Background Health-related factors may influence blood-based biomarkers (BBBM) of Alzheimer's disease (AD). In this analysis, associations between modifiable factors and plasma biomarkers of neurodegeneration were investigated across the Alzheimer's disease spectrum and in cognitively healthy controls in a cerebrospinal fluid–confirmed (CSF) cohort. Methods Plasma biomarkers included the Aβ1–42/1–40 ratio, pTau181, GFAP, NFL and ApoE4. Multiple linear regression was used to test associations with lifestyle factors (physical activity and sleep), physiological factors (including renal and lipid metabolism markers), genetic factors (APOE ε4), age and sex. Percentage effect sizes and confidence intervals were calculated. Results The study included CSF-characterized individuals with AD (mild cognitive impairment due to AD and AD dementia) and cognitively healthy controls (n = 116; mean age 71.2 years). Overall, the associations were modest, with wide confidence intervals reflecting variability in the outcomes and the limited range of predictors in this relatively healthy sample. In CSF-confirmed participants, age emerged as the most consistent predictor of plasma biomarker levels, particularly NFL and pTau181. APOE ε3/ε4 genotype was additionally associated with higher pTau181 levels. Other demographic, metabolic and lifestyle-related variables showed only weak or inconsistent associations. Conclusion To implement BBBM in broader populations, a systematic evaluation of confounders is required. As aging cohorts present with mixed pathologies, strategies to address heterogeneity will be essential. The limited number of robust associations observed suggests that plasma biomarkers are influenced primarily by age and genetic background rather than by metabolic factors in this cohort. Validation in more diverse populations remains warranted.
Carolin I. Kurz, Marleen Taute, Paulina Tegethoff et al.· Aging Brain· 0 citations
BACKGROUND
Currently, no single biomarker can reliably identify preclinical Alzheimer's disease (AD), particularly at or before the mild cognitive impairment (MCI) stage. Given the heterogeneity of MCI, integrative approaches are needed to improve early risk stratification.
OBJECTIVES
(i) To derive robust latent cognitive components from a multicenter, clinically defined MCI cohort using principal component analysis (PCA); (ii) to investigate the associations between these components and plasma p-tau217 and p-tau181 levels.
METHODS
Data from 742 MCI participants in the AI-Mind cohort were analyzed. Cognitive domains were derived using PCA with varimax rotation and tested for associations with plasma p-tau biomarkers using site-specific linear regressions, adjusted for age, sex, and education.
RESULTS
A reproducible four-component cognitive structure emerged (memory, executive/processing speed, verbal fluency, visuospatial ability), with memory as the most p-tau-sensitive domain. The p-tau217 measure showed stronger associations with memory than p-tau181, though effects varied by site.
CONCLUSION
The findings indicate that a robust four-factor cognitive structure can be identified in clinically defined MCI cohorts without prior biological selection. The association between latent memory factors and plasma p-tau217, observed primarily in cohorts with higher biomarker burden or clearer amnestic profiles, highlights the potential for blood-based biomarkers to refine risk assessment in routine clinical practice.
Ana S. Perez, Hugo L. Hammer, V. Andersson et al.· GeroScience· 0 citations
In this large longitudinal sample of asymptomatic individuals, the Aβ-dominant biomarker component showed the strongest association with longitudinal GM atrophy and cognitive decline, beyond the effects of tau pathophysiology and neuroaxonal injury.
W. Pelkmans, R. Cacciaglia, Michalis Kassinopoulos et al.· Molecular Neurodegeneration· 0 citations
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