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Article type: Research Article
Authors: Baldeiras, Inêsa; b; c; * | Silva-Spínola, Anuschkac | Lima, Marisaa; c; d | Leitão, Maria Joãoc | Durães, João a; b; c | Vieira, Danielaa | Tábuas-Pereira, Miguela; b; c | Cruz, Vitor Tedime | Rocha, Raquele | Alves, Luisaf | Machado, Álvarog | Milheiro, Miguelh | Santiago, Beatrizi | Santana, Isabela; b; c
Affiliations: [a] Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal | [b] Faculdade de Medicina, Universidade de Coimbra, Coimbra, Portugal | [c] Center for Neuroscience and Cell Biology; Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal | [d] Center for Research in Neuropsychology and Cognitive Behavioral Intervention, Faculty of Psychology and Educational Sciences, University of Coimbra, Coimbra, Portugal | [e] ULSM Unidade Local de Sáude de Matosinhos, Matosinhos, Portugal | [f] Hospital Egas Moniz, Centro Hospitalar de Lisboa Ocidental, Lisboa, Portugal | [g] Hospital de Braga, Braga, Portugal | [h] Hospital de Faro, Faro, Portugal | [i] Centro Hospitalar Baixo Vouga, Aveiro, Portugal
Correspondence: [*] Correspondence to: Inês Baldeiras, Faculty of Medicine, Azinhaga de Santa Comba, 3000-548 Coimbra, Portugal. Tel.: +351 239 400448; Fax: +351 239 822637; ibaldeirasmed.uc.pt
Abstract: Background:The ATN scheme was proposed as an unbiased biological characterization of the Alzheimer’s disease (AD) spectrum, grouping biomarkers into three categories: brain Amyloidosis-A, Tauopathy-T, Neurodegeneration-N. Although this scheme was mainly recommended for research, it is relevant for diagnosis. Objective:To evaluate the ATN scheme performance in real-life cohorts reflecting the inflow of patients with cognitive complaints and different underlying disorders in general neurological centers. Methods:We included patients (n = 1,128) from six centers with their core cerebrospinal fluid-AD biomarkers analyzed centrally. A was assessed through Aβ42/Aβ40, T through pTau-181, and N through tTau. Association between demographic features, clinical diagnosis at baseline/follow-up and ATN profiles was assessed. Results:The prevalence of ATN categories was: A-T-N-: 28.3%; AD continuum (A + T-/+N-/+): 47.8%; non-AD (A- plus T or/and N+): 23.9%. ATN profiles prevalence was strongly influenced by age, showing differences according to gender, APOE genotype, and cognitive status. At baseline, 74.6% of patients classified as AD fell in the AD continuum, decreasing to 47.4% in mild cognitive impairment and 42.3% in other neurodegenerative conditions. At follow-up, 41% of patients changed diagnosis, and 92% of patients that changed to AD were classified within the AD continuum. A + was the best individual marker for predicting a final AD diagnosis, and the combinations A + T+ (irrespective of N) and A + T+N+ had the highest overall accuracy (83%). Conclusion:The ATN scheme is useful to guide AD diagnosis in real-life neurological centers settings. However, it shows a lack of accuracy for patients with other types of dementia. In such cases, the inclusion of other markers specific for non-AD proteinopathies could be an important aid to the differential diagnosis.
Keywords: Alzheimer’s disease, ATN scheme, cerebrospinal fluid biomarkers, cognitive complaints
DOI: 10.3233/JAD-220587
Journal: Journal of Alzheimer's Disease, vol. 90, no. 1, pp. 419-432, 2022
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