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      Comparing the Clinical Utility and Diagnostic Performance of CSF P-Tau181, P-Tau217, and P-Tau231 Assays

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          Abstract

          Background and Objectives

          Phosphorylated tau (p-tau) in CSF is considered an important biomarker in Alzheimer disease (AD) and has been incorporated in recent diagnostic criteria. Several variants exist, including p-tau at threonines 181 (p-tau181), 217 (p-tau217), and 231 (p-tau231). However, no studies have compared their diagnostic performance or association to β-amyloid (Aβ) and tau-PET. Understanding which p-tau variant to use remains an important yet answered question. We aimed to compare the diagnostic accuracy of p-tau181, p-tau217, and p-tau231 in CSF for AD and their association with Aβ and tau-PET.

          Methods

          A total of 629 participants in the Swedish BioFINDER-2 study were included (cognitively unimpaired, n = 334; Aβ-positive mild cognitive impairment, n = 84; AD dementia, n = 119; and non-AD disorders, n = 92). In addition to p-tau181 and p-tau217 measured using assays with the same detector antibodies from Eli Lilly (p-tau181 Lilly, p-tau217 Lilly) and p-tau231, we also included p-tau181 measurements from 2 commonly used assays (Innotest and Elecsys).

          Results

          Although all p-tau variants increased across the AD continuum, p-tau217 Lilly showed the greatest dynamic range (13-fold increase vs 1.9–5.4-fold increase for other p-tau variants for AD dementia vs non-AD). P-Tau217 Lilly showed stronger correlations with Aβ- and tau-PET ( p < 0.0001). P-Tau217 Lilly exhibited higher accuracy than other p-tau variants for separating AD dementia from non-AD (area under the curve [AUC], 0.98 vs 0.88 [ p < 0.0001] - 0.96 [ p < 0.05]) and for identifying Aβ-PET (AUC, 0.86 vs 0.74 [ p < 0.0001] and 0.83 [ p < 0.001]) and tau-PET positivity (AUC, 0.94 vs 0.80—0.92, p < 0.0001). Finally, p-Tau181 Lilly generally performed better than the other p-tau181 assays (e.g., AD dementia vs non-AD, AUC, 0.96 vs 0.88 [p-tau181 Innotest] and 0.89 [p-tau181 Elecsys]; p < 0.0001).

          Discussion

          CSF p-tau217 Lilly seems to be more useful than other included p-tau assays in the workup of AD. Varied results across p-tau181 assays highlights the importance of anti-tau antibodies for biomarker performance.

          Classification of Evidence

          This study provides Class II evidence that p-tau217 provides higher diagnostic accuracy for diagnosis of AD dementia than p-tau181 or p-tau231.

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          Most cited references49

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          NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease

          In 2011, the National Institute on Aging and Alzheimer’s Association created separate diagnostic recommendations for the preclinical, mild cognitive impairment, and dementia stages of Alzheimer’s disease. Scientific progress in the interim led to an initiative by the National Institute on Aging and Alzheimer’s Association to update and unify the 2011 guidelines. This unifying update is labeled a “research framework” because its intended use is for observational and interventional research, not routine clinical care. In the National Institute on Aging and Alzheimer’s Association Research Framework, Alzheimer’s disease (AD) is defined by its underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers. The diagnosis is not based on the clinical consequences of the disease (i.e., symptoms/signs) in this research framework, which shifts the definition of AD in living people from a syndromal to a biological construct. The research framework focuses on the diagnosis of AD with biomarkers in living persons. Biomarkers are grouped into those of β amyloid deposition, pathologic tau, and neurodegeneration [AT(N)]. This ATN classification system groups different biomarkers (imaging and biofluids) by the pathologic process each measures. The AT(N) system is flexible in that new biomarkers can be added to the three existing AT(N) groups, and new biomarker groups beyond AT(N) can be added when they become available. We focus on AD as a continuum, and cognitive staging may be accomplished using continuous measures. However, we also outline two different categorical cognitive schemes for staging the severity of cognitive impairment: a scheme using three traditional syndromal categories and a six-stage numeric scheme. It is important to stress that this framework seeks to create a common language with which investigators can generate and test hypotheses about the interactions among different pathologic processes (denoted by biomarkers) and cognitive symptoms. We appreciate the concern that this biomarker-based research framework has the potential to be misused. Therefore, we emphasize, first, it is premature and inappropriate to use this research framework in general medical practice. Second, this research framework should not be used to restrict alternative approaches to hypothesis testing that do not use biomarkers. There will be situations where biomarkers are not available or requiring them would be counterproductive to the specific research goals (discussed in more detail later in the document). Thus, biomarker-based research should not be considered a template for all research into age-related cognitive impairment and dementia; rather, it should be applied when it is fit for the purpose of the specific research goals of a study. Importantly, this framework should be examined in diverse populations. Although it is possible that β-amyloid plaques and neurofibrillary tau deposits are not causal in AD pathogenesis, it is these abnormal protein deposits that define AD as a unique neurodegenerative disease among different disorders that can lead to dementia. We envision that defining AD as a biological construct will enable a more accurate characterization and understanding of the sequence of events that lead to cognitive impairment that is associated with AD, as well as the multifactorial etiology of dementia. This approach also will enable a more precise approach to interventional trials where specific pathways can be targeted in the disease process and in the appropriate people.
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            Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia.

