Head-to-head comparison of plasma biomarker assays across platforms for amyloid pathology in a multicenter cohort.

Analytical validation and amyloid-status discrimination of a high-throughput, research-use-only plasma p-Tau217 immunoassay

Optimal amyloid and tau CSF biomarkers for the detection of amyloid and tau PET positivity in a memory clinic population

Accurate detection of Alzheimer’s disease (AD) pathophysiological changes is crucial for research and clinical practice. While positron emission tomography (PET) imaging is an established reference standard for detecting brain amyloid and tau deposition, cerebrospinal fluid (CSF) biomarkers offer a more accessible alternative. This study aimed to identify optimal CSF biomarkers and thresholds for predicting tau and amyloid PET positivity in a memory clinic population. This cross-sectional, observational study included 220 participants from a memory clinic who underwent amyloid or tau PET scans and CSF biomarker analysis using either Fujirebio INNOTEST or LUMIPULSE assays. CSF biomarker performance was assessed via receiver operating characteristic (ROC) analysis. Double-threshold approaches were implemented to address classification uncertainty. Ratios combining biomarkers of both amyloid and tau, such as Aβ42/pTau, consistently outperformed individual biomarkers in detecting amyloid and tau PET positivity. For amyloid PET, the Aβ42/pTau ratio achieved an AUC of 0.93 (95% CI: 0.86–0.99) with INNOTEST and an AUC of 0.89 (95% CI: 0.8–0.98) with LUMIPULSE. For tau PET, the Aβ42/pTau ratio achieved an AUC of 0.85 (95% CI: 0.77–0.93) with INNOTEST and an AUC of 0.97 (95% CI: 0.9-1.00) with LUMIPULSE. Double thresholds enabled classification based on predefined sensitivity and specificity, and can be used by clinicians to quickly assess a subject’s likelihood of positivity based on their biomarker levels. CSF biomarker ratios such as Aβ42/pTau provide high predictive accuracy for brain amyloid and tau deposition. Implementing double thresholds enhances clinical utility by highlighting ambiguous cases requiring further assessment.

Plasma p-tau217 for detecting Aβ-PET positivity and tracking early amyloid accumulation in cognitively unimpaired ADNI participants

Amyloid-β (Aβ) accumulation begins before cognitive impairment, highlighting the need for scalable blood-based biomarkers to identify individuals at risk during the preclinical stage of Alzheimer's disease. To evaluate whether plasma %p-tau217 detects Aβ-PET positivity and whether longitudinal plasma %p-tau217 change is associated with early Aβ accumulation in cognitively unimpaired participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). This retrospective longitudinal study included 98 cognitively unimpaired ADNI participants with plasma %p-tau217, plasma Aβ 42/40 , Aβ-PET, and clinical/genetic data. Aβ-PET positivity was defined as Centiloid (CL) ≥ 40. Among participants with baseline Aβ-PET <40 CL, participant-specific annual slopes for Aβ-PET CL and plasma biomarkers were estimated from matched longitudinal measurements using linear mixed-effects models. Regression and receiver operating characteristic analyses assessed associations with Aβ-PET change and discrimination of Aβ-PET positivity and Aβ accumulator status. Plasma %p-tau217 showed excellent discrimination of Aβ-PET positivity (area under the curve (AUC) = 0.962) and yielded a higher AUC than plasma Aβ 42/40 . In participants with baseline Aβ-PET <40 CL, longitudinal plasma %p-tau217 slope was the only plasma biomarker independently associated with annual Aβ-PET CL increase in fully adjusted models (β = 1.38; FDR-adjusted p < 0.001). Plasma %p-tau217 slope also yielded a higher AUC for Aβ accumulator status than baseline plasma %p-tau217. Plasma %p-tau217 is a strong blood-based biomarker for detecting Aβ-PET positivity in cognitively unimpaired individuals. Longitudinal plasma %p-tau217 change provides additional information beyond baseline plasma biomarkers and may support enrichment or monitoring strategies in Alzheimer's disease prevention trials, pending validation in larger independent cohorts.

