Cognivue Clarity® characterizes amyloid status and preclinical Alzheimer's disease in biomarker confirmed cohorts in the Bio-Hermes Study

BackgroundAn easy and reliable method for detection of Alzheimer's Disease (AD) and mild cognitive impairment (MCI) is critical for clinical trial enrollment. In the era of amyloid‐lowering therapies, there is a need to identify individuals likely to have amyloid to enrich recruitment and lower costs related to amyloid PET. In addition, a subset of cognitively normal individuals have amyloid deposition (Preclinical AD) but to date there is no cognitive assessment or screening method that can detect these individuals in the absence of expensive biomarkers. Cognivue Clarity is an adaptive psychophysics computerized cognitive assessment generating a global score and 10 subtest scores.MethodsAs part of the Bio‐Hermes study, sponsored by the Global Alzheimer’s Platform Foundation, Cognivue Clarity was administered to 964 individuals who also had amyloid PET, plasma amyloid and tau measures, ApoE genotyping, MMSE, Functional Activities Questionnaire (FAQ), and Rey Auditory Verbal Learning Task (RAVLT). Cognivue Clarity performance was compared between (1) clinically‐defined, (2) biomarker‐defined, and (3) clinicopathological‐defined groups.ResultsThe sample had a mean age of 72.0 ± 6.7y, 15.5 ± 2.7y education, 55.9% females and 23.0% individuals from underrepresented groups. Clinical groups included 42.8% Healthy, 31.6% MCI, and 25.5% Probable AD. Amyloid PET was positive in 62.7%. Clinicopathological groups included 33.5% Healthy, 10.3% Preclinical AD, 27.2% MCI/AD, and 29.1% non‐AD. While Cognivue, MMSE, FAQ, and RAVLT scores were different between impaired vs unimpaired and amyloid positive vs amyloid negative individuals, only Cognivue Clarity was different between Healthy vs Preclinical AD (p=.009). Three subtests [Shape Discrimination (p=.002), Visual Salience (p=.005), Adaptive Motor Control (p=.004)] and their mean (p<.001) differentiated True Controls from Preclinical AD with an area under the curve of 0.634 (95%CI:0.570‐0.698, p<.001) and were moderately correlated with Amyloid PET Centiloid (r=‐.308) and pTau217 (r=‐.315). ApoE carriers had lower scores than non‐carriers (p=.02).ConclusionsCognivue Clarity, a 10‐minute computerized cognitive battery, can detect individuals with cognitive impairment and identify individuals likely to have amyloid positivity. Cognivue Clarity is the first test able to identify individuals with Preclinical AD. This has great potential as an enrichment strategy for AD clinical trials testing amyloid‐lowering therapies and AD prevention.

Decision letter: Stage-dependent differential influence of metabolic and structural networks on memory across Alzheimer’s disease continuum

Circadian fragmentation: a harbinger of Alzheimer's disease?

The literature on cognitive markers in preclinical AD is reviewed. The findings demonstrate that impairment in multiple cognitive domains is typically observed several years before clinical diagnosis. Measures of executive functioning, episodic memory and perceptual speed appear to be most effective at identifying at-risk individuals. The fact that these cognitive domains are most implicated in normal cognitive aging suggests that the cognitive deficit observed preclinically is not qualitatively different from that observed in normal aging. The degree of cognitive impairment prior to the diagnosis of Alzheimer's disease (AD) appears to generalize relatively well across major study characteristics, including sample ascertainment procedures, age and cognitive status of participants, as well as time to diagnosis of dementia. In episodic memory, there is evidence that the size of the preclinical deficit increases with increasing cognitive demands. The global cognitive impairment observed is highly consistent with observations that multiple brain structures and functions are affected long before the diagnosis of AD. However, there is substantial overlap in the distribution of cognitive scores between those who will and those who will not be diagnosed with AD, hence limiting the clinical utility of cognitive markers for early identification of cases. Future research should consider combining cognitive indicators with other types of markers (i.e. social, somatic, genetic, brain-based) in order to increase prediction accuracy.

