce only modest errors of up to a few percent. An exception was the anterior ventral striatum in which fractional errors of up to 0.29 per millimeter (3D) of error in w were observed.

Conclusion

While this study does not address all the issues regarding the quantitative strengths and weakness of GTM PVC, we find that with reasonable caution, the unavoidable inaccuracies associated with PSF specification do not preclude its use in amyloid quantitation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40658-021-00403-5.

Current advances in digital cognitive assessment for preclinical Alzheimer's disease

There is a pressing need to capture and track subtle cognitive change at the preclinical stage of Alzheimer's disease (AD) rapidly, cost-effectively, and with high sensitivity. Concurrently, the landscape of digital cognitive assessment is rapidly evolving as technology advances, older adult tech-adoption increases, and external events (i.e., COVID-19) necessitate remote digital assessment. Here, we provide a snapshot review of the current state of digital cognitive assessment for preclinical AD including different device platforms/assessment approaches, levels of validation, and implementation challenges. We focus on articles, grants, and recent conference proceedings specifically querying the relationship between digital cognitive assessments and established biomarkers for preclinical AD (e.g., amyloid beta and tau) in clinically normal (CN) individuals. Several digital assessments were identified across platforms (e.g., digital pens, smartphones). Digital assessments varied by intended setting (e.g., remote vs. in-clinic), level of supervision (e.g., self vs. supervised), and device origin (personal vs. study-provided). At least 11 publications characterize digital cognitive assessment against AD biomarkers among CN. First available data demonstrate promising validity of this approach against both conventional assessment methods (moderate to large effect sizes) and relevant biomarkers (predominantly weak to moderate effect sizes). We discuss levels of validation and issues relating to usability, data quality, data protection, and attrition. While still in its infancy, digital cognitive assessment, especially when administered remotely, will undoubtedly play a major future role in screening for and tracking preclinical AD.

Detecting Alzheimer's disease biomarkers with a brief tablet-based cognitive battery: sensitivity to Aβ and tau PET

Background

β-amyloid (Aβ) and tau positron emission tomography (PET) detect the pathological changes that define Alzheimer’s disease (AD) in living people. Cognitive measures sensitive to Aβ and tau burden may help streamline identification of cases for confirmatory AD biomarker testing.

Methods

We examined the association of Brain Health Assessment (BHA) tablet-based cognitive measures with dichotomized Aβ -PET status using logistic regression models in individuals with mild cognitive impairment (MCI) or dementia (N = 140; 43 Aβ-, 97 Aβ+). We also investigated the relationship between the BHA tests and regional patterns of tau-PET signal using voxel-wise regression analyses in a subsample of 60 Aβ+ individuals with MCI or dementia.

Results

Favorites (associative memory), Match (executive functions and speed), and Everyday Cognition Scale scores were significantly associated with Aβ positivity (area under the curve [AUC] = 0.75 [95% CI 0.66–0.85]). We found significant associations with tau-PET signal in mesial temporal regions for Favorites, frontoparietal regions for Match, and occipitoparietal regions for Line Orientation (visuospatial skills) in a subsample of individuals with MCI and dementia.

Conclusion

The BHA measures are significantly associated with both Aβ and regional tau in vivo imaging markers and could be used for the identification of patients with suspected AD pathology in clinical practice.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-021-00776-w.

Cross-sectional associations of amyloid burden with semantic cognition in older adults without dementia: A systematic review and meta-analysis

Previous research suggests the presence of subtle semantic decline in early stages of Alzheimer's disease. This study investigated associations between amyloid burden, a biomarker for Alzheimer's disease, and tasks of semantic impairment in older individuals without dementia. A systematic search in MEDLINE, PsycINFO, and Embase yielded 3691 peer-reviewed articles excluding duplicates. After screening, 41 studies with overall 7495 participants were included in the meta-analysis and quality assessment. The overall weighted effect size of the association between larger amyloid burden and larger semantic impairment was 0.10 (95% CI [-0.03; 0.22], p = 0.128) for picture naming, 0.19 (95% CI [0.11; 0.27], p < 0.001) for semantic fluency, 0.15 (95% CI [-0.15; 0.45], p = 0.326) for vocabulary, and 0.10 (95% CI [-0.14; 0.35], p = 0.405; 2 studies) for WAIS Information. Risk of bias was highest regarding comparability, as effect sizes were often not calculated on covariate-adjusted statistics. The relevance of the indicated amyloid-related decline in semantic fluency for research and clinical applications is likely negligible due to the effect's small magnitude. Future research should develop more sensitive metrics of semantic fluency to optimize its use for early detection of Alzheimer's disease-related cognitive impairment.