Grey matter network markers identify individuals with prodromal Alzheimer's disease who will show rapid clinical decline

Individuals with prodromal Alzheimer's disease show considerable variability in rates of cognitive decline, which hampers the ability to detect potential treatment effects in clinical trials. Prognostic markers to select those individuals who will decline rapidly within a trial time frame are needed. Brain network measures based on grey matter covariance patterns have been associated with future cognitive decline in Alzheimer's disease. In this longitudinal cohort study, we investigated whether cut-offs for grey matter networks could be derived to detect fast disease progression at an individual level. We further tested whether detection was improved by adding other biomarkers known to be associated with future cognitive decline [i.e. CSF tau phosphorylated at threonine 181 (p-tau181) levels and hippocampal volume]. We selected individuals with mild cognitive impairment and abnormal CSF amyloid β1-42 levels from the Amsterdam Dementia Cohort and the Alzheimer's Disease Neuroimaging Initiative, when they had available baseline structural MRI and clinical follow-up. The outcome was progression to dementia within 2 years. We determined prognostic cut-offs for grey matter network properties (gamma, lambda and small-world coefficient) using time-dependent receiver operating characteristic analysis in the Amsterdam Dementia Cohort. We tested the generalization of cut-offs in the Alzheimer's Disease Neuroimaging Initiative, using logistic regression analysis and classification statistics. We further tested whether combining these with CSF p-tau181 and hippocampal volume improved the detection of fast decliners. We observed that within 2 years, 24.6% (Amsterdam Dementia Cohort, n = 244) and 34.0% (Alzheimer's Disease Neuroimaging Initiative, n = 247) of prodromal Alzheimer's disease patients progressed to dementia. Using the grey matter network cut-offs for progression, we could detect fast progressors with 65% accuracy in the Alzheimer's Disease Neuroimaging Initiative. Combining grey matter network measures with CSF p-tau and hippocampal volume resulted in the best model fit for classification of rapid decliners, increasing detecting accuracy to 72%. These data suggest that single-subject grey matter connectivity networks indicative of a more random network organization can contribute to identifying prodromal Alzheimer's disease individuals who will show rapid disease progression. Moreover, we found that combined with p-tau and hippocampal volume this resulted in the highest accuracy. This could facilitate clinical trials by increasing chances to detect effects on clinical outcome measures

Disease Course Varies According to Age and Symptom Length in Alzheimer's Disease

Health-care professionals, patients, and families seek as much information as possible about prognosis for patients with Alzheimer’s disease (AD); however, we do not yet have a robust understanding of how demographic factors predict prognosis. We evaluated associations between age at presentation, age of onset, and symptom length with cognitive decline as measured using the Mini-Mental State Examination (MMSE) and Clinical Dementia Rating sum-of-boxes (CDR-SOB) in a large dataset of AD patients. Age at presentation was associated with post-presentation decline in MMSE (p < 0.001), with younger patients showing faster decline. There was little evidence of an association with change in CDR-SOB. Symptom length, rather than age, was the strongest predictor of MMSE and CDR-SOB at presentation, with increasing symptom length associated with worse outcomes. The evidence that younger AD patients have a more aggressive disease course implies that early diagnosis is essential

Impact of sharing Alzheimer's disease biomarkers with individuals without dementia:A systematic review and meta-analysis of empirical data