High amyloid has been associated with substantial episodic memory decline over 18 and 36 months in healthy older adults and individuals with mild cognitive impairment. However, the nature and magnitude of amyloid-related memory and non-memory change from the preclinical to the clinical stages of Alzheimer's disease has not been evaluated over the same time interval. Healthy older adults (n = 320), individuals with mild cognitive impairment (n = 57) and individuals with Alzheimer's disease (n = 36) enrolled in the Australian Imaging, Biomarkers and Lifestyle study underwent at least one positron emission tomography neuroimaging scan for amyloid. Cognitive assessments were conducted at baseline, and 18- and 36-month follow-up assessments. Compared with amyloid-negative healthy older adults, amyloid-positive healthy older adults, and amyloid-positive individuals with mild cognitive impairment and Alzheimer's disease showed moderate and equivalent decline in verbal and visual episodic memory over 36 months (d's = 0.47-0.51). Relative to amyloid-negative healthy older adults, amyloid-positive healthy older adults showed no decline in non-memory functions, but amyloid-positive individuals with mild cognitive impairment showed additional moderate decline in language, attention and visuospatial function (d's = 0.47-1.12), and amyloid-positive individuals with Alzheimer's disease showed large decline in all aspects of memory and non-memory function (d's = 0.73-2.28). Amyloid negative individuals with mild cognitive impairment did not show any cognitive decline over 36 months. When non-demented individuals (i.e. healthy older adults and adults with mild cognitive impairment) were further dichotomized, high amyloid-positive non-demented individuals showed a greater rate of decline in episodic memory and language when compared with low amyloid positive non-demented individuals. Memory decline does not plateau with increasing disease severity, and decline in non-memory functions increases in amyloid-positive individuals with mild cognitive impairment and Alzheimer's disease. The combined detection of amyloid positivity and objectively-defined decline in memory are reliable indicators of early Alzheimer's disease, and the detection of decline in non-memory functions in amyloid-positive individuals with mild cognitive impairment may assist in determining the level of disease severity in these individuals. Further, these results suggest that grouping amyloid data into at least two categories of abnormality may be useful in determining the disease risk level in non-demented individuals.

Editor's evaluation: Multimodal brain age estimates relate to Alzheimer disease biomarkers and cognition in early stages: a cross-sectional observational study

Decision letter: Multimodal brain age estimates relate to Alzheimer disease biomarkers and cognition in early stages: a cross-sectional observational study

Alzheimer's disease biomarkers are widely accepted as surrogate markers of underlying neuropathological changes. However, few studies have evaluated whether preclinical Alzheimer's disease biomarkers predict Alzheimer's neuropathology at autopsy. We sought to determine whether amyloid PET imaging or CSF biomarkers accurately predict cognitive outcomes and Alzheimer's disease neuropathological findings. This study included 720 participants, 42-91 years of age, who were enrolled in longitudinal studies of memory and aging in the Washington University Knight Alzheimer Disease Research Center and were cognitively normal at baseline, underwent amyloid PET imaging and/or CSF collection within 1 year of baseline clinical assessment, and had subsequent clinical follow-up. Cognitive status was assessed longitudinally by Clinical Dementia Rating®. Biomarker status was assessed using predefined cut-offs for amyloid PET imaging or CSF p-tau181/amyloid-β42. Subsequently, 57 participants died and underwent neuropathologic examination. Alzheimer's disease neuropathological changes were assessed using standard criteria. We assessed the predictive value of Alzheimer's disease biomarker status on progression to cognitive impairment and for presence of Alzheimer's disease neuropathological changes. Among cognitively normal participants with positive biomarkers, 34.4% developed cognitive impairment (Clinical Dementia Rating > 0) as compared to 8.4% of those with negative biomarkers. Cox proportional hazards modelling indicated that preclinical Alzheimer's disease biomarker status, APOE ɛ4 carrier status, polygenic risk score and centred age influenced risk of developing cognitive impairment. Among autopsied participants, 90.9% of biomarker-positive participants and 8.6% of biomarker-negative participants had Alzheimer's disease neuropathological changes. Sensitivity was 87.0%, specificity 94.1%, positive predictive value 90.9% and negative predictive value 91.4% for detection of Alzheimer's disease neuropathological changes by preclinical biomarkers. Single CSF and amyloid PET baseline biomarkers were also predictive of Alzheimer's disease neuropathological changes, as well as Thal phase and Braak stage of pathology at autopsy. Biomarker-negative participants who developed cognitive impairment were more likely to exhibit non-Alzheimer's disease pathology at autopsy. The detection of preclinical Alzheimer's disease biomarkers is strongly predictive of future cognitive impairment and accurately predicts presence of Alzheimer's disease neuropathology at autopsy.

