Functional Changes in the Language Network in Response to Increased Amyloid β Deposition in Cognitively Intact Older Adults

Longitudinal associations of serum biomarkers with early cognitive, amyloid and grey matter changes

Blood-based biomarkers have been extensively evaluated for their diagnostic potential in Alzheimer's disease. However, their relative prognostic and monitoring capabilities for cognitive decline, amyloid-β (Aβ) accumulation and grey matter loss in cognitively unimpaired elderly require further investigation over extended time periods. This prospective cohort study in cognitively unimpaired elderly [n = 185, mean age (range) = 69 (53-84) years, 48% female] examined the prognostic and monitoring capabilities of glial fibrillary acidic protein (GFAP), neurofilament light (NfL), Aβ1-42/Aβ1-40 and phosphorylated tau (pTau)181 through their quantification in serum. All participants underwent baseline Aβ-PET, MRI and blood sampling as well as 2-yearly cognitive testing. A subset additionally underwent Aβ-PET (n = 109), MRI (n = 106) and blood sampling (n = 110) during follow-up [median time interval (range) = 6.1 (1.3-11.0) years]. Matching plasma measurements were available for Aβ1-42/Aβ1-40 and pTau181 (both n = 140). Linear mixed-effects models showed that high serum GFAP and NfL predicted future cognitive decline in memory (βGFAP×Time = -0.021, PFDR = 0.007 and βNfL×Time = -0.031, PFDR = 0.002) and language (βGFAP×Time = -0.021, PFDR = 0.002 and βNfL×Time = -0.018, PFDR = 0.03) domains. Low serum Aβ1-42/Aβ1-40 equally but independently predicted memory decline (βAβ1-42/Aβ1-40×Time = -0.024, PFDR = 0.02). Whole-brain voxelwise analyses revealed that low Aβ1-42/Aβ1-40 predicted Aβ accumulation within the precuneus and frontal regions, high GFAP and NfL predicted grey matter loss within hippocampal regions and low Aβ1-42/Aβ1-40 predicted grey matter loss in lateral temporal regions. Serum GFAP, NfL and pTau181 increased over time, while Aβ1-42/Aβ1-40 decreased only in Aβ-PET-negative elderly. NfL increases associated with declining memory (βNfLchange×Time = -0.030, PFDR = 0.006) and language (βNfLchange×Time = -0.021, PFDR = 0.02) function and serum Aβ1-42/Aβ1-40 decreases associated with declining language function (βAβ1-42/Aβ1-40×Time = -0.020, PFDR = 0.04). GFAP increases associated with Aβ accumulation within the precuneus and NfL increases associated with grey matter loss. Baseline and longitudinal serum pTau181 only associated with Aβ accumulation in restricted occipital regions. In head-to-head comparisons, serum outperformed plasma Aβ1-42/Aβ1-40 (ΔAUC = 0.10, PDeLong, FDR = 0.04), while both plasma and serum pTau181 demonstrated poor performance to detect asymptomatic Aβ-PET positivity (AUC = 0.55 and 0.63, respectively). However, when measured with a more phospho-specific assay, plasma pTau181 detected Aβ-positivity with high performance (AUC = 0.82, PDeLong, FDR < 0.007). In conclusion, serum GFAP, NfL and Aβ1-42/Aβ1-40 are valuable prognostic and/or monitoring tools in asymptomatic stages providing complementary information in a time- and pathology-dependent manner.

Neuroimaging Modalities in Alzheimer's Disease: Diagnosis and Clinical Features

Alzheimer's disease (AD) is a neurodegenerative disease causing progressive cognitive decline until eventual death. AD affects millions of individuals worldwide in the absence of effective treatment options, and its clinical causes are still uncertain. The onset of dementia symptoms indicates severe neurodegeneration has already taken place. Therefore, AD diagnosis at an early stage is essential as it results in more effective therapy to slow its progression. The current clinical diagnosis of AD relies on mental examinations and brain imaging to determine whether patients meet diagnostic criteria, and biomedical research focuses on finding associated biomarkers by using neuroimaging techniques. Multiple clinical brain imaging modalities emerged as potential techniques to study AD, showing a range of capacity in their preciseness to identify the disease. This review presents the advantages and limitations of brain imaging modalities for AD diagnosis and discusses their clinical value.