Introduction: We conducted a systematic literature review and meta-analysis of empirical evidence on expected and experienced implications of sharing Alzheimer's disease (AD) biomarker results with individuals without dementia. Methods: PubMed, Embase, APA PsycInfo, and Web of Science Core Collection were searched according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Results from included studies were synthesized, and quantitative data on psychosocial impact were meta-analyzed using a random-effects model. Results: We included 35 publications. Most personal stakeholders expressed interest in biomarker assessment. Learning negative biomarker results led to relief and sometimes frustration, while positive biomarkers induced anxiety but also clarity. Meta-analysis of five studies including 2012 participants (elevated amyloid = 1324 [66%], asymptomatic = 1855 [92%]) showed short-term psychological impact was not significant (random-effect estimate = 0.10, standard error = 0.23, P = 0.65). Most professional stakeholders valued biomarker testing, although attitudes and practices varied considerably. Discussion: Interest in AD biomarker testing was high and sharing their results did not cause psychological harm. Highlights: Most personal stakeholders expressed interest in Alzheimer's disease biomarker assessment. Personal motivations included gaining insight, improving lifestyle, or preparing for the future. There was no short-term psychological impact of sharing biomarker status, implying it can be safe. Most professional stakeholders valued biomarker testing, believing the benefits outweigh the risk. Harmonized guidelines on biomarker testing and sharing results are required.</p

Association of the ATN Research Framework With Clinical Profile, Ccognitive Decline, and Mortality in Patients With Dementia With Lewy Bodies

Background and Objectives: The ATN framework has been developed to categorize biological processes within the Alzheimer’s disease (AD) continuum. Since AD pathology often coincides with dementia with Lewy Bodies (DLB), we aimed to investigate the distribution of ATN profiles in DLB and associate ATN-profiles in DLB to prognosis. / Methods: We included 202 DLB patients from the Amsterdam Dementia Cohort (68±7yrs, 19%F, MMSE: 24±3, DAT-SPECT abnormal: 105/119). Patients were classified into eight profiles according to the ATN framework, using CSF Aβ42 (A), CSF p-tau (T) and medial temporal atrophy scores (N). We compared presence of clinical symptoms in ATN profiles and used linear mixed models to analyze decline on cognitive tests (follow-up 3±2yrs for n=139). Mortality risk was assessed using Cox proportional hazards analysis. Analyses were performed on both the eight profiles, as well as three clustered categories (normal AD biomarkers, non-AD pathologic change, AD continuum). / Results: Fifty (25%) DLB patients had normal AD biomarkers (A-T-N-), 37 (18%) had non-AD pathologic change (A-T+N-: 10%/A-T-N+: 6%/A-T+N+: 3%) and 115 (57%) were classified within the AD continuum (A+T-N-: 20%/A+T+N-: 16%/A+T-N+: 10%/A+T+N+: 9%). A+T+N+ patients were older and least often had RBD symptoms. Parkinsonism was more often present in A+T-, compared to A-T+ (independent of N). Compared to patients with normal AD biomarkers, patients in A+ categories showed steeper decline on memory tests and higher mortality risk. Cognitive decline and mortality did not differ between non-AD pathologic change and normal AD biomarkers. / Discussion: In our DLB cohort, we found clinically relevant associations between ATN categories and disease manifestation. Patients within the AD continuum had steeper cognitive decline and shorter survival. Implementing the ATN framework within DLB patients aids in subtyping patients based on underlying biological processes and could provide targets for future treatment strategies, e.g. AD modifying treatment. Expanding the framework by incorporating markers for alpha-synucleinopathy would improve the use of the framework to characterize dementia patients with mixed pathology, which could enhance proper stratification of patients for therapeutic trials

Trajectories and Determinants of Quality of Life in Dementia with Lewy Bodies and Alzheimer's Disease

