Cognitively defined Alzheimer's dementia subgroups have distinct atrophy patterns

INTRODUCTION

We sought to determine structural magnetic resonance imaging (MRI) characteristics across subgroups defined based on relative cognitive domain impairments using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and to compare cognitively defined to imaging-defined subgroups.

METHODS

We used data from 584 people with Alzheimer's disease (AD) (461 amyloid positive, 123 unknown amyloid status) and 118 amyloid-negative controls. We used voxel-based morphometry to compare gray matter volume (GMV) for each group compared to controls and to AD-Memory.

RESULTS

There was pronounced bilateral lower medial temporal lobe atrophy with relative cortical sparing for AD-Memory, lower left hemisphere GMV for AD-Language, anterior lower GMV for AD-Executive, and posterior lower GMV for AD-Visuospatial. Formal asymmetry comparisons showed substantially more asymmetry in the AD-Language group than any other group (p = 1.15 × 10-10 ). For overlap between imaging-defined and cognitively defined subgroups, AD-Memory matched up with an imaging-defined limbic predominant group.

DISCUSSION

MRI findings differ across cognitively defined AD subgroups.

Autonomic dysregulation during sleep in Parkinsonian spectrum disorders - A proof of concept

INTRODUCTION

Autonomic dysfunction is common in α-synucleinopathies such as Lewy Body dementias (LBD), Parkinson's disease (PD), and isolated REM Sleep Behavior Disorder (iRBD). We analyzed pulse-rate changes during sleep to index autonomic nervous system (ANS) dysfunction in patients with α-synucleinopathies vs. non-synucleinopathy groups expected to have normal ANS function.

METHODS

Patients with LBD (n = 16), PD (PD, n = 14) or iRBD (n = 12) were compared to the non-synucleinopathy groups Alzheimers disease dementia (ADem, n = 26), mild cognitive impairment (MCI, n = 34) or controls (CG, n = 54). Sleep Profiler was used to derive a sleep autonomic activation index (AAI), i.e., ≥6 beat-per-minute increase/decrease, pulse rate coefficient of variation (PR-CV), and automated sleep staging with sleep-spindles and non-REM hypertonia (NRH). Analysis included statistical group comparisons and receiver operating characteristics curves to determine optimal classification of groups.

RESULTS

AAI and PR-CV were moderately correlated across all recordings (rs = 0.58, P < 0.0001), except in the LBD and PD groups. AAI but not PR-CV differentiated the LBD, PD and iRBD from non-Parkinsonian groups. AAI was decreased in LBD and PD patients compared to the CG (p < 0.003) and MCI (p < 0.03). AAI decreased based on age and its receiver operating characteristic area under the curve ranged from 0.63 to 0.75. AAI had a weak negative correlation to NRH (rs ≤ -0.26) but not sleep-spindles.

CONCLUSION

Synucleinopathy-related ANS dysfunction can reasonably discriminate prodromal and manifest PD/LBD diseased groups from non-synucleinopathies. Further studies incorporating AAI into a multivariate classifier of neurodegenerative disorders based on sleep characteristics acquired in the patient's home are planned.

Validation of the National Alzheimer's Coordinating Center (NACC) Lewy Body Disease Module neuropsychological tests

INTRODUCTION

This study assessed the construct validity and clinical utility of the National Alzheimer's Coordinating Center Lewy Body Dementia (LBD) Module, consisting of the Speeded Attention and Noise Pareidolia Tasks.

METHODS

Participants included 459 older adults diagnosed as cognitively normal (n = 202), or with non-amnestic mild cognitive impairment (n = 61), amnestic mild cognitive impairment (n = 96), Alzheimer's disease dementia (n = 44), or LBD (n = 56).

RESULTS

Speeded Attention demonstrated strong convergent validity and moderate discriminant validity when compared to established neuropsychological tests. Noise Pareidolia demonstrated strong discriminant validity, but limited convergent validity. Noise Pareidolia scores were significantly lower in those with reported hallucinations, delusions, or REM sleep behavior disorder symptoms. LBD Module tests discriminated well between cognitively normal adults and those with LBD.

DISCUSSION

The LBD Module demonstrates promising construct validity and clinical utility, which support its use across research and clinical settings.

Automated text-level semantic markers of Alzheimer's disease

INTRODUCTION

Automated speech analysis has emerged as a scalable, cost-effective tool to identify persons with Alzheimer's disease dementia (ADD). Yet, most research is undermined by low interpretability and specificity.