Classification of 18F-Flutemetamol scans in cognitively normal older adults using machine learning trained with neuropathology as ground truth

Purpose

End-of-life studies have validated the binary visual reads of ¹⁸F-labeled amyloid PET tracers as an accurate tool for the presence or absence of increased neuritic amyloid plaque density. In this study, the performance of a support vector machine (SVM)-based classifier will be tested against pathological ground truths and its performance determined in cognitively healthy older adults.

Methods

We applied SVM with a linear kernel to an ¹⁸F-Flutemetamol end-of-life dataset to determine the regions with the highest feature weights in a data-driven manner and to compare between two different pathological ground truths: based on neuritic amyloid plaque density or on amyloid phases, respectively. We also trained and tested classifiers based on the 10% voxels with the highest amplitudes of feature weights for each of the two neuropathological ground truths. Next, we tested the classifiers’ diagnostic performance in the asymptomatic Alzheimer’s disease (AD) phase, a phase of interest for future drug development, in an independent dataset of cognitively intact older adults, the Flemish Prevent AD Cohort-KU Leuven (F-PACK). A regression analysis was conducted between the Centiloid (CL) value in a composite volume of interest (VOI), as index for amyloid load, and the distance to the hyperplane for each of the two classifiers, based on the two pathological ground truths. A receiver operating characteristic analysis was also performed to determine the CL threshold that optimally discriminates between neuritic amyloid plaque positivity versus negativity, or amyloid phase positivity versus negativity, within F-PACK.

Results

The classifiers yielded adequate specificity and sensitivity within the end-of-life dataset (neuritic amyloid plaque density classifier: specificity of 90.2% and sensitivity of 83.7%; amyloid phase classifier: specificity of 98.4% and sensitivity of 84.0%). The regions with the highest feature weights corresponded to precuneus, caudate, anteromedial prefrontal, and also posterior inferior temporal and inferior parietal cortex. In the cognitively normal cohort, the correlation coefficient between CL and distance to the hyperplane was −0.66 for the classifier trained with neuritic amyloid plaque density, and −0.88 for the classifier trained with amyloid phases. This difference was significant. The optimal CL cut-off for discriminating positive versus negative scans was CL = 48–51 for the different classifiers (area under the curve (AUC) = 99.9%), except for the classifier trained with amyloid phases and based on the 10% voxels with highest feature weights. There the cut-off was CL = 26 (AUC = 99.5%), which closely matched the CL threshold for discriminating phases 0–2 from 3–5 based on the end-of-life dataset and the neuropathological ground truth.

Discussion

Among a set of neuropathologically validated classifiers trained with end-of-life cases, transfer to a cognitively normal population works best for a classifier trained with amyloid phases and using only voxels with the highest amplitudes of feature weights.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-022-05808-7.

Lower regional gray matter volume in the absence of higher cortical amyloid burden in late-life depression

