Background Blood-based biomarkers for Alzheimer’s disease (AD) might facilitate identification of participants for clinical trials targeting amyloid beta (Abeta) accumulation, and aid in AD diagnostics. We examined the potential of plasma markers Abeta(1-42/1-40), glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) to identify cerebral amyloidosis and/or disease severity. Methods We included individuals with a positive (n = 176: 63 ± 7 years, 87 (49%) females) or negative (n = 76: 61 ± 9 years, 27 (36%) females) amyloid PET status, with syndrome diagnosis subjective cognitive decline (18 PET+, 25 PET−), mild cognitive impairment (26 PET+, 24 PET−), or AD-dementia (132 PET+). Plasma Abeta(1-42/1-40), GFAP, and NfL were measured by Simoa. We applied two-way ANOVA adjusted for age and sex to investigate the associations of the plasma markers with amyloid PET status and syndrome diagnosis; logistic regression analysis with Wald’s backward selection to identify an optimal panel that identifies amyloid PET positivity; age, sex, and education-adjusted linear regression analysis to investigate associations between the plasma markers and neuropsychological test performance; and Spearman’s correlation analysis to investigate associations between the plasma markers and medial temporal lobe atrophy (MTA). Results Abeta(1-42/1-40) and GFAP independently associated with amyloid PET status (p = 0.009 and p < 0.001 respectively), and GFAP and NfL independently associated with syndrome diagnosis (p = 0.001 and p = 0.048 respectively). The optimal panel identifying a positive amyloid status included Abeta(1-42/1-40) and GFAP, alongside age and APOE (AUC = 88% (95% CI 83–93%), 82% sensitivity, 86% specificity), while excluding NfL and sex. GFAP and NfL robustly associated with cognitive performance on global cognition and all major cognitive domains (GFAP: range standardized β (sβ) = − 0.40 to − 0.26; NfL: range sβ = − 0.35 to − 0.18; all: p < 0.002), whereas Abeta(1-42/1-40) associated with global cognition, memory, attention, and executive functioning (range sβ = 0.22 – 0.11; all: p < 0.05) but not language. GFAP and NfL showed moderate positive correlations with MTA (both: Spearman’s rho> 0.33, p < 0.001). Abeta(1-42/1-40) showed a moderate negative correlation with MTA (Spearman’s rho = − 0.24, p = 0.001). Discussion and conclusions Combination of plasma Abeta(1-42/1-40) and GFAP provides a valuable tool for the identification of amyloid PET status. Furthermore, plasma GFAP and NfL associate with various disease severity measures suggesting potential for disease monitoring.

Introduction: Pre-analytical sample handling might affect the results of Alzheimer's disease blood-based biomarkers. We empirically tested variations of common blood collection and handling procedures. Methods:We created sample sets that address the effect of blood collection tube type, and of ethylene diamine tetraacetic acid plasma delayed centrifugation, centrifugation temperature, aliquot volume, delayed storage, and freeze-thawing. We measuredThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Background Variation in pre‐analytical sample handling can critically affect biomarker concentrations in biofluids. A study on pre‐analytical effects on novel blood‐based biomarkers is therefore of importance to facilitate their swift introduction in clinical settings. Guided by the Alzheimer’s Association, we established a biorepository of systematically “mistreated” blood samples for analysis of various biomarkers using various technologies. Here we present the first results. Method Blood samples were collected from 90 volunteers presenting at the hospital for any disease. Blood was mistreated according to 8 pre‐analytical protocols, resulting in n=10 sample sets per protocol with several aliquots per set to be shared among labs for biomarker analysis. The protocols were designed to test the effects of type of collection tube, and the effects on K2‐EDTA plasma of delayed centrifugation (at room temperature (RT) or 4°C), centrifugation temperature (RT or 4°C), delayed freezing after centrifugation (RT or 4°C), two‐week intermittent storage at low temperature (4°C or ‐20°C), freezing‐thawing (up to 4x) and aliquot tube filling (250µl, 500µl or 1000µl in 1.5‐mL tube). Using a novel 4‐plex Simoa assay simultaneously measuring Abeta(1‐42), Abeta(1‐40), GFAP and NfL, we obtained the first results on our sample sets. A decline was regarded relevant when a change of at least a 10% was observed in the biomarker value compared to the reference conditions. Result Collection tube type affected the levels of the assessed markers Abeta(1‐42/1‐40), GFAP and NfL (Figure 1). Delayed centrifugation affected only plasma Abeta(1‐42/1‐40), and only when kept at RT for 24h (average ‐18% decline compared to no delay) and not when kept at 4°C (Figure 2). This same pattern was observed for hold time after centrifugation (Abeta(1‐42/1‐40): ‐16% for 24h hold at RT). Two‐week storage at 4°C but not at ‐20°C affected only Abeta(1‐42/1‐40) (average ‐15%). Centrifugation temperature, up to four freeze‐thaw cycles and aliquot tube filling did not affect the biomarker values Abeta(1‐42/1‐40), GFAP and NfL. Conclusion These first results of the project on pre‐analytical effects on novel blood‐based biomarker concentrations show that relevant pre‐analytical effects exist and that it is essential to work towards unified standard operating procedures for blood sample collection, handling and storage.

Background: Pre-analytical sample handling might affect the results of Alzheimer's blood-based biomarkers. In this collaborative study of the SABB-GBSC working group guided by the Alzheimer's Association, we elucidate the effects of the most common sample handling variations on blood-based amyloid and non-amyloid biomarkers. Method:Freshly collected blood was differentially treated, to create sample sets (n=10 per condition). We investigated the effect of collection tube type, and of EDTA plasma handling variations: delayed centrifugation, centrifugation temperature, aliquot volume, delayed storage, and freeze-thawing. Frozen aliquots were shipped to participating labs, to measure amyloid beta (Abeta) peptides (with different technologies: C 2 N LS-mass spectrometry (MS), Shimadzu MALID-MS, N4PE and N3PA Simoa, Euroimmun and Araclon ELISA), Abeta oligomerization tendency (OAβ; PeopleBio), glial fibrillary acidic protein (GFAP; Quanterix), neurofilament light (NfL; Quanterix), total tau (tTau; Quanterix) and phosphorylated tau181 (pTau181; Eli Lilly Simoa assay). Data analysis was descriptive.Result: Using other sample types than EDTA plasma resulted in different absolute levels for most of the measured biomarkers (figures 1-4), with generally higher levels in lithium-heparin plasma, lower levels in sodium-citrate plasma, and variable but comparable levels in serum. Independent of the technology used, when EDTA plasma was kept at room temperature pre-or post-centrifugation, Abeta42 and Abeta40 levels remained stable for up to 3 hours, while at 24 hours levels were decreased. When kept at 2-8 • C, Abeta levels were stable for up to 24 hours delayed centrifugation or storage (figure 1 and 2). The Abeta42/40 ratio mitigated some of the variability noted in Abeta42 and Abeta40 levels for some of the technologies and conditions, but not for all (figure 3). Abeta42 and Abeta40 levels were robust to differences in tube filling, short-term -20 • C storage, and up to 4 freeze-thaw cycles (figure 1 and 2). While the other biomarkers OAβ, GFAP, NfL and pTau181 were mostly resistant to pre-analytical