Background: Quality of Life (QoL) is an important outcome measure in dementia, particularly in the context of interventions. Research investigating longitudinal QoL in dementia with Lewy bodies (DLB) is currently lacking. Objective: To investigate determinants and trajectories of QoL in DLB compared to Alzheimer’s disease (AD) and controls. Methods: QoL was assessed annually in 138 individuals, using the EQ5D-utility-score (0–100) and the health-related Visual Analogue Scale (VAS, 0–100). Twenty-nine DLB patients (age 69 ± 6), 68 AD patients (age 70 ± 6), and 41 controls (age 70 ± 5) were selected from the Dutch Parelsnoer Institute-Neurodegenerative diseases and Amsterdam Dementia Cohort. We examined clinical work-up over time as determinants of QoL, including cognitive tests, neuropsychiatric inventory, Geriatric Depression Scale (GDS), and disability assessment of dementia (DAD). Results: Mixed models showed lower baseline VAS-scores in DLB compared to AD and controls (AD: ±SE = -7.6 ± 2.8, controls: ±SE = -7.9 ± 3.0, p < 0.05). An interaction between diagnosis and time since diagnosis indicated steeper decline on VAS-scores for AD patients compared to DLB patients (±SE = 2.9 ± 1.5, p < 0.1). EQ5D-utility-scores over time did not differ between groups. Higher GDS and lower DAD-scores were independently associated with lower QoL in dementia patients (GDS: VAS ±SE = -1.8 ± 0.3, EQ5D-utility ±SE = -3.7 ± 0.4; DAD: VAS = 0.1 ± 0.0, EQ5D-utility ±SE = 0.1 ± 0.1, p < 0.05). No associations between cognitive tests and QoL remained in the multivariate model. Conclusion: QoL is lower in DLB, while in AD QoL shows steepe

Cerebral Blood Flow and Cognitive Functioning in a Community-Based, Multi-Ethnic Cohort: The SABRE Study

Introduction: Lower cerebral blood flow (CBF) is associated with cardiovascular disease and vascular risk factors, and is increasingly acknowledged as an important contributor to cognitive decline and dementia. In this cross-sectional study, we examined the association between CBF and cognitive functioning in a community-based, multi-ethnic cohort.Methods: From the SABRE (Southall and Brent Revisited) study, we included 214 European, 151 South Asian and 87 African Caribbean participants (71 ± 5 years; 39%F). We used 3T pseudo-continuous arterial spin labeling to estimate whole-brain, hematocrit corrected CBF. We measured global cognition and three cognitive domains (memory, executive functioning/attention and language) with a neuropsychological test battery. Associations were investigated using linear regression analyses, adjusted for demographic variables, vascular risk factors and MRI measures.Results: Across groups, we found an association between higher CBF and better performance on executive functioning/attention (standardized ß [stß] = 0.11, p &lt; 0.05). Stratification for ethnicity showed associations between higher CBF and better performance on memory and executive functioning/attention in the white European group (stß = 0.14; p &lt; 0.05 and stß = 0.18; p &lt; 0.01 respectively), associations were weaker in the South Asian and African Caribbean groups.Conclusions: In a multi-ethnic community-based cohort we showed modest associations between CBF and cognitive functioning. In particular, we found an association between higher CBF and better performance on executive functioning/attention and memory in the white European group. The observations are consistent with the proposed role of cerebral hemodynamics in cognitive decline

Microglial activation in Alzheimer's disease: an (R)-[11C]PK11195 positron emission tomography study

AbstractInflammatory mechanisms, like microglial activation, could be involved in the pathogenesis of Alzheimer's disease (AD). (R)-[11C]PK11195 (1-(2-chlorophenyl)-N-methyl-N-1(1-methylpropyl)-3-isoquinolinecarboxamide), a positron emission tomography (PET) ligand, can be used to quantify microglial activation in vivo. The purpose of this study was to assess whether increased (R)-[11C]PK11195 binding is present in AD and mild cognitive impairment (MCI), currently also known as “prodromal AD.”MethodsNineteen patients with probable AD, 10 patients with prodromal AD (MCI), and 21 healthy control subjects were analyzed. Parametric images of binding potential (BPND) of (R)-[11C]PK11195 scans were generated using receptor parametric mapping (RPM) with supervised cluster analysis. Differences between subject groups were tested using mixed model analysis, and associations between BPND and cognition were evaluated using Pearson correlation coefficients.ResultsVoxel-wise statistical parametric mapping (SPM) analysis showed small clusters of significantly increased (R)-[11C]PK11195 BPND in occipital lobe in AD dementia patients compared with healthy control subjects. Regions of interest (ROI)-based analyses showed no differences, with large overlap between groups. There were no differences in (R)-[11C]PK11195 BPND between clinically stable prodromal AD patients and those who progressed to dementia, and BPND did not correlate with cognitive function.ConclusionMicroglial activation is a subtle phenomenon occurring in AD