Late-life depression (LLD) is associated with a risk of developing Alzheimer's disease (AD). However, the role of AD-pathophysiology in LLD, and its association with clinical symptoms and cognitive function are elusive. In this study, one hundred subjects underwent amyloid positron emission tomography (PET) imaging with [¹⁸F]-flutemetamol and structural MRI: 48 severely depressed elderly subjects (age 74.1 ± 7.5 years, 33 female) and 52 age-/gender-matched healthy controls (72.4 ± 6.4 years, 37 female). The Geriatric Depression Scale (GDS) and Rey Auditory Verbal Learning Test (RAVLT) were used to assess the severity of depressive symptoms and episodic memory function respectively. Amyloid deposition was quantified using the standardized uptake value ratio. Whole-brain voxel-wise comparisons of amyloid deposition and gray matter volume (GMV) between LLD and controls were performed. Multivariate analysis of covariance was conducted to investigate the association of regional differences in amyloid deposition and GMV with clinical factors, including GDS and RAVLT. As a result, there were no significant group differences in amyloid deposition. In contrast, LLD showed significant lower GMV in the left temporal and parietal region. GMV reduction in the left temporal region was associated with episodic memory dysfunction, but not with depression severity. Regional GMV reduction was not associated with amyloid deposition. LLD is associated with lower GMV in regions that overlap with AD-pathophysiology, and which are associated with episodic memory function. The lack of corresponding associations with amyloid suggests that lower GMV driven by non-amyloid pathology may play a central role in the neurobiology of LLD presenting as a psychiatric disorder.Trial registration: European Union Drug Regulating Authorities Clinical Trials identifier: EudraCT 2009-018064-95.

Baseline cognition is the best predictor of 4-year cognitive change in cognitively intact older adults

BACKGROUND

We examined in cognitively intact older adults the relative weight of cognitive, genetic, structural and amyloid brain imaging variables for predicting cognitive change over a 4-year time course.

METHODS

One hundred-eighty community-recruited cognitively intact older adults (mean age 68 years, range 52-80 years, 81 women) belonging to the Flemish Prevent Alzheimer's Disease Cohort KU Leuven (F-PACK) longitudinal observational cohort underwent a baseline evaluation consisting of detailed cognitive assessment, structural MRI and 18F-flutemetamol PET. At inclusion, subjects were stratified based on Apolipoprotein E (APOE) ε4 and Brain-Derived Neurotrophic Factor (BDNF) val66met polymorphism according to a factorial design. At inclusion, 15% were amyloid-PET positive (Centiloid >23.4). All subjects underwent 2-yearly follow-up of cognitive performance for a 4-year time period. Baseline cognitive scores were analysed using factor analysis. The slope of cognitive change over time was modelled using latent growth curve analysis. Using correlation analysis, hierarchical regression and mediation analysis, we examined the effect of demographic (age, sex, education) and genetic variables, baseline cognition, MRI volumetric (both voxelwise and region-based) as well as amyloid imaging measures on the longitudinal slope of cognitive change.

RESULTS

A base model of age and sex explained 18.5% of variance in episodic memory decline. This increased to 41.6% by adding baseline episodic memory scores. Adding amyloid load or volumetric measures explained only a negligible additional amount of variance (increase to 42.2%). A mediation analysis indicated that the effect of age on episodic memory scores was partly direct and partly mediated via hippocampal volume. Amyloid load did not play a significant role as mediator between age, hippocampal volume and episodic memory decline.

CONCLUSION

In cognitively intact older adults, the strongest baseline predictor of subsequent episodic memory decline was the baseline episodic memory score. When this score was included, only very limited explanatory power was added by brain volume or amyloid load measures. The data warn against classifications that are purely biomarker-based and highlight the value of baseline cognitive performance levels in predictive models.

Comparison of ELISA- and SIMOA-based quantification of plasma Aβ ratios for early detection of cerebral amyloidosis

BACKGROUND

Blood-based amyloid biomarkers may provide a non-invasive, cost-effective and scalable manner for detecting cerebral amyloidosis in early disease stages.

METHODS

In this prospective cross-sectional study, we quantified plasma Aβ1-42/Aβ1-40 ratios with both routinely available ELISAs and novel SIMOA Amyblood assays, and provided a head-to-head comparison of their performances to detect cerebral amyloidosis in a nondemented elderly cohort (n = 199). Participants were stratified according to amyloid-PET status, and the performance of plasma Aβ1-42/Aβ1-40 to detect cerebral amyloidosis was assessed using receiver operating characteristic analysis. We additionally investigated the correlations of plasma Aβ ratios with amyloid-PET and CSF Alzheimer's disease biomarkers, as well as platform agreement using Passing-Bablok regression and Bland-Altman analysis for both Aβ isoforms.