Preclinical Alzheimer's disease and its outcome: a longitudinal cohort study

Falls in Elderly May Predict Alzheimer's

Preclinical Alzheimer's disease (AD) is characterized by amyloid deposition in the absence of overt clinical impairment. There is substantial heterogeneity in the long-term clinical outcomes among amyloid positive individuals, yet limited work has focused on identifying molecular factors driving resilience from amyloid-related cognitive impairment. We apply a recently developed predicted gene expression analysis (PrediXcan) to identify genes that modify the association between baseline amyloid deposition and longitudinal cognitive changes. Participants free of clinical AD (n=631) were selected from the AD Neuroimaging Initiative (ADNI) who had a baseline positron emission tomography measure of amyloid deposition (quantified as a standard uptake value ratio), longitudinal neuropsychological data, and genetic data. PrediXcan was used to impute gene expression levels across 15 heart and brain tissues. Mixed effect regression models assessed the interaction between predicted gene expression levels and amyloid deposition on longitudinal cognitive outcomes. The predicted gene expression levels for two genes in the coronary artery (CNTLN, PROK1) and two genes in the atrial appendage (PRSS50, PROK1) interacted with amyloid deposition on episodic memory performance. The predicted gene expression levels for two additional genes (TMC4 in the basal ganglia and HMBS in the aorta) interacted with amyloid deposition on executive function performance. Post-hoc analyses provide additional validation of the HMBS and PROK1 effects across two independent subsets of ADNI using two additional metrics of amyloid deposition. These results highlight a subset of unique candidate genes of resilience and provide evidence that cell-cycle regulation, angiogenesis, and heme biosynthesis likely play a role in AD progression.

BackgroundMaximizing the efficiency to screen amyloid-positive individuals in asymptomatic and non-demented aged population using blood-based biomarkers is essential for future success of clinical trials in the early stage of Alzheimer’s disease (AD). In this study, we elucidate the utility of combination of plasma amyloid-β (Aβ)-related biomarkers and tau phosphorylated at threonine 217 (p-tau217) to predict abnormal Aβ-positron emission tomography (PET) in the preclinical and prodromal AD.MethodsWe designed the cross-sectional study including two ethnically distinct cohorts, the Japanese trial-ready cohort for preclinica and prodromal AD (J-TRC) and the Swedish BioFINDER study. J-TRC included 474 non-demented individuals (CDR 0: 331, CDR 0.5: 143). Participants underwent plasma Aβ and p-tau217 assessments, and Aβ-PET imaging. Findings in J-TRC were replicated in the BioFINDER cohort including 177 participants (cognitively unimpaired: 114, mild cognitive impairment: 63). In both cohorts, plasma Aβ(1-42) (Aβ42) and Aβ(1-40) (Aβ40) were measured using immunoprecipitation-MALDI TOF mass spectrometry (Shimadzu), and p-tau217 was measured with an immunoassay on the Meso Scale Discovery platform (Eli Lilly).ResultsAβ-PET was abnormal in 81 participants from J-TRC and 71 participants from BioFINDER. Plasma Aβ42/Aβ40 ratio and p-tau217 individually showed moderate to high accuracies when detecting abnormal Aβ-PET scans, which were improved by combining plasma biomarkers and by including age, sex and APOE genotype in the models. In J-TRC, the highest AUCs were observed for the models combining p-tau217/Aβ42 ratio, APOE, age, sex in the whole cohort (AUC = 0.936), combining p-tau217, Aβ42/Aβ40 ratio, APOE, age, sex in the CDR 0 group (AUC = 0.948), and combining p-tau217/Aβ42 ratio, APOE, age, sex in the CDR 0.5 group (AUC = 0.955), respectively. Each subgroup results were replicated in BioFINDER, where the highest AUCs were seen for models combining p-tau217, Aβ42/40 ratio, APOE, age, sex in cognitively unimpaired (AUC = 0.938), and p-tau217/Aβ42 ratio, APOE, age, sex in mild cognitive impairment (AUC = 0.914).ConclusionsCombination of plasma Aβ-related biomarkers and p-tau217 exhibits high performance when predicting Aβ-PET positivity. Adding basic clinical information (i.e., age, sex, APOE ε genotype) improved the prediction in preclinical AD, but not in prodromal AD. Combination of Aβ-related biomarkers and p-tau217 could be highly useful for pre-screening of participants in clinical trials of preclinical and prodromal AD.

