Cortical thickness and semantic fluency in Alzheimer's disease and mild cognitive impairment

Lower semantic fluency scores and a phonemic-over-semantic advantage predict abnormal CSF P-tau181 levels in Aβ + patients within the Alzheimer's disease clinical spectrum

BACKGROUND

The present study aimed to determine whether patients with mild cognitive impairment (MCI) and dementia due to Alzheimer's disease (AD), semantic verbal fluency (SVF), and the semantic-phonemic discrepancy (SPD) could predict abnormal cerebrospinal fluid (CSF) phosphorylated tau (P-tau₁₈₁) and total tau (T-tau) levels.

METHODS

Phonemic verbal fluency (PVF) and SVF scores of N = 116 Aβ-positive patients with either MCI due to AD (N = 39) or probable AD dementia (ADD; N = 77) were retrospectively collected. The SPD was computed by subtracting PVF scores from SVF ones (positive and negative values corresponding to a semantic and phonemic advantage, respectively). Patients were cognitively phenotyped via a thorough test battery and profiled according to the amyloidosis/tauopathy/neurodegeneration (ATN) framework via CSF analyses. Two separate sets of logistic regressions were run to predict normal vs. abnormal P-tau₁₈₁ and T-tau levels by encompassing as predictors SVF + PVF and SPD and covarying for demographic, disease-related features, and cognitive profile.

RESULTS

Lower SVF, but not PVF, scores, as well as a greater phonemic advantage (i.e., negative SPD values), predicted abnormal CSF P-tau₁₈₁ levels (p ≤ .01). Moreover, lower SVF scores were selectively predictive of abnormal CSF T-tau levels too (p = .016), while the SPD was not.

DISCUSSION

SVF and the SPD are able to predict tauopathy across the AD spectrum, thus supporting their status of valid, and sufficiently specific, cognitive markers of AD.

A comparison of techniques for deriving clustering and switching scores from verbal fluency word lists

Objective

To compare techniques for computing clustering and switching scores in terms of agreement, correlation, and empirical value as predictors of incident cognitive impairment (ICI).

Methods

We transcribed animal and letter F fluency recordings on 640 cases of ICI and matched controls from a national epidemiological study, amending each transcription with word timings. We then calculated clustering and switching scores, as well as scores indexing speed of responses, using techniques described in the literature. We evaluated agreement among the techniques with Cohen’s κ and calculated correlations among the scores. After fitting a base model with raw scores, repetitions, and intrusions, we fit a series of Bayesian logistic regression models adding either clustering and switching scores or speed scores, comparing the models in terms of several metrics. We partitioned the ICI cases into acute and progressive cases and repeated the regression analysis for each group.

Results

For animal fluency, we found that models with speed scores derived using the slope difference algorithm achieved the best values of the Watanabe–Akaike Information Criterion (WAIC), but with good net reclassification improvement (NRI) only for the progressive group (8.2%). For letter fluency, different models excelled for prediction of acute and progressive cases. For acute cases, NRI was best for speed scores derived from a network model (3.4%), while for progressive cases, the best model used clustering and switching scores derived from the same network model (5.1%). Combining variables from the best animal and letter F models led to marginal improvements in model fit and NRI only for the all-cases and acute-cases analyses.

Conclusion

Speed scores improve a base model for predicting progressive cognitive impairment from animal fluency. Letter fluency scores may provide complementary information.

Automated assessment of speech production and prediction of MCI in older adults

The population of older adults is growing dramatically and, with it comes increased prevalence of neurological disorders, including Alzheimer's disease (AD). Though existing cognitive screening tests can aid early detection of cognitive decline, these methods are limited in their sensitivity and require trained administrators. The current study sought to determine whether it is possible to identify persons with mild cognitive impairment (MCI) using automated analysis of spontaneous speech. Participants completed a brief neuropsychological test battery and a spontaneous speech task. MCI was classified using established research criteria, and lexical-semantic features were calculated from spontaneous speech. Logistic regression analyses compared the predictive ability of a commonly-used cognitive screening instrument (the Modified Mini Mental Status Exam, 3MS) and speech indices for MCI classification. Testing against constant-only logistic regression models showed that both the 3MS [χ2(1) = 6.18, p = .013; AIC = 41.46] and speech indices [χ2(16) = 32.42, p = .009; AIC = 108.41] were able to predict MCI status. Follow-up testing revealed the full speech model better predicted MCI status than did 3MS (p = .049). In combination, the current findings suggest that spontaneous speech may have value as a potential screening measure for the identification of cognitive deficits, though confirmation is needed in larger, prospective studies.