RESULTS

ELISA and SIMOA plasma Aβ1-42/Aβ1-40 detected cerebral amyloidosis with identical accuracy (ELISA: area under curve (AUC) 0.78, 95% CI 0.72-0.84; SIMOA: AUC 0.79, 95% CI 0.73-0.85), and both increased the performance of a basic demographic model including only age and APOE-ε4 genotype (p ≤ 0.02). ELISA and SIMOA had positive predictive values of respectively 41% and 36% in cognitively normal elderly and negative predictive values all exceeding 88%. Plasma Aβ1-42/Aβ1-40 correlated similarly with amyloid-PET for both platforms (Spearman ρ = - 0.32, p <  0.0001), yet correlations with CSF Aβ1-42/t-tau were stronger for ELISA (ρ = 0.41, p = 0.002) than for SIMOA (ρ = 0.29, p = 0.03). Plasma Aβ levels demonstrated poor agreement between ELISA and SIMOA with concentrations of both Aβ1-42 and Aβ1-40 measured by SIMOA consistently underestimating those measured by ELISA.

CONCLUSIONS

ELISA and SIMOA demonstrated equivalent performances in detecting cerebral amyloidosis through plasma Aβ1-42/Aβ1-40, both with high negative predictive values, making them equally suitable non-invasive prescreening tools for clinical trials by reducing the number of necessary PET scans for clinical trial recruitment.

TRIAL REGISTRATION

EudraCT 2009-014475-45 (registered on 23 Sept 2009) and EudraCT 2013-004671-12 (registered on 20 May 2014, https://www.clinicaltrialsregister.eu/ctr-search/trial/2013-004671-12/BE ).

How pattern information analyses of semantic brain activity elicited in language comprehension could contribute to the early identification of Alzheimer's Disease

Alzheimer's disease (AD) is associated with a loss of semantic knowledge reflecting brain pathophysiology that begins years before dementia. Identifying early signs of pathophysiology induced dysfunction in the neural systems that access and process words' meaning could therefore help forecast dementia. This article reviews pioneering studies demonstrating that abnormal functional Magnetic Resonance Imaging (fMRI) response patterns elicited in semantic tasks reflect both AD-pathophysiology and the hereditary risk of AD, and also can help forecast cognitive decline. However, to bring current semantic task-based fMRI research up to date with new AD research guidelines the relationship with different types of AD-pathophysiology needs to be more thoroughly examined. We shall argue that new analytic techniques and experimental paradigms will be critical for this. Previous work has relied on specialized tests of specific components of semantic knowledge/processing (e.g. famous name recognition) to reveal coarse AD-related changes in activation across broad brain regions. Recent computational advances now enable more detailed tests of the semantic information that is represented within brain regions during more natural language comprehension. These new methods stand to more directly index how pathophysiology alters neural information processing, whilst using language comprehension as the basis for a more comprehensive examination of semantic brain function. We here connect the semantic pattern information analysis literature up with AD research to raise awareness to potential cross-disciplinary research opportunities.

Cerebrospinal fluid levels of synaptic and neuronal integrity correlate with gray matter volume and amyloid load in the precuneus of cognitively intact older adults