Plasma p-Tau217 and SPECT-Based eZIS in Mild Cognitive Impairment: Concordance Analysis with Validation in an Amyloid PET Sub-Cohort

(1) Background/Objectives: Blood-based biomarkers have emerged as practical tools for identifying Alzheimer’s disease (AD) pathology in patients with mild cognitive impairment (MCI). Among them, plasma phosphorylated Tau217 (p-Tau217) demonstrates strong associations with cerebral amyloid deposition. In parallel, the easy Z-score Imaging System (eZIS), a quantitative brain perfusion SPECT analysis tool, has been widely used to detect characteristic AD-related hypoperfusion patterns. Although both measures reflect distinct AD processes, the relationship between plasma p-Tau217 and eZIS in MCI remains unclear. (2) Methods: This retrospective study included 62 patients with MCI who underwent plasma p-Tau217 testing and brain perfusion SPECT with eZIS analysis. Associations between plasma p-Tau217 and the three eZIS indices (severity, extent, and ratio) were evaluated. Exploratory subgroup analyses were performed using a previously reported plasma p-Tau217 threshold of 0.63 pg/mL. In addition, a validation sub-cohort of 21 participants who underwent plasma p-Tau217 testing, eZIS, and amyloid PET was analyzed to assess concordance with cerebral amyloid pathology. (3) Results: Among the three eZIS indices, severity demonstrated the highest sensitivity relative to elevated plasma p-Tau217 levels. However, all eZIS indices showed limited discriminative performance. Optimal eZIS cutoff values derived from the present cohort were higher than previously reported thresholds. In the amyloid PET-validated sub-cohort, plasma p-Tau217 demonstrated closer concordance with amyloid positivity than any individual eZIS parameter. The reduced performance of eZIS appeared to be associated with advanced age, substantial vascular burden, white matter lesions, and cerebral atrophy. (4) Conclusions: Plasma p-Tau217 showed a stronger association with cerebral amyloid pathology than eZIS indices in this elderly MCI cohort. Nevertheless, eZIS may provide complementary information regarding downstream neurodegenerative and cerebrovascular processes that are not directly captured by plasma biomarkers. This integrated approach highlights plasma p-Tau217 as a primary screening tool for amyloid pathology to guide disease-modifying therapies (DMTs), alongside eZIS for tracking follow-up mixed co-pathologies.

Relative importance of blood-based biomarkers for Alzheimer’s disease-specific neurodegeneration and cognitive decline

A stratified approach based on amyloid status is essential for the optimal application of blood-based biomarkers in monitoring disease progression and evaluating therapeutic efficacy in future clinical trials and precision medicine.

Blood transcriptomic signatures link β-amyloid deposition to molecular pathways across SCD, MCI, and dementia

Introduction Brain β-amyloid (Aβ) accumulation is a hallmark of Alzheimer’s disease, but noninvasive detection remains challenging. Blood transcriptomics may provide accessible biomarkers associated with Aβ pathology. Methods We integrated peripheral blood transcriptomic profiling and MRI-derived structural metrics from 48 individuals across the cognitive continuum, including subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia, stratified by Aβ-PET status. Predictive models were constructed using leave-one-out cross-validation (LOOCV), and selected genes were validated by qRT-PCR. Results Cross-stage analysis identified RUNX1T1 and COL14A1 as consistently downregulated in Aβ-positive individuals regardless of clinical stage. A predictive model incorporating these two genes demonstrated moderate discrimination of Aβ-PET status in internal leave-one-out cross-validation (LOOCV) evaluation (AUC = 0.81). In addition, COL14A1 expression was associated with cortical thickness and hippocampal volume, whereas RUNX1T1 was primarily associated with hippocampal structure. Among individuals with MCI or dementia, HCN1 and NRG3 were upregulated, whereas KCNMB2 was downregulated in Aβ-positive subjects. A three-gene model based on these markers achieved an LOOCV AUC of 0.79. Discussion These findings indicate that peripheral blood transcriptomic alterations are associated with Aβ pathology across clinical groups. RUNX1T1 and COL14A1 represent candidate peripheral biomarkers associated with Aβ pathology, while the observed molecular signatures and their associations with brain structural measures provide a basis for further validation in larger, longitudinal cohorts and mechanistic studies.