METHODS

Combining statistical and machine learning analyses of natural speech data, we aimed to discriminate ADD patients from healthy controls (HCs) based on automated measures of domains typically affected in ADD: semantic granularity (coarseness of concepts) and ongoing semantic variability (conceptual closeness of successive words). To test for specificity, we replicated the analyses on Parkinson's disease (PD) patients.

RESULTS

Relative to controls, ADD (but not PD) patients exhibited significant differences in both measures. Also, these features robustly discriminated between ADD patients and HC, while yielding near-chance classification between PD patients and HCs.

DISCUSSION

Automated discourse-level semantic analyses can reveal objective, interpretable, and specific markers of ADD, bridging well-established neuropsychological targets with digital assessment tools.

Association of cardiovascular risk burden with risk of dementia and brain pathologies: A population-based cohort study

INTRODUCTION

The impact of cardiovascular risk burden on brain pathologies remains unclear. We aimed to examine the association of the Framingham General Cardiovascular Risk Score (FGCRS) with dementia risk, and brain pathologies.

METHODS

Within the Rush Memory and Aging Project, 1588 dementia-free participants were assessed on FGCRS at baseline and followed up to 21 years. During the follow-up, 621 participants died and underwent autopsies.

RESULTS

The multi-adjusted hazard ratios (HRs) (95% confidence intervals [CIs]) of FGCRS were 1.03 (1.00-1.07) for dementia and 1.04 (1.01-1.07) for Alzheimer's disease (AD) dementia. Further, a higher FGCRS was associated with higher gross chronic cerebral infarctions (odds ratio [OR] 1.08, 95% CI 1.02-1.14), cerebral atherosclerosis (OR 1.10, 95% CI 1.03-1.17), and global AD pathology (OR 1.06, 95% CI 1.01-1.12).

CONCLUSIONS

A higher FGCRS is associated with an increased risk of dementia and AD dementia. Both vascular and AD pathologies in the brain may underlie this association.

Polygenic score modifies risk for Alzheimer's disease in APOE ε4 homozygotes at phenotypic extremes

INTRODUCTION

Diversity in cognition among apolipoprotein E (APOE) ε4 homozygotes can range from early-onset Alzheimer's disease (AD) to a lifetime with no symptoms.

METHODS

We evaluated a phenotypic extreme polygenic risk score (PRS) for AD between cognitively healthy APOE ε4 homozygotes aged ≥75 years (n = 213) and early-onset APOE ε4 homozygote AD cases aged ≤65 years (n = 223) as an explanation for this diversity.

RESULTS

The PRS for AD was significantly higher in APOE ε4 homozygote AD cases compared to older cognitively healthy APOE ε4/ε4 controls (odds ratio [OR] 8.39; confidence interval [CI] 2.0-35.2; P = .003). The difference in the same PRS between APOE ε3/ε3 extremes was not as significant (OR 3.13; CI 0.98-9.92; P = .053) despite similar numbers and power. There was no statistical difference in an educational attainment PRS between these age extreme case-controls.

DISCUSSION

A PRS for AD contributes to modified cognitive expression of the APOE ε4/ε4 genotype at phenotypic extremes of risk.

The "cognitive clock": A novel indicator of brain health

INTRODUCTION

We identified a "cognitive clock," a novel indicator of brain health that provides person-specific estimates of cognitive age, and tested the hypothesis that cognitive age is a better predictor of brain health than chronological age in two independent datasets.

METHODS

The initial analyses were based on 1057 participants from the Rush Memory and Aging Project and the Religious Orders Study who began without impairment and underwent cognitive assessments up to 24 years. A shape invariant model characterized the latent pattern of cognitive decline, conceptualized here as the "cognitive clock," and yielded person-specific estimates of cognitive age. Survival analyses examined cognitive versus chronological age for predicting Alzheimer's disease dementia, mild cognitive impairment and mortality, and regression analyses examined associations of cognitive versus chronological age with neuropathology and brain atrophy. Finally, we applied the cognitive clock to an independent validation sample of 2592 participants from the Chicago Health and Aging Project, a biracial population-based study, to confirm the predictive utility of cognitive age.

