Related Experiment Video
Updated: May 16, 2026

Using Retinal Imaging to Study Dementia
Published on: November 6, 2017
The Role of Clinical, Plasma, and Imaging Biomarkers in Assessing Future Dementia Risk in Individuals With Subjective
María Rivera Sánchez1,2,3,4, Sophie E Mastenbroek1,5,6, Shorena Janelidze1
1Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Sweden.
Background And Objectives:
Subjective cognitive decline (SCD) is a well-recognized risk state for developing mild cognitive impairment (MCI) and dementia. Optimal risk stratification for early interventions and clinical trial selection remains challenging. This study evaluates progression risk across multimodal biomarker profiles in SCD.
Methods:
We conducted a longitudinal observational study including participants from the BioFINDER-1 and BioFINDER-2 cohorts with a baseline diagnosis of SCD, at least 1 follow-up visit, and available information on dementia progression. Baseline predictors included cognitive performance, APOE4 status, plasma phosphorylated tau (p-tau) 217, "AD-signature" cortical thickness, hippocampal volume, and white matter hyperintensities (WMHs) measured by the Fazekas scale. Missing data were handled using multiple imputation. Predictors were evaluated individually and then combined in progressively complex Cox regression models to predict progression to all-cause dementia, Alzheimer disease (AD) dementia, and MCI (BioFINDER-2 only). Model performance was assessed using the Harrell C-index, and Akaike information criterion was used for comparing model fit.
Results:
A total of 469 participants with SCD (mean age 69.1 ± 7.1 years, 51.4% female) were included in the main sample. Eighty-four individuals progressed to dementia over 4.0 ± 2.1 years (66.7% AD dementia). Progressors were older and more frequently APOE4 carriers and showed worse baseline cognition, higher plasma p-tau217, and greater atrophy and WMH burden. Plasma p-tau217 was the strongest individual predictor for AD dementia (C-index = 0.86 ± 0.012), but multivariable models outperformed single-biomarker models. The best model for all-cause dementia included all variables and achieved a C-index of 0.89 ± 0.003. For AD dementia, a more parsimonious model combining plasma p-tau217, cognitive scores, and APOE4 status showed excellent predictive ability (C-index = 0.91 ± 0.009), with only marginal improvement when MRI markers were added. Among 249 individuals from BioFINDER-2, 84 progressed to MCI within 2.3 ± 1.2 years. For MCI prediction, model performance was generally lower and similar between the plasma model and the model including all variables (C-index = 0.83 ± 0.009).
Discussion:
A clinically feasible multimodal approach combining cognitive assessment, plasma p-tau217, and APOE4 status accurately predicts AD dementia risk in individuals with SCD. Adding MRI measures of brain atrophy and WMHs further improves prediction for all-cause dementia. These findings underscore the clinical value of plasma p-tau217 in refining risk assessment in SCD and support its potential implementation in memory clinic settings alongside other widely available biomarkers.
Related Concept Videos
Dementia
The progression of dementia is generally gradual.
Dementia l: Introduction
Alzheimer's Disease: Overview
The clinical diagnosis of AD hinges on the presence of memory and other cognitive impairments. Biomarkers, such as changes in Aβ and tau...
Alzheimer Disease l: Introduction
Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT
Cognitive Development During Adulthood
