Introduction Studies using different assays and technologies showed highly promising diagnostic value of plasma phosphorylated (P-)tau levels for Alzheimer’s disease (AD). We aimed to compare six P-tau Simoa assays, including three P-tau181 (Eli Lilly, ADx, Quanterix), one P-tau217 (Eli Lilly), and two P-tau231 (ADx, Gothenburg). Methods We studied the analytical (sensitivity, precision, parallelism, dilution linearity, and recovery) and clinical (40 AD dementia patients, age 66±8years, 50%F; 40 age- and sex-matched controls) performance of the assays. Results All assays showed robust analytical performance, and particularly P-tau217 Eli Lilly; P-tau231 Gothenburg and all P-tau181 assays showed robust clinical performance to differentiate AD from controls, with AUCs 0.936–0.995 (P-tau231 ADx: AUC = 0.719). Results obtained with all P-tau181 assays, P-tau217 Eli Lilly assay, and P-tau231 Gothenburg assay strongly correlated (Spearman’s rho > 0.86), while correlations with P-tau231 ADx results were moderate (rho < 0.65). Discussion P-tau isoforms can be measured robustly by several novel high-sensitive Simoa assays.

BackgroundSeveral blood‐based biomarkers for Alzheimer’s disease (AD) can now be reliably measured. It is not yet clear how those markers should be interpreted in a real‐world clinical setting, where a heterogeneous group of patients presents in different syndromal stages and with different symptoms. We aim to establish a ready‐to‐implement blood‐based biomarker panel including Abeta1‐42/1‐40, P‐tau181, GFAP and NfL with cutoffs for clinical application among subjective cognitive decline (SCD), mild cognitive impairment (MCI), AD‐dementia, frontotemporal dementia (FTD) and dementia with Lewy bodies (DLB).MethodWe included n=1132 individuals of the Amsterdam Dementia Cohort (table 1) with known baseline amyloid‐beta (Aβ) status, who had SCD (n=237 Aβ‐, n=66 Aβ+), MCI (n=108 Aβ‐, n=151 Aβ+), AD‐dementia (n=297, all Aβ+), FTD (n=162 of whom n=121 Aβ) or DLB (n=111 of whom n=53 Aβ‐). Plasma markers were measured with Simoa (neurology 4‐plex E, P‐tau181 V2). We applied ROC analysis and subsequently LASSO regression to identify panels among the plasma markers.ResultROC analysis (table 2, figure 1) showed that among SCD and MCI, AUCs of the individual plasma markers to predict Aβ status were 0.738–0.799 (lowest for NfL, highest for P‐tau181). LASSO regression (table 2, figure 1) selected Abeta1‐42/1‐40, P‐tau181 and GFAP, but not NfL as the optimal panel (AUC=0.846, 95%CI: 0.812–0.880). Stratifying for SCD or MCI stage resulted in largely similar findings (not shown). When discriminating AD from FTD, AUCs of the individual plasma markers were 0.643–0.820 (lowest for Abeta1‐42/1‐40, highest for P‐tau). LASSO regression selected P‐tau181, GFAP and NfL as the optimal panel (AUC=0.889, 95%CI: 0.850–0.927). For AD versus DLB, AUCs were 0.514–0.741 (lowest for NfL, highest for P‐tau181). LASSO regression selected only P‐tau181 (AUC=0.741, 95%CI: 0.683–0.800). Plasma marker cutoffs at Youden’s indices differed depending on the diagnostic groups, with higher cutoffs for P‐tau181, GFAP and NfL in AD versus FTD or DLB analyses, compared to the SCD and MCI analyses (table 2).ConclusionWe showed that depending on the clinical question at hand, the four biomarkers add valuable information with their own cutoffs. Decision trees might lead to ready‐to‐apply cutoffs for daily clinical practice.

BackgroundBlood‐based biomarkers can provide a non‐invasive and accessible way to identify neurodegenerative diseases before the clinical onset of dementia. Our study aimed to examine whether levels of phosphorylated‐tau‐181 (pTau181), amyloid beta1‐42/1‐40 (Aβ42/40), glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) are associated with risk of developing dementia in a memory clinic population of individuals with either subjective cognitive decline (SCD) or mild cognitive impairment (MCI).MethodFrom the Amsterdam Dementia Cohort we included 311 individuals with SCD (age 61±9 years, n=128 (41%) female, MMSE 29±1) and 252 with MCI (age 65±7 years, n=89 (35%) female, MMSE 27±2), who had annual follow‐up visits for re‐evaluation of diagnosis (average follow‐up duration: 2.7±1.7 years.) Baseline plasma biomarkers were measured using Simoa and the associations of the Z‐transformed biomarker concentrations with incident dementia were evaluated using Cox regression models adjusted for age, sex, baseline diagnosis and the interaction between baseline diagnosis (SCD/MCI) and the biomarker concentration. The markers were first evaluated individually and then simultaneously in a combined model. We stratified results for baseline diagnosis when the biomarker*diagnosis interaction was significant.ResultDuring follow‐up, 94 individuals developed dementia (14 with SCD, 80 with MCI at baseline, 86 Alzheimer’s Disease, 8 other forms of dementia; average time to progression: 2.8±1.8 years). We found an interaction between baseline diagnosis and NfL for incident dementia (p=0.03). No other interactions were found. In the total set, both high baseline pTau181 (hazard ratio (HR)=3.4 (95%CI: 1.3–9.0); figure 1A), and high baseline GFAP (HR=5.5 (95%CI: 1.6–18.6); figure 1B) were associated with increased risk of dementia, but the association with Aβ42/40 was not significant (HR=0.4 (95%CI: 0.2–1.1)). NfL had no significant association with increased dementia incident risk in both SCD subset (HR=1.8, (95%CI: 0.9‐3.6)) and the MCI subset (HR= 1.3, (95%CI: 1.0–1.6)). When we simultaneously entered all biomarkers, pTau181 and GFAP remained significantly associated with incident dementia (table 1.)ConclusionOur results suggest that plasma GFAP and pTau181 have prognostic value to predict dementia in individuals presenting at a memory clinic.