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Plasma ATN biomarkers across the alzheimer’s disease continuum in a Chilean community- and clinic-based cohort

  • Paulina Orellana
  • , Fernando Henríquez
  • , Felipe Cabral-Miranda
  • , Hernán Hernandez
  • , Pamela C.L. Ferreira
  • , Bruna Bellaver
  • , Ariel Caviedes
  • , Matias Pizarro
  • , Carolina Gonzalez-Silva
  • , Nickole Marin-Diaz
  • , Patricio Riquelme
  • , Natalia Pozo
  • , Francisca Damm
  • , Felipe A. Court
  • , Christian Gonzalez-Billault
  • , Patricia Lillo
  • , Daniela Thumala-Dockendorff
  • , Mauricio Cerda
  • , Roque Villagra
  • , Rolando de la Cruz
  • Thomas Karikari, Agustín Ibañez, Henrik Zetterberg, Tharick A Pascoal, Claudia Duran-Aniotz, Andrea Slachevsky

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Plasma biomarkers have emerged as robust indicators of Alzheimer’s disease (AD) pathology, offering accessible tools for staging and stratification. However, their expression across globally diverse populations remains poorly characterized. The aim of this study was to evaluate whether the combination of plasma biomarkers could distinguish different stages along the AD continuum and assess their clinical associations in a Latin American cohort. Methods: We evaluated plasma amyloid, tau, and neurodegeneration (ATN) biomarkers in 318 older adults from a Chilean community- and clinic-based cohort, including individuals with subjective cognitive complaints (SCC), mild cognitive impairment (MCI), and Alzheimer’s disease dementia (ADD), alongside cognitively unimpaired (CU) participants. Plasma ATN biomarkers (Aβ42/Aβ40, p-tau217, NfL, and GFAP) were quantified using Simoa technology. Global cognition was assessed with the Addenbrooke’s Cognitive Examination (ACE), memory with the Free and Cued Selective Reminding Test (FCSRT), and functional ability with the Technology–Activities of Daily Living Questionnaire (T-ADLQ). Group differences in plasma biomarkers were examined using ANCOVA models adjusted for age, sex, and education, and associations with cognitive performance were evaluated through linear regression analyses. In addition, supervised machine-learning models were implemented to classify participants across diagnostic categories based on plasma biomarker profiles, using cross-validation to evaluate predictive performance. Results: We observed a progressive decline in the Aβ42/Aβ40 ratio and elevations in p-tau217 and GFAP across the clinical continuum. Additionally, p-tau217 and NfL levels were inversely associated with cognitive, memory, and functional performance. Notably, p-tau217 distinguished ADD from CU with high accuracy (AUC = 0.88), although its performance in earlier stages was limited. Conclusion: These findings support the biological consistency of plasma biomarkers in AD-related neurodegeneration and provide novel evidence from a Latin American population. Further studies are needed to improve early-stage detection and to better understand how genetic, environmental, and health factors shape biomarker expressions in underrepresented regions.

Original languageEnglish
Article number70
JournalAlzheimer's Research and Therapy
Volume18
Issue number1
DOIs
StatePublished - Dec 2026

Keywords

  • Alzheimer disease
  • Alzheimer’s disease dementia
  • Machine learning
  • Mild cognitive impairment
  • Plasma ATN biomarkers
  • Subjective cognitive complaints
  • p-tau217

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