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      Developments in scalable strategies for detecting early markers of cognitive decline

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          Abstract

          Effective strategies for early detection of cognitive decline, if deployed on a large scale, would have individual and societal benefits. However, current detection methods are invasive or time-consuming and therefore not suitable for longitudinal monitoring of asymptomatic individuals. For example, biological markers of neuropathology associated with cognitive decline are typically collected via cerebral spinal fluid, cognitive functioning is evaluated from face-to-face assessments by experts and brain measures are obtained using expensive, non-portable equipment. Here, we describe scalable, repeatable, relatively non-invasive and comparatively inexpensive strategies for detecting the earliest markers of cognitive decline. These approaches are characterized by simple data collection protocols conducted in locations outside the laboratory: measurements are collected passively, by the participants themselves or by non-experts. The analysis of these data is, in contrast, often performed in a centralized location using sophisticated techniques. Recent developments allow neuropathology associated with potential cognitive decline to be accurately detected from peripheral blood samples. Advances in smartphone technology facilitate unobtrusive passive measurements of speech, fine motor movement and gait, that can be used to predict cognitive decline. Specific cognitive processes can be assayed using ‘gamified’ versions of standard laboratory cognitive tasks, which keep users engaged across multiple test sessions. High quality brain data can be regularly obtained, collected at-home by users themselves, using portable electroencephalography. Although these methods have great potential for addressing an important health challenge, there are barriers to be overcome. Technical obstacles include the need for standardization and interoperability across hardware and software. Societal challenges involve ensuring equity in access to new technologies, the cost of implementation and of any follow-up care, plus ethical issues.

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          Most cited references146

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          The amyloid hypothesis of Alzheimer's disease at 25 years

          Abstract Despite continuing debate about the amyloid β‐protein (or Aβ hypothesis, new lines of evidence from laboratories and clinics worldwide support the concept that an imbalance between production and clearance of Aβ42 and related Aβ peptides is a very early, often initiating factor in Alzheimer's disease (AD). Confirmation that presenilin is the catalytic site of γ‐secretase has provided a linchpin: all dominant mutations causing early‐onset AD occur either in the substrate (amyloid precursor protein, APP) or the protease (presenilin) of the reaction that generates Aβ. Duplication of the wild‐type APP gene in Down's syndrome leads to Aβ deposits in the teens, followed by microgliosis, astrocytosis, and neurofibrillary tangles typical of AD. Apolipoprotein E4, which predisposes to AD in > 40% of cases, has been found to impair Aβ clearance from the brain. Soluble oligomers of Aβ42 isolated from AD patients' brains can decrease synapse number, inhibit long‐term potentiation, and enhance long‐term synaptic depression in rodent hippocampus, and injecting them into healthy rats impairs memory. The human oligomers also induce hyperphosphorylation of tau at AD‐relevant epitopes and cause neuritic dystrophy in cultured neurons. Crossing human APP with human tau transgenic mice enhances tau‐positive neurotoxicity. In humans, new studies show that low cerebrospinal fluid (CSF) Aβ42 and amyloid‐PET positivity precede other AD manifestations by many years. Most importantly, recent trials of three different Aβ antibodies (solanezumab, crenezumab, and aducanumab) have suggested a slowing of cognitive decline in post hoc analyses of mild AD subjects. Although many factors contribute to AD pathogenesis, Aβ dyshomeostasis has emerged as the most extensively validated and compelling therapeutic target.
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            High performance plasma amyloid-β biomarkers for Alzheimer’s disease