Associations Between Nutrient Intake and Corresponding Nutritional Biomarker Levels in Blood in a Memory Clinic Cohort:The NUDAD Project

Diet is a promising intervention target to prevent or slow Alzheimer's disease (AD). Early (predementia) stages of AD offer a unique opportunity for dietary interventions. Nutritional assessment methods to estimate nutrient intake have, however, not been validated in clinical populations. Hence, we assessed the association between nutrient intake assessed by food frequency questionnaire (FFQ) and nutrient status measured by nutritional biomarkers in blood in a clinical sample of controls, mild cognitive impairment (MCI), and patients with AD

Repeatability of parametric methods for [F-18]florbetapir imaging in Alzheimer's disease and healthy controls:A test-retest study

Accumulation of amyloid beta (Aβ) is one of the pathological hallmarks of Alzheimer’s disease (AD), which can be visualized using [18F]florbetapir positron emission tomography (PET). The aim of this study was to evaluate various parametric methods and to assess their test-retest (TRT) reliability. Two 90 min dynamic [18F]florbetapir PET scans, including arterial sampling, were acquired (n = 8 AD patient, n = 8 controls). The following parametric methods were used; (reference:cerebellum); Logan and spectral analysis (SA), receptor parametric mapping (RPM), simplified reference tissue model2 (SRTM2), reference Logan (rLogan) and standardized uptake value ratios (SUVr(50–70)). BPND+1, DVR, VT and SUVr were compared with corresponding estimates (VT or DVR) from the plasma input reversible two tissue compartmental (2T4k_VB) model with corresponding TRT values for 90-scan duration. RPM (r2 = 0.92; slope = 0.91), Logan (r2 = 0.95; slope = 0.84) and rLogan (r2 = 0.94; slope = 0.88), and SRTM2 (r2 = 0.91; slope = 0.83), SA (r2 = 0.91; slope = 0.88), SUVr (r2 = 0.84; slope = 1.16) correlated well with their 2T4k_VB counterparts. RPM (controls: 1%, AD: 3%), rLogan (controls: 1%, AD: 3%) and SUVr(50–70) (controls: 3%, AD: 8%) showed an excellent TRT reliability. In conclusion, most parametric methods showed excellent performance for [18F]florbetapir, but RPM and rLogan seem the methods of choice, combining the highest accuracy and best TRT reliability

Accelerating regional atrophy rates in the progression from normal aging to Alzheimer’s disease

We investigated progression of atrophy in vivo, in Alzheimer’s disease (AD), and mild cognitive impairment (MCI). We included 64 patients with AD, 44 with MCI and 34 controls with serial MRI examinations (interval 1.8 ± 0.7 years). A nonlinear registration algorithm (fluid) was used to calculate atrophy rates in six regions: frontal, medial temporal, temporal (extramedial), parietal, occipital lobes and insular cortex. In MCI, the highest atrophy rate was observed in the medial temporal lobe, comparable with AD. AD patients showed even higher atrophy rates in the extramedial temporal lobe. Additionally, atrophy rates in frontal, parietal and occipital lobes were increased. Cox proportional hazard models showed that all regional atrophy rates predicted conversion to AD. Hazard ratios varied between 2.6 (95% confidence interval (CI) = 1.1–6.2) for occipital atrophy and 15.8 (95% CI = 3.5–71.8) for medial temporal lobe atrophy. In conclusion, atrophy spreads through the brain with development of AD. MCI is marked by temporal lobe atrophy. In AD, atrophy rate in the extramedial temporal lobe was even higher. Moreover, atrophy rates also accelerated in parietal, frontal, insular and occipital lobes. Finally, in nondemented elderly, medial temporal lobe atrophy was most predictive of progression to AD, demonstrating the involvement of this region in the development of AD