Very little is known about functional change in persons in the preclinical stage of AD. As currently conceptualized, functional impairment in Alzheimer’s disease (AD) is the final and somewhat remote downstream outcome of a cascade of preceding pathophysiological and clinical events characterizing AD: amyloid deposition, neurodegenerative cellular, metabolic and network pathway changes, tissue loss and atrophy, and significant cognitive decline. Given this prevailing conceptual framework, possible functional change in preclinical AD, and related clinical trial methodology, have received relatively little attention. For example, the 2013 draft guidance of the FDA for treatment of early stage Alzheimer’s disease anticipates that persons in the preclinical phase will only show subtle cognitive deficits “in the absence of any detectable functional impairment” (1), and that in these circumstances the field may be allowed to pursue valid and reliable cognitive assessments as a single primary efficacy measure (1). This prevailing framework notwithstanding, a new perspective has recently begun to emerge concerning functional change and outcome measures in preclinical AD. The intriguing possibility that detectable functional change actually commences much earlier in the AD disease process, possibly as early as the preclinical stage, has recently been suggested (2, 3). In support of this proposition is the now well-established finding that functional impairment is clearly present in prodromal AD. Prior research by several groups (3–7) has shown that complex functional skills (Independent Activities of Daily Life, or IADLs) show impairment in patients with mild cognitive impairment (MCI) and continue to decline over time (5). In particular, financial capacity is a higher order functional skill that is highly sensitive and vulnerable to MCI and mild AD (4, 5, 8), which raises the possibility that measurable financial decline may also occur in persons with preclinical AD. It should be noted that current diagnostic criteria for preclinical AD explicitly contemplate and posit incipient subtle cognitive changes emerging in the third or “late” stage of the preclinical phase (9). Consistent with this theoretical view, recent studies have shown episodic memory impairments in older individuals with abnormal levels of brain amyloid (10, 11). The presence of detectable albeit subtle cognitive impairments in individuals with preclinical AD raises the possibility that associated subtle changes in complex functional activities may also be present and detectable. A critical factor here is the sensitivity of the functional measure employed. Detection of functional impairment in cognitively normal individuals with preclinical AD will require instruments sensitive to subclinical cognitive and functional changes. Informant report measures commonly used to characterize functional decline in late MCI and AD type dementia likely lack sensitivity to detect these very subtle functional changes. In contrast, performance based assessment measures may have sufficient sensitivity as they can support finely grained quantitative measurement using performance and task completion time variables. In the author’s view, in order to maximize detection of functional impairment in preclinical AD, proposed functional assessment measures should incorporate the following features: Assess cognitively complex functional abilities relevant to independent living and sensitive to early decline in AD. Assess the functional ability using an interval scaled, direct performance measure that evaluates performance variables in a highly detailed and granular manner. Include time limitations for performance items in order to enhance item difficulty. In addition to performance items, include task completion time variables in order to capture subtle processing speed changes.

Topographical pattern of blood‐brain barrier impairment in preclinical and clinical Alzheimer’s disease

Topographical pattern of blood‐brain barrier impairment in preclinical and clinical Alzheimer’s disease