The main pathophysiological alterations of Alzheimer's disease (AD) include loss of neuronal and synaptic integrity, amyloidogenic processing, and neuroinflammation. Similar alterations can, however, also be observed in cognitively intact older subjects and may prelude the clinical manifestation of AD. The objectives of this prospective cross-sectional study in a cohort of 38 cognitively intact older adults were twofold: (i) to investigate the latent relationship among cerebrospinal fluid (CSF) biomarkers reflecting the main pathophysiological processes of AD, and (ii) to assess the correlation between these biomarkers and gray matter volume as well as amyloid load. All subjects underwent extensive neuropsychological examinations, CSF sampling, [¹⁸ F]-flutemetamol amyloid positron emission tomography, and T₁ -weighted magnetic resonance imaging. A factor analysis revealed one factor that explained most of the variance in the CSF biomarker dataset clustering t-tau, α-synuclein, p-tau₁₈₁ , neurogranin, BACE1, visinin-like protein 1, chitinase-3-like protein 1 (YKL-40), Aβ_1-40 and Aβ_1-38 . Higher scores on this factor correlated with lower gray matter volume and with higher amyloid load in the precuneus. At the level of individual CSF biomarkers, levels of visinin-like protein 1, neurogranin, BACE1, Aβ_1-40 , Aβ_1-38, and YKL-40 all correlated inversely with gray matter volume of the precuneus. These findings demonstrate that in cognitively intact older subjects, CSF levels of synaptic and neuronal integrity biomarkers, amyloidogenic processing and measures of innate immunity (YKL-40) display a latent structure of common variance, which is associated with loss of structural integrity of brain regions implicated in the earliest stages of AD. OPEN SCIENCE BADGES: This article has received a badge for *Open Materials* because it provided all relevant information to reproduce the study in the manuscript, and for *Preregistration* because the study was pre-registered at https://osf.io/7qm9t/. The complete Open Science Disclosure form for this article can be found at the end of the article. More information about the Open Practices badges can be found at https://cos.io/our-services/open-science-badges/.

Single-word comprehension deficits in the nonfluent variant of primary progressive aphasia

BACKGROUND

A subset of patients with the nonfluent variant of primary progressive aphasia (PPA) exhibit concomitant single-word comprehension problems, constituting a 'mixed variant' phenotype. This phenotype is rare and currently not fully characterized. The aim of this study was twofold: to assess the prevalence and nature of single-word comprehension problems in the nonfluent variant and to study multimodal imaging characteristics of atrophy, tau, and amyloid burden associated with this mixed phenotype.

METHODS

A consecutive memory-clinic recruited series of 20 PPA patients (12 nonfluent, five semantic, and three logopenic variants) were studied on neurolinguistic and neuropsychological domains relative to 64 cognitively intact healthy older control subjects. The neuroimaging battery included high-resolution volumetric magnetic resonance imaging processed with voxel-based morphometry, and positron emission tomography with the tau-tracer [18F]-THK5351 and amyloid-tracer [11C]-Pittsburgh Compound B.

RESULTS

Seven out of 12 subjects who had been classified a priori with nonfluent variant PPA showed deficits on conventional single-word comprehension tasks along with speech apraxia and agrammatism, corresponding to a mixed variant phenotype. These mixed variant cases included three females and four males, with a mean age at onset of 65 years (range 44-77 years). Object knowledge and object recognition were additionally affected, although less severely compared with the semantic variant. The mixed variant was characterized by a distributed atrophy pattern in frontal and temporoparietal regions. A more focal pattern of elevated [18F]-THK5351 binding was present in the supplementary motor area, the left premotor cortex, midbrain, and basal ganglia. This pattern was closely similar to that seen in pure nonfluent variant PPA. At the individual patient level, elevated [18F]-THK5351 binding in the supplementary motor area and premotor cortex was present in six out of seven mixed variant cases and in five and four of these cases, respectively, in the thalamus and midbrain. Amyloid biomarker positivity was present in two out of seven mixed variant cases, compared with none of the five pure nonfluent cases.

CONCLUSIONS

A substantial proportion of PPA patients with speech apraxia and agrammatism also have single-word comprehension deficits. At the neurobiological level, the mixed variant shows a high degree of similarity with the pure nonfluent variant of PPA.

TRIAL REGISTRATION

EudraCT, 2014-002976-10 . Registered on 13-01-2015.