Cognitive dysfunction and cerebral volumetric deficits in individuals with Alzheimer's disease, alcohol use disorder, and dual diagnosis

Epidemiological surveys suggest that excessive drinking is associated with higher risk of Alzheimer's disease (AD). The present study utilized data from the National Alzheimer's Coordinating Center to examine cognition as well as gray/white matter and ventricular volumes among participants with AD and alcohol use disorder (AD/AUD, n = 52), AD only (n = 701), AUD only (n = 67), and controls (n = 1283). AUD diagnosis was associated with higher Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) in AD than in non-AD. AD performed worse on semantic fluency and Trail Making Test A + B (TMT A + B) and showed smaller total GMV, WMV, and larger ventricular volume than non-AD. AD had smaller regional GMV in the inferior/superior parietal cortex, hippocampal formation, occipital cortex, inferior frontal gyrus, posterior cingulate cortex, and isthmus cingulate cortex than non-AD. AUD had significantly smaller somatomotor cortical GMV and showed a trend towards smaller volume in the hippocampal formation, relative to non-AUD participants. Misuse of alcohol has an additive effect on dementia severity among AD participants. Smaller hippocampal volume is a common feature of both AD and AUD. Although AD is associated with more volumetric deficits overall, AD and AUD are associated with atrophy in largely distinct brain regions.

Brain-predicted age difference score is related to specific cognitive functions: a multi-site replication analysis

Brain-predicted age difference scores are calculated by subtracting chronological age from 'brain' age, which is estimated using neuroimaging data. Positive scores reflect accelerated ageing and are associated with increased mortality risk and poorer physical function. To date, however, the relationship between brain-predicted age difference scores and specific cognitive functions has not been systematically examined using appropriate statistical methods. First, applying machine learning to 1359 T1-weighted MRI scans, we predicted the relationship between chronological age and voxel-wise grey matter data. This model was then applied to MRI data from three independent datasets, significantly predicting chronological age in each dataset: Dokuz Eylül University (n = 175), the Cognitive Reserve/Reference Ability Neural Network study (n = 380), and The Irish Longitudinal Study on Ageing (n = 487). Each independent dataset had rich neuropsychological data. Brain-predicted age difference scores were significantly negatively correlated with performance on measures of general cognitive status (two datasets); processing speed, visual attention, and cognitive flexibility (three datasets); visual attention and cognitive flexibility (two datasets); and semantic verbal fluency (two datasets). As such, there is firm evidence of correlations between increased brain-predicted age differences and reduced cognitive function in some domains that are implicated in cognitive ageing.

Relationship between Brain Tissue Changes and Blood Biomarkers of Cyclophilin A, Heme Oxygenase-1, and Inositol-Requiring Enzyme 1 in Patients with Alzheimer's Disease

Cyclophilin A (CypA), heme oxygenase-1 (HO-1), and inositol-requiring enzyme 1 (IRE1) are believed to be associated with Alzheimer's disease (AD). In this study, we investigated the association between gray matter volume (GMV) changes and blood levels of CypA, HO-1, and IRE1 in cognitively normal (CN) subjects and those with amnestic mild cognitive impairment (aMCI) and AD. Forty-five elderly CN, 34 aMCI, and 39 AD subjects were enrolled in this study. The results of voxel-based multiple regression analysis showed that blood levels of CypA, HO-1, and IRE1 were correlated with GMV on brain magnetic resonance imaging (MRI) in the entire population (p = 0.0005). The three serum protein levels were correlated with GMV of signature AD regions in the population as a whole. CypA values increased with increasing GMV in the occipital gyrus (r = 0.387, p < 0.0001) and posterior cingulate (r = 0.196, p = 0.034). HO-1 values increased with increasing GMV at the uncus (r = 0.307, p = 0.0008), lateral globus pallidus and putamen (r = 0.287, p = 0.002), and hippocampus (r = 0.197, p = 0.034). IRE1 values decreased with increasing GMV at the uncus (r = -0.239, p = 0.010) and lateral globus pallidus and putamen (r = -0.335, p = 0.0002). Associations between the three serum protein levels and regional GMV indicate that the blood levels of these biomarkers may reflect the pathological mechanism of AD in the brain.

