AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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While most studies of Alzheimer's disease (AD) examine cross‐sectional relationships among biomarkers, longitudinal relationships are also highly relevant.
Staging amyloid beta (Aβ) burden along a continuous spectrum provides clinically relevant information. Conventional phosphorylated tau (p‐tau)217 reliably identifies amyloid positron emission tomography (PET) positivity, but its ability to capture the full Aβ continuum is limited. Recently developed brain‐derived (BD) p‐tau217 assays enrich for central nervous system tau species and may improve specificity.
Lifestyle habits, cognitive reserve, and affective reserve (secure attachment, extraversion, psychological resilience) predict resilience in the oldest-old, though the underlying biological mechanisms remain unclear. This study explored relationships between these protective factors, 120 + NULISA CNS blood biomarkers, and multidimensional health outcomes (global cognition, mental health, walking speed) in 401 dementia-free participants (age 83-87) from the InveCe.Ab study. Using sparse partial least squares (sPLS) regression, eight biomarkers were stably associated with the protective factors: HBA1, DDC, IFNG, IL15, GOT1, ACHE, SNAP25, and SNCB. Structural equation modeling (SEM) showed that the three protective factors exerted an independent and domain-specific effect on health outcomes. Moreover, lifestyle habits were associated with ACHE (β = 0.26), IL15 (β = 0.22), and GOT1 (β = 0.28); affective reserve showed inverse associations with IFNG (β = -0.13) and IL15 (β = -0.31), and GOT1 (β = -0.18). Regarding health domains, SNAP25 was inversely related to global cognition (β = -0.10), while SNCB was associated with global cognition (β = 0.16) and walking speed (β = 0.13). Notably, no significant mediated effects were found, suggesting that the clinical benefits observed were not directly driven by the aforementioned biological pathways. The present study paves the way for further investigations on the biological mechanisms underlying resilient aging, while further demonstrating the key protective role of individual habits and psychosocial characteristics during the life course.
BACKGROUND There is increasing evidence for the role of central and peripheral inflammation across neurodegenerative disorders, with animal models and post-mortem studies identifying T-cell infiltration in the brain associated with pathology and neurodegeneration. Peripheral T-cell changes have been measured in Alzheimer's disease (AD), dementia with Lewy bodies (DLB), frontotemporal dementia (FTD) and progressive supranuclear palsy (PSP). This study examines a unique cohort of blood-based T-cell profiles across a range of neurodegenerative dementias including AD, DLB, FTD, corticobasal syndrome (CBS), PSP, and aged-matched healthy controls. Then it also explores their associations with dementia-relevant plasma biomarkers and clinical outcomes. METHODS Freshly prepared peripheral blood mononuclear cells (PBMCs) from 174 participants (AD = 20, DLB = 24, FTD = 19, CBS = 18, PSP = 58, controls = 35) were studied using a flow-cytometry panel designed to analyse major T-cell subpopulations, including memory and T-helper subtypes. Neurodegeneration-relevant biomarkers (p-tau217, p-tau231, GFAP, NfL, and A-beta42/40) were measured in plasma samples. T-cell populations were compared between groups and in association with biomarkers, and principal components analysis (PCA) was used to identify T-cell profiles and their association with dementia-relevant biomarkers in diagnostic classification and survival prediction. RESULTS There was a significant reduction in the fraction of CD3+ cells in patients with DLB compared to other diagnostic groups, and an increase in relative Th1/17-like cell levels in patients with FTD compared to controls. This increase in Th1/17-like cells correlated with NfL and GFAP plasma levels in patients with FTD. PCA identified five components primarily representing CD4+ memory cell population subsets. After sex and age adjustments, component 4 marked by effector memory types including Th2-like, Th-like1 and Th1/17-like cells was a significant predictor of FTD, however was not as accurate as plasma NfL. Higher scores in specific T-cell components (1 and 3) were associated with reduced mortality across all diseases, with component 3 remaining a significant predictor even when controlling for traditional neurodegenerative biomarkers like NfL and p-tau217. CONCLUSIONS This study provides evidence that T-cell dysregulation is not unified in patients with neurodegenerative diseases. We observe different involvement across different dementia types establishing adaptive immunity as a key contributor to disease heterogeneity. However, although plasma biomarkers such as NfL and p-tau217 exhibit superior diagnostic accuracy for clinical classification, peripheral T-cell signature were associated with survival outcomes across diagnostic groups, highlighting their promise for prognostic applications and disease monitoring. The characterisation of T-cell populations across neurodegenerative conditions may inform target development and patient stratification for new interventional trials.
Whether these proteins, alone or combined with plasma phosphorylated tau 217 (p‐tau217), predict progression from cognitively unimpaired to symptomatic AD is evaluated.
These findings highlight the complementary roles of CSF and plasma tau biomarkers in tracking disease progression: CSF biomarkers capture early pathological changes, whereas plasma biomarkers more effectively reflect disease progression within symptomatic stages.
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