            Based on the recent literature and collective experience, an international consortium developed revised guidelines for the diagnosis of behavioural variant frontotemporal dementia. The validation process retrospectively reviewed clinical records and compared the sensitivity of proposed and earlier criteria in a multi-site sample of patients with pathologically verified frontotemporal lobar degeneration. According to the revised criteria, 'possible' behavioural variant frontotemporal dementia requires three of six clinically discriminating features (disinhibition, apathy/inertia, loss of sympathy/empathy, perseverative/compulsive behaviours, hyperorality and dysexecutive neuropsychological profile). 'Probable' behavioural variant frontotemporal dementia adds functional disability and characteristic neuroimaging, while behavioural variant frontotemporal dementia 'with definite frontotemporal lobar degeneration' requires histopathological confirmation or a pathogenic mutation. Sixteen brain banks contributed cases meeting histopathological criteria for frontotemporal lobar degeneration and a clinical diagnosis of behavioural variant frontotemporal dementia, Alzheimer's disease, dementia with Lewy bodies or vascular dementia at presentation. Cases with predominant primary progressive aphasia or extra-pyramidal syndromes were excluded. In these autopsy-confirmed cases, an experienced neurologist or psychiatrist ascertained clinical features necessary for making a diagnosis according to previous and proposed criteria at presentation. Of 137 cases where features were available for both proposed and previously established criteria, 118 (86%) met 'possible' criteria, and 104 (76%) met criteria for 'probable' behavioural variant frontotemporal dementia. In contrast, 72 cases (53%) met previously established criteria for the syndrome (P < 0.001 for comparison with 'possible' and 'probable' criteria). Patients who failed to meet revised criteria were significantly older and most had atypical presentations with marked memory impairment. In conclusion, the revised criteria for behavioural variant frontotemporal dementia improve diagnostic accuracy compared with previously established criteria in a sample with known frontotemporal lobar degeneration. Greater sensitivity of the proposed criteria may reflect the optimized diagnostic features, less restrictive exclusion features and a flexible structure that accommodates different initial clinical presentations. Future studies will be needed to establish the reliability and specificity of these revised diagnostic guidelines.
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              Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach.

              Methods of evaluating and comparing the performance of diagnostic tests are of increasing importance as new tests are developed and marketed. When a test is based on an observed variable that lies on a continuous or graded scale, an assessment of the overall value of the test can be made through the use of a receiver operating characteristic (ROC) curve. The curve is constructed by varying the cutpoint used to determine which values of the observed variable will be considered abnormal and then plotting the resulting sensitivities against the corresponding false positive rates. When two or more empirical curves are constructed based on tests performed on the same individuals, statistical analysis on differences between curves must take into account the correlated nature of the data. This paper presents a nonparametric approach to the analysis of areas under correlated ROC curves, by using the theory on generalized U-statistics to generate an estimated covariance matrix.
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                Author and article information

                Journal
                Neurology
                Neurology
                neurology
                neur
                NEUROLOGY
                Neurology
                Lippincott Williams & Wilkins (Hagerstown, MD )
                0028-3878
                1526-632X
                26 October 2021
                26 October 2021
                : 97
                : 17
                : e1681-e1694
                Affiliations
                From the Clinical Memory Research Unit (A.L., S.J., N.M.-C., S.P., C.C., E.S., O.H.), Department of Clinical Sciences, Lund University, Malmö; Department of Neurology (N.M.-C.) and Memory Clinic (S.P., E.S., O.H.), Skåne University Hospital, Lund; Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University, Sweden; ADx NeuroSciences NV (D.J., E.V.), Ghent, Belgium; and Eli Lilly and Company (J.L.D.), Indianapolis, IN.
                Author notes

                Go to Neurology.org/N for full disclosures. Funding information and disclosures deemed relevant by the authors, if any, are provided at the end of the article.

                The Article Processing Charge was funded by the authors.

                Author information
                http://orcid.org/0000-0003-1806-7089
                http://orcid.org/0000-0002-9466-5366
                Article
                NEUROLOGY2021170733
                10.1212/WNL.0000000000012727
                8605616
                34493616
                8fb6e383-2736-4be2-9251-6a3626353add
                Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.

                This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (CC BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 16 January 2021
                : 19 August 2021
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