Word retrieval across the biomarker-confirmed Alzheimer's disease syndromic spectrum

Alzheimer's disease (AD) is now conceptualized as a biological entity defined by amyloid and tau deposition and neurodegeneration, with heterogeneous clinical presentations. With the aid of in vivo biomarkers, clinicians are better poised to examine clinical syndromic variability arising from a common pathology. Word retrieval deficits, measured using verbal fluency and confrontation naming tests, are hallmark features of the early clinical stages of the amnestic presentations of AD, specifically in category fluency and naming with relatively spared letter fluency. As yet, there is no consensus regarding performance on these tests in atypical clinical phenotypes of AD, including posterior cortical atrophy (PCA) and logopenic primary progressive aphasia (lvPPA), in individuals who are amyloid-positive (Aβ+) but present with different clinical profiles and patterns of neurodegeneration compared to amnestic AD. The goal of the current study is to determine how Aβ+ individuals across the syndromic spectrum of AD perform on three different word retrieval tasks. A secondary goal is to determine the neuroanatomical substrates underlying word retrieval performance in these Aβ+ individuals. Thirty-two Aβ+ participants with the amnestic presentation, 16 with Aβ+ PCA, 22 with Aβ+ lvPPA, and 99 amyloid-negative (Aβ-) control participants were evaluated with verbal fluency and visual confrontation naming tests as well as high-resolution MRI. The Aβ+ patient groups were rated at very mild or mild levels of severity (CDR 0.5 or 1) and had comparable levels of global cognitive impairment (average MMSE = 23.7 ± 3.9). Behaviorally, we found that the word retrieval profile of PCA patients is comparable to that of amnestic patients, characterized by intact letter fluency but impaired category fluency and visual confrontation naming, while lvPPA patients demonstrated impairment across all tests of word retrieval. Across all AD variants, we observed that letter fluency was associated with cortical thickness in prefrontal, central precuneus, lateral parietal and temporal cortex, while category fluency and naming were associated with cortical thickness in left middle frontal gyrus, posterior middle temporal gyrus, and lateral parietal cortex. Visual confrontation naming was uniquely associated with atrophy in inferior temporal and visual association cortex. We conclude that a better understanding of the word retrieval profiles and underlying neurodegeneration across the AD syndromic spectrum will help improve interpretation of neuropsychological profiles with regard to the localization of neurodegeneration, particularly in the atypical AD variants.

Accuracy of verbal fluency tests in the discrimination of mild cognitive impairment and probable Alzheimer's disease in older Spanish monolingual individuals

The main objetive was to analyze the accuracy of different verbal fluency tests (VFTs) in discriminating cognitively healthy subjects from individuals with mild cognitive impairment (MCI) and probable Alzheimer's disease (AD) in a cohort of older Spanish speaking adults. As a result, we aimed to identify the VFT that best predicts conversion from MCI to probable AD. 287 subjects: 170 controls (HC), 90 stable MCI and 27 patients with MCI that evolved into probable AD (MCI-AD) were assessed with a neuropsychological battery test and five VFTs. The animal fluency test produced the best differentiation of HC from MCI (p < .001), of HC from MCI-AD (p < .001) and of MCI from MCI-AD converters (p < .001), with sensitivities 98.8%, 98.8% and 75.6%, respectively. Logistic regression showed that the animal fluency test (p < 0.001) appears to be the most useful and neuropsychological VFT to predict conversion to probable dementia.

Optimizing the preclinical Alzheimer's cognitive composite with semantic processing: The PACC5

INTRODUCTION

Amyloid-related decline in semantic memory was recently shown to be observable in the preclinical period of Alzheimer's disease. Cognitive composites designed to be sensitive to cognitive change in preclinical Alzheimer's disease (e.g., preclinical Alzheimer's cognitive composite [PACC]) and currently used in secondary prevention trials do not currently integrate measures of semantic processing. Our objective was to determine whether a standard semantic measure (i.e., category fluency [CAT] to animals, fruits, and vegetables) adds independent information above and beyond Aβ-related decline captured by the PACC.