Amyloid-β, Tau, and Cognition in Cognitively Normal Older Individuals: Examining the Necessity to Adjust for Biomarker Status in Normative Data

We investigated whether amyloid-β (Aβ) and tau affected cognition in cognitively normal (CN) individuals, and whether norms for neuropsychological tests based on biomarker-negative individuals would improve early detection of dementia. We included 907 CN individuals from 8 European cohorts and from the Alzheimer's disease Neuroimaging Initiative. All individuals were aged above 40, had Aβ status and neuropsychological data available. Linear mixed models were used to assess the associations of Aβ and tau with five neuropsychological tests assessing memory (immediate and delayed recall of Auditory Verbal Learning Test, AVLT), verbal fluency (Verbal Fluency Test, VFT), attention and executive functioning (Trail Making Test, TMT, part A and B). All test except the VFT were associated with Aβ status and this influence was augmented by age. We found no influence of tau on any of the cognitive tests. For the AVLT Immediate and Delayed recall and the TMT part A and B, we calculated norms in individuals without Aβ pathology (Aβ- norms), which we validated in an independent memory-clinic cohort by comparing their predictive accuracy to published norms. For memory tests, the Aβ- norms rightfully identified an additional group of individuals at risk of dementia. For non-memory test we found no difference. We confirmed the relationship between Aβ and cognition in cognitively normal individuals. The Aβ- norms for memory tests in combination with published norms improve prognostic accuracy of dementia.

Large-scale brain network associated with creative insight: combined voxel-based morphometry and resting-state functional connectivity analyses

Creative insight occurs with an “Aha!” experience when solving a difficult problem. Here, we investigated large-scale networks associated with insight problem solving. We recruited 232 healthy participants aged 21–69 years old. Participants completed a magnetic resonance imaging study (MRI; structural imaging and a 10 min resting-state functional MRI) and an insight test battery (ITB) consisting of written questionnaires (matchstick arithmetic task, remote associates test, and insight problem solving task). To identify the resting-state functional connectivity (RSFC) associated with individual creative insight, we conducted an exploratory voxel-based morphometry (VBM)-constrained RSFC analysis. We identified positive correlations between ITB score and grey matter volume (GMV) in the right insula and middle cingulate cortex/precuneus, and a negative correlation between ITB score and GMV in the left cerebellum crus 1 and right supplementary motor area. We applied seed-based RSFC analysis to whole brain voxels using the seeds obtained from the VBM and identified insight-positive/negative connections, i.e. a positive/negative correlation between the ITB score and individual RSFCs between two brain regions. Insight-specific connections included motor-related regions whereas creative-common connections included a default mode network. Our results indicate that creative insight requires a coupling of multiple networks, such as the default mode, semantic and cerebral-cerebellum networks.

Language-related cerebral oscillatory changes are influenced equally by genetic and environmental factors

Twin studies have suggested that there are genetic influences on inter-individual variation in terms of verbal abilities, and candidate genes have been identified by genome-wide association studies. However, the brain activities under genetic influence during linguistic processing remain unclear. In this study, we investigated neuromagnetic activities during a language task in a group of 28 monozygotic (MZ) and 12 dizygotic (DZ) adult twin pairs. We examined the spatio-temporal distribution of the event-related desynchronizations (ERDs) in the low gamma band (25-50Hz) using beamformer analyses and time-frequency analyses. Heritability was evaluated by comparing the respective MZ and DZ correlations. The genetic and environmental contributions were then estimated by structural equation modeling (SEM). We found that the peaks of the low gamma ERDs were localized to the left frontal area. The power of low gamma ERDs in this area exhibited higher similarity between MZ twins than that between DZ twins. SEM estimated the genetic contribution as approximately 50%. In addition, these powers were negatively correlated with the behavioral verbal scores. These results improve our understanding of how genetic and environmental factors influence cerebral activities during linguistic processes.