RESULTS

The "cognitive clock" showed that cognition remained stable until a cognitive age of about 80, then declined moderately until 90, then declined precipitously. In the initial dataset, cognitive age was a better predictor of dementia, mild cognitive impairment and mortality than chronological age, and was more strongly associated with neuropathology and brain atrophy. Application of the cognitive clock to the independent validation sample provided further support for the utility of cognitive age as a strong prognostic indicator of adverse outcomes.

DISCUSSION

Cognitive age is a robust prognostic indicator of adverse health outcomes and may serve as a useful biomarker in aging research.

P-tau/Aβ42 and Aβ42/40 ratios in CSF are equally predictive of amyloid PET status

INTRODUCTION

Measurement of amyloid beta (Aβ40 and Aβ42) and tau (phosphorylated tau [p-tau] and total tau [t-tau]) in cerebrospinal fluid (CSF) can be utilized to differentiate clinical and preclinical Alzheimer's disease dementia (AD) from other neurodegenerative processes.

METHODS

CSF biomarkers were measured in 150 participants from the Mayo Clinic Study of Aging and the Alzheimer's Disease Research Center. P-tau/Aβ42 (Roche Elecsys, Fujirebio LUMIPULSE) and Aβ42/40 (Fujirebio LUMIPULSE) ratios were compared to one another and to amyloid positron emission tomography (PET) classification.

RESULTS

Strong correlation was observed between LUMIPULSE p-tau/Aβ42 and Aβ42/40, as well as Elecsys and LUMIPULSE p-tau/Aβ42 and Aβ42/40 (Spearman's ρ = -0.827, -0.858, and 0.960, respectively). Concordance between LUMIPULSE p-tau/Aβ42 and Aβ42/40 was 96% and between Elecsys p-tau/Aβ42 and both LUMIPULSE ratios was 97%. All ratios had > 94% overall, positive, and negative percent agreement with amyloid PET classification.

DISCUSSION

These data suggest that p-tau/Aβ42 and Aβ42/40 ratios provide similar clinical information in the assessment of amyloid pathology.

The Association Between Biomarkers and Neuropsychiatric Symptoms Across the Alzheimer's Disease Spectrum

OBJECTIVE

To investigate the relationship between Alzheimer's disease biomarkers and neuropsychiatric symptoms.

METHODS

Data from two large cohort studies, the Dutch Parelsnoer Institute - Neurodegenerative Diseases and the Alzheimer's Disease Neuroimaging Initiative was used, including subjects with subjective cognitive decline (N = 650), mild cognitive impairment (N = 887), and Alzheimer's disease dementia (N = 626). Cerebrospinal fluid (CSF) levels of Aβ₄₂, t-tau, p-tau, and hippocampal volume were associated with neuropsychiatric symptoms (measured with the Neuropsychiatric Inventory) using multiple logistic regression analyses. The effect of the Mini-Mental State Examination (as proxy for cognitive functioning) on these relationships was assessed with mediation analyses.

RESULTS

Alzheimer's disease biomarkers were not associated with depression, agitation, irritability, and sleep disturbances. Lower levels of CSF Aβ₄₂, higher levels of t- and p-tau were associated with presence of anxiety. Lower levels of CSF Aβ₄₂ and smaller hippocampal volumes were associated with presence of apathy. All associations were mediated by cognitive functioning.

CONCLUSION

The association between Alzheimer's disease pathology and anxiety and apathy is partly due to impairment in cognitive functioning.

Biomarker-Based Prediction of Progression to Dementia: F-18 FDG-PET in Amnestic MCI

Background

Metabolic patterns on brain F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) can predict the decline in amnestic mild cognitive impairment (aMCI) to Alzheimer's disease dementia (AD) or other dementias.

Objective

This study was undertaken to evaluate the diagnostic accuracy of baseline F-18 FDG-PET in aMCI for predicting conversion to AD or other dementias on follow-up.

Patients and Methods

A total of 87 patients with aMCI were enrolled in the study. Each patient underwent a detailed clinical and neuropsychological examination and FDG-PET at baseline. Each PET scan was visually classified based on predefined dementia patterns. Automated analysis of FDG PET was performed using Cortex ID (GE Healthcare). The mean follow-up duration was 30.4 ± 9.3 months (range: 18-48 months). Diagnosis of dementia at follow-up (obtained using clinical diagnostic criteria) constituted the reference standard, and all the included aMCI patients were divided into two groups: the aMCI converters (MCI-C) and MCI nonconverters (MCI-NC). Diagnostic accuracy of FDG PET was calculated using this reference standard.

