A blood-based predictor for neocortical Aβ burden in Alzheimer\u27s disease: results from the AIBL study

Dementia is a global epidemic with Alzheimer’s disease (AD) being the leading cause. Early identification of patients at risk of developing AD is now becoming an international priority. Neocortical Aβ (extracellular β-amyloid) burden (NAB), as assessed by positron emission tomography (PET), represents one such marker for early identification. These scans are expensive and are not widely available, thus, there is a need for cheaper and more widely accessible alternatives. Addressing this need, a blood biomarker-based signature having efficacy for the prediction of NAB and which can be easily adapted for population screening is described. Blood data (176 analytes measured in plasma) and Pittsburgh Compound B (PiB)-PET measurements from 273 participants from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study were utilised. Univariate analysis was conducted to assess the difference of plasma measures between high and low NAB groups, and cross-validated machine-learning models were generated for predicting NAB. These models were applied to 817 non-imaged AIBL subjects and 82 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) for validation. Five analytes showed significant difference between subjects with high compared to low NAB. A machine-learning model (based on nine markers) achieved sensitivity and specificity of 80 and 82%, respectively, for predicting NAB. Validation using the ADNI cohort yielded similar results (sensitivity 79% and specificity 76%). These results show that a panel of blood-based biomarkers is able to accurately predict NAB, supporting the hypothesis for a relationship between a blood-based signature and Aβ accumulation, therefore, providing a platform for developing a population-based scree

Fifteen years of the Australian imaging, biomarkers and lifestyle (AIBL) study: Progress and observations from 2,359 older adults spanning the spectrum from cognitive normality to Alzheimer\u27s disease

Background: The Australian Imaging, Biomarkers and Lifestyle (AIBL) Study commenced in 2006 as a prospective study of 1,112 individuals (768 cognitively normal (CN), 133 with mild cognitive impairment (MCI), and 211 with Alzheimer\u27s disease dementia (AD)) as an \u27Inception cohort\u27 who underwent detailed ssessments every 18 months. Over the past decade, an additional 1247 subjects have been added as an \u27Enrichment cohort\u27 (as of 10 April 2019). Objective: Here we provide an overview of these Inception and Enrichment cohorts of more than 8,500 person-years of investigation. Methods: Participants underwent reassessment every 18 months including comprehensive cognitive testing, neuroimaging (magnetic resonance imaging, MRI; positron emission tomography, PET), biofluid biomarkers and lifestyle evaluations. Results: AIBL has made major contributions to the understanding of the natural history of AD, with cognitive and biological definitions of its three major stages: preclinical, prodromal and clinical. Early deployment of Aβ-amyloid and tau molecular PET imaging and the development of more sensitive and specific blood tests have facilitated the assessment of genetic and environmental factors which affect age at onset and rates of progression. Conclusion: This fifteen-year study provides a large database of highly characterized individuals with longitudinal cognitive, imaging and lifestyle data and biofluid collections, to aid in the development of interventions to delay onset, prevent or treat AD. Harmonization with similar large longitudinal cohort studies is underway to further these aims

The Containment Problem and the Evolutionary Debunking of Morality

Machery and Mallon [The moral psychology handbook (pp. 3–47). New York, NY: Oxford University Press, 2010] argue that existing evidence does not support the claim that moral cognition, understood as a specific form of normative cognition, is a product of evolution. Instead, they suggest that the evidence only supports the claim that a general capacity for normative cognition evolved. They argue that if this is the case, then the prospects for evolutionary debunking arguments (EDAs) of morality are bleak. A debunking argument which relied on the fact that normative cognition in general evolved seems like it would debunk all areas of normative belief, including the epistemic norms upon which the argument relies. For the sake of argument, we accept their claim that specifically moral cognition did not evolve. However, we reject their contention that this critically undermines EDAs of morality. A number of strategies are available to solve what we call the “containment problem” of how to effectively debunk morality without thereby debunking normative cognition tout court. Furthermore, the debunking argument need not rely even on the claim that normative cognition in general evolved. So long as at least some aspects of moral cognition have evolved, this may be sufficient to support an EDA against many of our moral beliefs. Thus, even if Machery and Mallon are right that specifically moral cognition did not evolve, research in evolutionary psychology may have radical implications for moral philosophy

Predicting Alzheimer disease from a blood-based biomarker profile : a 54-month follow-up

OBJECTIVE: We assessed a blood-based signature, which previously demonstrated high accuracy at stratifying individuals with high or low neocortical β-amyloid burden (NAB), to determine whether it could also identify individuals at risk of progression to Alzheimer disease (AD) within 54 months. METHODS: We generated the blood-based signature for 585 healthy controls (HCs) and 74 participants with mild cognitive impairment (MCI) from the Australian Imaging, Biomarkers and Lifestyle Study who underwent clinical reclassification (blinded to biomarker findings) at 54-month follow-up. The individuals were split into estimated high and low NAB groups based on a cutoff of 1.5 standardized uptake value ratio. We assessed the predictive accuracy of the high and low NAB groupings based on progression to mild cognitive impairment or AD according to clinical reclassification at 54-month follow-up. RESULTS: Twelve percent of HCs with estimated high NAB progressed in comparison to 5% of HCs with estimated low NAB (odds ratio = 2.4). Forty percent of the participants with MCI who had estimated high NAB progressed in comparison to 5% of the participants with MCI who had estimated low NAB (odds ratio = 12.3). These ratios are in line with those reported for Pittsburgh compound B-PET results. Individuals with estimated high NAB had faster rates of memory decline than those with estimated low NAB. CONCLUSION: These findings suggest that a simple blood-based signature not only provides estimates of NAB but also predicts cognitive decline and disease progression, identifying individuals at risk of progressing toward AD at the prodromal and preclinical stages.9 page(s

Rates of diagnostic transition and cognitive change at 18-month follow-up among 1,112 participants in the Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing (AIBL)

The Australian Imaging, Biomarkers and Lifestyle (AIBL) Flagship Study of Ageing is a prospective study of 1,112 individuals (211 with Alzheimer's disease (AD), 133 with mild cognitive impairment (MCI), and 768 healthy controls (HCs)). Here we report diagnostic and cognitive findings at the first (18-month) follow-up of the cohort. The first aim was to compute rates of transition from HC to MCI, and MCI to AD. The second aim was to characterize the cognitive profiles of individuals who transitioned to a more severe disease stage compared with those who did not. Eighteen months after baseline, participants underwent comprehensive cognitive testing and diagnostic review, provided an 80 ml blood sample, and completed health and lifestyle questionnaires. A subgroup also underwent amyloid PET and MRI neuroimaging. The diagnostic status of 89.9% of the cohorts was determined (972 were reassessed, 28 had died, and 112 did not return for reassessment). The 18-month cohort comprised 692 HCs, 82 MCI cases, 197 AD patients, and one Parkinson's disease dementia case. The transition rate from HC to MCI was 2.5%, and cognitive decline in HCs who transitioned to MCI was greatest in memory and naming domains compared to HCs who remained stable. The transition rate from MCI to AD was 30.5%. There was a high retention rate after 18 months. Rates of transition from healthy aging to MCI, and MCI to AD, were consistent with established estimates. Follow-up of this cohort over longer periods will elucidate robust predictors of future cognitive decline