            To facilitate clinical trials of disease-modifying therapies for Alzheimer's disease, which are expected to be most efficacious at the earliest and mildest stages of the disease, supportive biomarker information is necessary. The only validated methods for identifying amyloid-β deposition in the brain-the earliest pathological signature of Alzheimer's disease-are amyloid-β positron-emission tomography (PET) imaging or measurement of amyloid-β in cerebrospinal fluid. Therefore, a minimally invasive, cost-effective blood-based biomarker is desirable. Despite much effort, to our knowledge, no study has validated the clinical utility of blood-based amyloid-β markers. Here we demonstrate the measurement of high-performance plasma amyloid-β biomarkers by immunoprecipitation coupled with mass spectrometry. The ability of amyloid-β precursor protein (APP)669-711/amyloid-β (Aβ)1-42 and Aβ1-40/Aβ1-42 ratios, and their composites, to predict individual brain amyloid-β-positive or -negative status was determined by amyloid-β-PET imaging and tested using two independent data sets: a discovery data set (Japan, n = 121) and a validation data set (Australia, n = 252 including 111 individuals diagnosed using 11C-labelled Pittsburgh compound-B (PIB)-PET and 141 using other ligands). Both data sets included cognitively normal individuals, individuals with mild cognitive impairment and individuals with Alzheimer's disease. All test biomarkers showed high performance when predicting brain amyloid-β burden. In particular, the composite biomarker showed very high areas under the receiver operating characteristic curves (AUCs) in both data sets (discovery, 96.7%, n = 121 and validation, 94.1%, n = 111) with an accuracy approximately equal to 90% when using PIB-PET as a standard of truth. Furthermore, test biomarkers were correlated with amyloid-β-PET burden and levels of Aβ1-42 in cerebrospinal fluid. These results demonstrate the potential clinical utility of plasma biomarkers in predicting brain amyloid-β burden at an individual level. These plasma biomarkers also have cost-benefit and scalability advantages over current techniques, potentially enabling broader clinical access and efficient population screening.
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              Plasma P-tau181 in Alzheimer’s disease: relationship to other biomarkers, differential diagnosis, neuropathology and longitudinal progression to Alzheimer’s dementia

              Plasma phosphorylated tau181 (P-tau181) might be increased in Alzheimer's disease (AD), but its usefulness for differential diagnosis and prognosis is unclear. We studied plasma P-tau181 in three cohorts, with a total of 589 individuals, including cognitively unimpaired participants and patients with mild cognitive impairment (MCI), AD dementia and non-AD neurodegenerative diseases. Plasma P-tau181 was increased in preclinical AD and further increased at the MCI and dementia stages. It correlated with CSF P-tau181 and predicted positive Tau positron emission tomography (PET) scans (area under the curve (AUC) = 0.87-0.91 for different brain regions). Plasma P-tau181 differentiated AD dementia from non-AD neurodegenerative diseases with an accuracy similar to that of Tau PET and CSF P-tau181 (AUC = 0.94-0.98), and detected AD neuropathology in an autopsy-confirmed cohort. High plasma P-tau181 was associated with subsequent development of AD dementia in cognitively unimpaired and MCI subjects. In conclusion, plasma P-tau181 is a noninvasive diagnostic and prognostic biomarker of AD, which may be useful in clinical practice and trials.
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                Author and article information

                Contributors
                Robert.whelan@tcd.ie
                Journal
                Transl Psychiatry
                Transl Psychiatry
                Translational Psychiatry
                Nature Publishing Group UK (London )
                2158-3188
                9 November 2022
                9 November 2022
                2022
                : 12
                : 473
                Affiliations
                [1 ]GRID grid.8217.c, ISNI 0000 0004 1936 9705, School of Psychology, , Trinity College Dublin, ; Dublin, Ireland
                [2 ]GRID grid.8217.c, ISNI 0000 0004 1936 9705, Global Brain Health Institute, , Trinity College Dublin, ; Dublin, Ireland
                [3 ]Cumulus Neuroscience Ltd, Dublin, Ireland
                [4 ]GRID grid.411247.5, ISNI 0000 0001 2163 588X, Department of Gerontology, , Universidade Federal de São Carlos, ; São Carlos, Brazil
                Author information
                http://orcid.org/0000-0002-2790-7281
                http://orcid.org/0000-0003-1162-0195
                http://orcid.org/0000-0001-6385-7392
                http://orcid.org/0000-0001-9065-403X
                http://orcid.org/0000-0001-9857-8705
                Article
                2237
                10.1038/s41398-022-02237-w
                9645320
                36351888
                98a82bec-ac7f-4e64-9ad6-6e2220d79575
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 2 June 2022
                : 24 October 2022
                : 26 October 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001602, Science Foundation Ireland (SFI);
                Award ID: 20/FFP-P/861
                Award ID: 19/FFP/6418
                Award ID: 19/FFP/6418
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100002081, Irish Research Council (An Chomhairle um Thaighde in Éirinn);
                Award ID: EBPPG/2019/53
                Award ID: EBPPG/2019/53
                Award Recipient :
                Funded by: Atlantic Fellowship for Equity in Brain Health
                Funded by: MQ: transforming mental health (MQ16IP13) European Research Council (ERC) Starting Grant (ERC-H2020-HABIT).
                Categories
                Review Article
                Custom metadata
                © The Author(s) 2022

                Clinical Psychology & Psychiatry
                neuroscience,biomarkers,psychology
                Clinical Psychology & Psychiatry
                neuroscience, biomarkers, psychology

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