Results

There were 23 MCI-C and 64 MCI-NC. Of the 23 MCI-C, 19 were diagnosed as probable AD, 1 as frontotemporal demetia (FTD), and 3 as vascular dementia (VD). Of the 64 MCI-NC, 9 had subjective improvement in cognition, and 55 remained stable. The conversion rate for all types of dementia in our series was 26.4% (23/87) and for Alzheimer's type dementia was 21.8% (19/87). The of PET-based visual interpretation was 91.9%. Sensitivity, specificity, positive predictive value, and negative predictive value for FDG-PET-based prediction of dementia conversion were 86.9% [confidence interval (CI) 66.4%-97.2%)], 93.7% (CI 84.7%-98.2%), 83.3% (CI 65.6%-92.9%), and 95.2% (CI 87.4%-98.9%), respectively. Kappa for agreement between visual and Cortex ID was 0.94 indicating excellent agreement. In the three aMCI patients progressing to VD, no specific abnormality in metabolic pattern was noted; however, there was marked cortical atrophy on computed tomography.

Conclusion

FDG-PET-based visual and cortex ID classification has a good accuracy in predicting progression to dementia including AD in the prodromal aMCI phase. Absence of typical metabolic patterns on FDG-PET can play an important exclusionary role for progression to dementia. Vascular cognitive impairment with cerebral atrophy needs further studies to confirm and uncover potential mechanisms.

Association between enrollment factors and incident cognitive impairment in Blacks and Whites: Data from the Alzheimer's Disease Center

INTRODUCTION

We examined the influence of enrollment factors demonstrated to differ by race on incident mild cognitive impairment and dementia using Alzheimer's Disease Center data.

METHODS

Differences in rates of incident impairment between non-Latino Whites and Blacks (n = 12,242) were examined with age-at-progression survival models. Models included race, sex, education, source of recruitment, health factors, and family history of dementia.

RESULTS

No significant race differences in progression were observed in cognitively unimpaired participants. In those with mild cognitive impairment at baseline, Whites evidenced greater risk for progression than Blacks. Enrollment factors, for example, referral source, were significantly related to progression.

DISCUSSION

The finding that Blacks demonstrated lower rate of progression than Whites is contrary to the extant literature. Nested-regression analyses suggested that selection-related factors, differing by race, may account for these findings and influence our ability to accurately estimate risk for progression. It is potentially problematic to make racial comparisons using Alzheimer's Disease Center data sets.

FDG-PET and CSF biomarker accuracy in prediction of conversion to different dementias in a large multicentre MCI cohort

Background/aims

In this multicentre study in clinical settings, we assessed the accuracy of optimized procedures for FDG-PET brain metabolism and CSF classifications in predicting or excluding the conversion to Alzheimer's disease (AD) dementia and non-AD dementias.

Methods

We included 80 MCI subjects with neurological and neuropsychological assessments, FDG-PET scan and CSF measures at entry, all with clinical follow-up. FDG-PET data were analysed with a validated voxel-based SPM method. Resulting single-subject SPM maps were classified by five imaging experts according to the disease-specific patterns, as "typical-AD", "atypical-AD" (i.e. posterior cortical atrophy, asymmetric logopenic AD variant, frontal-AD variant), "non-AD" (i.e. behavioural variant FTD, corticobasal degeneration, semantic variant FTD; dementia with Lewy bodies) or "negative" patterns. To perform the statistical analyses, the individual patterns were grouped either as "AD dementia vs. non-AD dementia (all diseases)" or as "FTD vs. non-FTD (all diseases)". Aβ42, total and phosphorylated Tau CSF-levels were classified dichotomously, and using the Erlangen Score algorithm. Multivariate logistic models tested the prognostic accuracy of FDG-PET-SPM and CSF dichotomous classifications. Accuracy of Erlangen score and Erlangen Score aided by FDG-PET SPM classification was evaluated.