METHODS

Clinically normal older adults from the Harvard Aging Brain Study were identified at baseline as Aβ+ (n = 70) or Aβ- (n = 209) using Pittsburgh compound B-positron emission tomography imaging and followed annually with neuropsychological testing for 3.87 ± 1.09 years. The relationships between PACC, CAT, and variations of the PACC including/excluding CAT were examined using linear mixed models controlling for age, sex, and education. We additionally examined decline on CAT by further grouping Aβ+ participants into preclinical stage 1 and stage 2 on the basis of neurodegeneration markers.

RESULTS

CAT explained unique variance in amyloid-related decline, with Aβ+'s continuing to decline relative to Aβ-'s in CAT even after controlling for overall PACC decline. In addition, removal of CAT from the PACC resulted in a longitudinal Aβ+/- effect size reduction of 20% at 3-year follow-up and 12% at 5-year follow-up. Finally, both stage 1 and stage 2 participants declined on CAT in comparison with stage 0, suggesting CAT declines early within the preclinical trajectory.

CONCLUSION

Addition of CAT to the PACC provides unique information about early cognitive decline not currently captured by the episodic memory, executive function, and global cognition components and may therefore improve detection of early Aβ-related cognitive decline.

Detrending Changes the Temporal Dynamics of a Semantic Fluency Task

Objective: To study the dynamics of clustering semantic fluency responses and switching between clusters. Methods: We conducted a cross-sectional study of participants (N = 60) in a study of patient reported outcomes who were given the Saint Louis University Mental Status test. Sixty-second animal naming tests were scored for the timing of responses as well as the clustering of responses into semantic categories. Time scores were detrended to correct for exponential exhaustion and normalize the time scale across individuals. Results: Grouped by number of responses given, low performers (LP; Carter et al., 2012) switched between clusters fewer times than medium performers (MP) and high performers (HP). Prior to detrending, LP showed increased intracluster response times when compared to the other groups, but no differences were shown in intercluster response times. After detrending, however, the difference in intracluster response times disappeared and LP showed significantly faster detrended intercluster response times compared to both MP and HP. Conclusion: Prior to detrending, slower intracluster response times appear to be driving poorer performance. When time scores are detrended, our findings suggest that LP participants have quicker intercluster response times but exhaust more quickly as well. Detrending can help describe the interplay between the structure-loss and retrieval-slowing models of declining semantic fluency by isolating the component mechanisms involved in each.

Altered Frontal Lateralization Underlies the Category Fluency Deficits in Older Adults with Mild Cognitive Impairment: A Near-Infrared Spectroscopy Study

Individuals with mild cognitive impairment (MCI) have been consistently found to have category fluency deficits. However, little is known about the neural basis of these deficits. A diversity of neuroimaging studies has revealed left-lateralized prefrontal activations due to verbal processing and control functions during the performance of category fluency tasks. Given the reports of structural and functional abnormalities in the prefrontal cortices in individuals with MCI, it is conceivable that these individuals would also exhibit altered prefrontal activation patterns during a category fluency task. The present study aimed to investigate the prefrontal dynamics during the category fluency task in older adults with MCI by using near-infrared spectroscopy (NIRS). Twenty-six older adults with MCI were compared with 26 older adults with normal cognition (NC) who were matched in age, gender, handedness, and educational level. All participants performed a category fluency task while the prefrontal dynamics were recorded. The results showed that the MCI group generated fewer unique words, made fewer switches between subcategories, and generated fewer new subcategories than did the NC group. Importantly, the NIRS results showed that the NC group exhibited a left lateralization of frontal activations during the category fluency task, while the MCI group did not exhibit such a lateralization. Furthermore, there was a significant positive correlation between the category fluency performance and the extent of lateralization, suggesting that the category fluency deficits in the MCI group could be related to frontal dysfunction. That is, the rightward shift of frontal activations in the MCI group may reflect the presence of cortical reorganization in which the contralateral regions (i.e., the right hemisphere) are recruited to take over the function that is declining in the specialized regions (i.e., the left hemisphere). Our lateralization finding may serve as an objective neural marker for distinguishing between normal aging and MCI. Our study highlights that an alteration of neural functioning is already present at the prodromal stage of dementia.