β-Amyloid Deposition Is Associated with Decreased Right Prefrontal Activation during Task Switching among Cognitively Normal Elderly

The accumulation of β-amyloid (Aβ) peptides, a pathological hallmark of Alzheimer's disease (AD), has been associated with functional alterations, often in an episodic memory system with a particular emphasis on medial temporal lobe function. The topography of Aβ deposition, however, largely overlaps with frontoparietal control (FPC) regions implicated in cognitive control that has been shown to be impaired in early mild AD. To understand the neural mechanism underlying early changes in cognitive control with AD, we examined the impact of Aβ deposition on task-evoked FPC activation using functional magnetic resonance imaging (fMRI) in humans. Forty-three young and 62 cognitively normal older adults underwent an fMRI session during an executive contextual task in which task difficulty varied: single (either letter case or vowel/consonant judgment task) vs dual (switching between letter case and vowel/consonant decisions) task. Older subjects additionally completed (18)F-florbetaben positron emission tomography scans and were classified as either amyloid positive (Aβ+) or negative (Aβ-). Consistent with previous reports, age-related increases in brain activity were found in FPC regions commonly identified across groups. For both task conditions, Aβ-related increases in brain activity were found compared with baseline activity. For higher cognitive control load, however, Aβ+ elderly showed reduced task-switching activation in the right inferior frontal cortex. Our findings suggest that with Aβ deposition, brain activation in the cognitive control region reaches a maximum with lower control demand and decreases with higher control demand, which may underlie early impairment in cognitive control with AD progression.

SIGNIFICANCE STATEMENT

The accumulation of β-amyloid (Aβ) peptides, a pathological hallmark of Alzheimer's disease, spatially overlaps with frontoparietal control (FPC) regions implicated in cognitive control, but the impact of Aβ deposition on FPC regions is largely unknown. Using functional magnetic resonance imaging with a task-switching task, we found Aβ-related increases in FPC regions compared with baseline activity. For higher cognitive control load, however, Aβ-related hypoactivity was found in the right inferior frontal cortex, a region highly implicated in cognitive control. The findings suggest that with Aβ deposition, task-related brain activity may reach a plateau early and undergo downstream pathways of neural dysfunction, which may relate to the early impairment of cognitive control seen in the progression of Aβ pathology.

Classification of the primary progressive aphasias: principles and review of progress since 2011

Highly influential recommendations published in 2011 for the classification of the primary progressive aphasias (PPA) distinguished three subtypes: the semantic variant, the nonfluent/agrammatic variant, and the logopenic variant. We review empirical evidence published after 2011 that bears relevance to the validity of the recommended classification scheme. The studies that we review principally rely on monocentric, memory clinic-based consecutive series of PPA patients. We review whether a data-driven analysis of neurolinguistic test scores confirms the subtyping that was based on expert consensus, whether the 2011 subtyping covers the diversity of PPA in a comprehensive manner, and whether the proposed subgroups differ along dimensions that are not explicitly part of the defining criteria, such as diffusion tractography. Data-driven mathematical analyses of neurolinguistic data in PPA broadly confirm the presence of separate clusters corresponding to the subtypes but also leave 15–30 % unclassified. A comprehensive description of PPA requires the addition of the mixed variant as a fourth subtype and needs to leave room for cases fulfilling the criteria for a root diagnosis of PPA but not those of any of the three subtypes. Finally, given the limited predictive value of the clinical phenotype for the underlying neuropathology, biomarkers of the underlying pathology are likely of clinical utility in PPA.

Diagnostic value of cerebrospinal fluid Aβ ratios in preclinical Alzheimer's disease

INTRODUCTION

In this study of preclinical Alzheimer's disease (AD) we assessed the added diagnostic value of using cerebrospinal fluid (CSF) Aβ ratios rather than Aβ42 in isolation for detecting individuals who are positive on amyloid positron emission tomography (PET).

METHODS

Thirty-eight community-recruited cognitively intact older adults (mean age 73, range 65-80 years) underwent (18)F-flutemetamol PET and CSF measurement of Aβ1-42, Aβ1-40, Aβ1-38, and total tau (ttau). (18)F-flutemetamol retention was quantified using standardized uptake value ratios in a composite cortical region (SUVRcomp) with reference to cerebellar grey matter. Based on a prior autopsy validation study, the SUVRcomp cut-off was 1.57. Sensitivities, specificities and cut-offs were defined based on receiver operating characteristic analysis with CSF analytes as variables of interest and (18)F-flutemetamol positivity as the classifier. We also determined sensitivities and CSF cut-off values at fixed specificities of 90 % and 95 %.