Results

The multivariate logistic model identified FDG-PET "AD" SPM classification (Expβ = 19.35, 95% C.I. 4.8-77.8, p < 0.001) and CSF Aβ42 (Expβ = 6.5, 95% C.I. 1.64-25.43, p < 0.05) as the best predictors of conversion from MCI to AD dementia. The "FTD" SPM pattern significantly predicted conversion to FTD dementias at follow-up (Expβ = 14, 95% C.I. 3.1-63, p < 0.001). Overall, FDG-PET-SPM classification was the most accurate biomarker, able to correctly differentiate either the MCI subjects who converted to AD or FTD dementias, and those who remained stable or reverted to normal cognition (Expβ = 17.9, 95% C.I. 4.55-70.46, p < 0.001).

Conclusions

Our results support the relevant role of FDG-PET-SPM classification in predicting progression to different dementia conditions in prodromal MCI phase, and in the exclusion of progression, outperforming CSF biomarkers.

Alzheimer's disease biomarker-guided diagnostic workflow using the added value of six combined cerebrospinal fluid candidates: Aβ1-42, total-tau, phosphorylated-tau, NFL, neurogranin, and YKL-40

INTRODUCTION

The diagnostic and classificatory performances of all combinations of three core (amyloid β peptide [i.e., Aβ_1-42], total tau [t-tau], and phosphorylated tau) and three novel (neurofilament light chain protein, neurogranin, and YKL-40) cerebrospinal fluid biomarkers of neurodegeneration were compared among individuals with mild cognitive impairment (n = 41), Alzheimer's disease dementia (ADD; n = 35), frontotemporal dementia (FTD; n = 9), and cognitively healthy controls (HC; n = 21), using 10-fold cross-validation.

METHODS

The combinations ranking in the top 10 according to diagnostic accuracy in differentiating between distinct diagnostic categories were identified.

RESULTS

The single biomarkers or biomarker combinations generating the best area under the receiver operating characteristics (AUROCs) were the following: the combination [amyloid β peptide + phosphorylated tau + neurofilament light chain] for distinguishing between ADD patients and HC (AUROC = 0.86), t-tau for distinguishing between ADD and FTD patients (AUROC = 0.82), and t-tau for distinguishing between FTD patients and HC (AUROC = 0.78).

CONCLUSIONS

Novel and established cerebrospinal fluid markers perform with at least fair accuracy in the discrimination between ADD and FTD. The classification of mild cognitive impairment individuals was poor.

Longitudinal uncoupling of cerebral perfusion, glucose metabolism, and tau deposition in Alzheimer's disease

INTRODUCTION

Cross-sectional findings using the tau tracer [¹⁸F]THK5317 (THK5317) have shown that [¹⁸F]fluorodeoxyglucose (FDG) positron emission tomography (PET) data can be approximated using perfusion measures (early-frame standardized uptake value ratio; ratio of tracer delivery in target to reference regions). In this way, a single PET study can provide both functional and molecular information.

METHODS

We included 16 patients with Alzheimer's disease who completed follow-up THK5317 and FDG studies 17 months after baseline investigations. Linear mixed-effects models and annual percentage change maps were used to examine longitudinal change.

RESULTS

Limited spatial overlap was observed between areas showing declines in THK5317 perfusion measures and FDG. Minimal overlap was seen between areas showing functional change and those showing increased retention of THK5317.

DISCUSSION

Our findings suggest a spatiotemporal offset between functional changes and tau pathology and a partial uncoupling between perfusion and metabolism, possibly as a function of Alzheimer's disease severity.

AD dementia risk in late MCI, in early MCI, and in subjective memory impairment

OBJECTIVE

To compare the risk of developing Alzheimer's disease (AD) dementia in late mild cognitive impairment (LMCI), early MCI (EMCI), and subjective memory impairment (SMI) with normal test performance.

METHODS

The baseline sample (n = 2892) of the prospective cohort study in nondemented individuals (German Study on Aging, Cognition and Dementia in Primary Care Patients) was divided into LMCI, EMCI, SMI, and control subjects by delayed recall performance. These groups were subdivided by the presence of self-reported concerns associated with experienced memory impairment. AD dementia risk was assessed over 6 years.

RESULTS

Across all groups, risk of AD dementia was greatest in LMCI. In those with self-reported concerns regarding their memory impairment, SMI and EMCI were associated with a similarly increased risk of AD dementia. In those subgroups without concerns, SMI was not associated with increased risk of AD dementia, but EMCI remained an at-risk condition.

CONCLUSIONS

SMI and EMCI with self-reported concerns were associated with the same risk of AD dementia, suggesting that pre-LMCI risk conditions should be extended to SMI with concerns.