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

Interaction Between Arteriosclerosis and Amyloid-β on Cognitive Function

Background: Dementia is a multifactorial disease, with Alzheimer’s disease (AD) and vascular pathology often co-occurring in many individuals with dementia. Yet, the interplay between AD and vascular pathology in cognitive decline is largely undetermined. Objective: The aim of the present study was to examine the joint effect of arteriosclerosis and AD pathology on cognition in the general population without dementia. Methods: We determined the interaction between blood-based AD biomarkers and CT-defined arteriosclerosis on cognition in 2,229 dementia-free participants of the population-based Rotterdam Study (mean age: 68.9 years, 52% women) crosssectionally. Results: Amyloid-β (Aβ)42 and arterial calcification were associated with cognitive performance. After further adjustment for confounders in a model that combined all biomarkers, only arterial calcification remained independently associated with cognition. There was a significant interaction between arterial calcification and Aβ42 and between arterial calcification and the ratio of Aβ42/40. Yet, estimates attenuated, and interactions were no longer statistically significant after adjustment for cardio metabolic risk factors. Conclusions: Arteriosclerosis and AD display additive interaction-effects on cognition in the general population, that are due in part to cardio metabolic risk factors. These findings suggest that joint assessment of arteriosclerosis and AD pathology is important for understanding of disease etiology in individuals with cognitive impairment.</p

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

Association of amyloid-beta with depression or depressive symptoms in older adults without dementia: a systematic review and meta-analysis

Several lines of evidence have indicated that depression might be a prodromal symptom of Alzheimer’s disease (AD). This systematic review and meta-analysis investigated the cross-sectional association between amyloid-beta, one of the key pathologies defining AD, and depression or depressive symptoms in older adults without dementia. A systematic search in PubMed yielded 689 peer-reviewed articles. After full-text screening, nine CSF studies, 11 PET studies, and five plasma studies were included. No association between amyloid-beta and depression or depressive symptoms were found using cerebrospinal fluid (CSF) (0.15; 95% CI: −0.08; 0.37), positron emission topography (PET) (Cohen’s d: 0.09; 95% CI: −0.05; 0.24), or plasma (−0.01; 95% CI: −0.23; 0.22). However, subgroup analyses revealed an association in plasma studies of individuals with cognitive impairment. A trend of an association was found in the studies using CSF and PET. This systematic review and meta-analysis suggested that depressive symptoms may be part of the prodromal stage of dementia

Cerebrospinal fluid VILIP-1 and YKL-40, candidate biomarkers to diagnose, predict and monitor Alzheimer’s disease in a memory clinic cohort

INTRODUCTION: We examined the utility of cerebrospinal fluid (CSF) proteins, Chitinase-3-like protein 1 (CHI3L1 or YKL-40), a putative marker of inflammation, and Visinin-like protein-1 (VILIP-1), a marker for neuronal injury, for diagnostic classification and monitoring of disease progression in a memory clinic cohort. METHODS: CSF levels of YKL-40 and VILIP-1 were measured in 37 cognitively normal, 61 Mild Cognitive Impairment (MCI) and 65 Alzheimer’s disease (AD) patients from the memory clinic-based Amsterdam Dementia Cohort who underwent two lumbar punctures, with minimum interval of 6 months and a mean(SE) interval of 2.0(0.1) years. Mean(SE) cognitive follow-up was 3.8 (0.2) years. ANOVA was used to compare baseline differences of log-transformed CSF measures. Cox proportional hazard models were used to evaluate disease progression as a function of CSF tertiles. Linear mixed models were used to evaluate longitudinal change over time. All analyses were sex and age adjusted. RESULTS: Baseline levels of YKL-40, but not VILIP-1, were higher in MCI and AD patients compared to cognitively normal individuals (mean (SE) pg/mL, 304 (16) and 288 (12) vs. 231 (16), p = 0.03 and p = 0.006). Baseline levels of both YKL-40 and VILIP-1 in MCI predicted progression to AD (HR 95 % CI = 3.0 (1.1–7.9) and 4.4 (1.5–13.0), respectively, for highest vs. lowest tertile). YKL-40 increased longitudinally in patients with MCI and AD (mean (SE) pg/mL per year, 8.9 (3.0) and 7.1 (3.1), respectively), but not in cognitively normal individuals, whereas levels of VILIP-1 increased only in MCI (mean (SE), 10.7 (2.6) pg/mL per year). CONCLUSIONS: CSF levels of YKL-40 may have utility for discriminating between cognitively normal individuals and patients with MCI or AD. Increased levels of both YKL-40 and VILIP-1 may be associated with disease progression. These CSF biomarkers should be considered for future evaluation in the characterization of the natural history of AD

Computerized decision support is an effective approach to select memory clinic patients for amyloid-PET

Background: The use of amyloid-PET in dementia workup is upcoming. At the same time, amyloid-PET is costly and limitedly available. While the appropriate use criteria (AUC) aim for optimal use of amyloid-PET, their limited sensitivity hinders the translation to clinical practice. Therefore, there is a need for tools that guide selection of patients for whom amyloid-PET has the most clinical utility. We aimed to develop a computerized decision support approach to select patients for amyloid-PET. // Methods: We included 286 subjects (135 controls, 108 Alzheimer’s disease dementia, 33 frontotemporal lobe dementia, and 10 vascular dementia) from the Amsterdam Dementia Cohort, with available neuropsychology, APOE, MRI and [18F]florbetaben amyloid-PET. In our computerized decision support approach, using supervised machine learning based on the DSI classifier, we first classified the subjects using only neuropsychology, APOE, and quantified MRI. Then, for subjects with uncertain classification (probability of correct class (PCC) < 0.75) we enriched classification by adding (hypothetical) amyloid positive (AD-like) and negative (normal) PET visual read results and assessed whether the diagnosis became more certain in at least one scenario (PPC≥0.75). If this was the case, the actual visual read result was used in the final classification. We compared the proportion of PET scans and patients diagnosed with sufficient certainty in the computerized approach with three scenarios: 1) without amyloid-PET, 2) amyloid-PET according to the AUC, and 3) amyloid-PET for all patients. // Results: The computerized approach advised PET in n = 60(21%) patients, leading to a diagnosis with sufficient certainty in n = 188(66%) patients. This approach was more efficient than the other three scenarios: 1) without amyloid-PET, diagnostic classification was obtained in n = 155(54%), 2) applying the AUC resulted in amyloid-PET in n = 113(40%) and diagnostic classification in n = 156(55%), and 3) performing amyloid-PET in all resulted in diagnostic classification in n = 154(54%). // Conclusion: Our computerized data-driven approach selected 21% of memory clinic patients for amyloid-PET, without compromising diagnostic performance. Our work contributes to a cost-effective implementation and could support clinicians in making a balanced decision in ordering additional amyloid PET during the dementia workup