RESULTS

Seven out of 38 subjects (18 %) were positive on amyloid PET. Aβ42/ttau, Aβ42/Aβ40, Aβ42/Aβ38, and Aβ42 had the highest accuracy to identify amyloid-positive subjects (area under the curve (AUC) ≥ 0.908). Aβ40 and Aβ38 had significantly lower discriminative power (AUC = 0.571). When specificity was fixed at 90 % and 95 %, Aβ42/ttau had the highest sensitivity among the different CSF markers (85.71 % and 71.43 %, respectively). Sensitivity of Aβ42 alone was significantly lower under these conditions (57.14 % and 42.86 %, respectively).

CONCLUSION

For the CSF-based definition of preclinical AD, if a high specificity is required, our data support the use of Aβ42/ttau rather than using Aβ42 in isolation.

Amyloid imaging in cognitively normal older adults: comparison between (18)F-flutemetamol and (11)C-Pittsburgh compound B

PURPOSE

Preclinical, or asymptomatic, Alzheimer's disease (AD) refers to the presence of positive AD biomarkers in the absence of cognitive deficits. This research concept is being applied to define target populations for clinical drug development. In a prospective community-recruited cohort of cognitively intact older adults, we compared two amyloid imaging markers within subjects: (18)F-flutemetamol and (11)C-Pittsburgh compound B (PIB).

METHODS

In 32 community-recruited cognitively intact older adults aged between 65 and 80 years, we determined the concordance between binary classification based on (18)F-flutemetamol versus (11)C-PIB according to semiquantitative assessment (standardized uptake value ratio in composite cortical volume, SUVRcomp) and, alternatively, according to visual reads. We also determined the correlation between (18)F-flutemetamol and (11)C-PIB SUVR and evaluated how this was affected by the reference region chosen (cerebellar grey matter versus pons) and the use of partial volume correction (PVC) in this population.

RESULTS

Binary classification based on semiquantitative assessment was concordant between (18)F-flutemetamol and (11)C-PIB in 94 % of cases. Concordance of blinded binary visual reads between tracers was 84 %. The Spearman correlation between (18)F-flutemetamol and (11)C-PIB SUVRcomp with cerebellar grey matter as reference region was 0.84, with a slope of 0.98. Correlations in neocortical regions were significantly lower with the pons as reference region. PVC improved the correlation in striatum and medial temporal cortex.

CONCLUSION

For the definition of preclinical AD based on (18)F-flutemetamol, concordance with (11)C-PIB was highest using semiquantitative assessment with cerebellar grey matter as reference region.

Brain Events Underlying Episodic Memory Changes in Aging: A Longitudinal Investigation of Structural and Functional Connectivity

Episodic memories are established and maintained by close interplay between hippocampus and other cortical regions, but degradation of a fronto-striatal network has been suggested to be a driving force of memory decline in aging. We wanted to directly address how changes in hippocampal-cortical versus striatal-cortical networks over time impact episodic memory with age. We followed 119 healthy participants (20-83 years) for 3.5 years with repeated tests of episodic verbal memory and magnetic resonance imaging for quantification of functional and structural connectivity and regional brain atrophy. While hippocampal-cortical functional connectivity predicted memory change in young, changes in cortico-striatal functional connectivity were related to change in recall in older adults. Within each age group, effects of functional and structural connectivity were anatomically closely aligned. Interestingly, the relationship between functional connectivity and memory was strongest in the age ranges where the rate of reduction of the relevant brain structure was lowest, implying selective impacts of the different brain events on memory. Together, these findings suggest a partly sequential and partly simultaneous model of brain events underlying cognitive changes in aging, where different functional and structural events are more or less important in various time windows, dismissing a simple uni-factorial view on neurocognitive aging.