Comparison of automated CLEIA and manual ELISA immunoassays for CSF AD biomarkers: The Fundació ACE Biomarker Research Program (FACEBREP). (31st December 2021)

• Record Type: Journal Article
• Authors: Orellana, Adelina; Valero, Sergi; Abdelnour, Carla; Montrreal, Laura; de Rojas, Itziar; Rosende‐Roca, Maitee; Mauleon, Ana; Vargas, Liliana; Tartari, Juan Pablo; Esteban‐De Antonio, Ester; García‐González, Pablo; Alarcón‐Martín, Emilio; Alegret, Montserrat; Alcolea, Daniel; Lleó, Alberto; Hernandez, Isabel; Tarraga, Lluis; Marquié, Marta; Boada, Mercè
• Is Part Of: Alzheimer's & dementia. Volume 17(2021)Supplement 5
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-12-31
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.051615
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Clinical diagnosis of Alzheimer's disease (AD) increasingly incorporate CSF biomarkers. However due to the intrinsic variability of the immunodetection techniques used to measure these biomarkers, it is recommended to establish in‐house cutoffs defining the positivity/negativity of CSF biomarkers. Method: We quantified CSF Aβ1‐42, t‐Tau, p181Tau and Aβ1‐40 with standard INNOTEST® ELISA and Lumipulse G® chemiluminescence enzyme‐immunoassay (CLEIA) performed on automated Lumipulse G600II. Determination of cutoffs included patients clinically diagnosed with Alzheimer Disease (AD, n=37) and amyloid‐negative Subjective Cognitive Decline subjects (SCD, n=45), cognitively stable during 3‐years and with no evidence of brain amyloidosis in 18 F‐Florbetaben‐labeled positron emission tomography (FBB‐PET). To compare both methods, a subset of samples for Aβ1‐42 (n=519), t‐Tau (n=399), p181Tau (n=77) and Aβ1‐40 (n=44) were analyzed. Kappa agreement of single biomarkers and Aβ1‐42/Aβ1‐40 was performed in an independent group of mild cognitive impairment (MCI) and dementia patients (n=68). Result: Cutoffs values of Aβ1‐42 and t‐Tau were higher for CLEIA than for ELISA and similar for p181Tau. Spearman coefficients ranged between 0.81 for Aβ1‐40 and 0.96 for p181TAU. Passing‐Bablok analysis showed a systematic and proportional difference for all biomarkers but only systematic for Aβ1‐40. Bland‐Altman analysis showed an average difference between methods in favor of CLEIA. Kappa agreement for single biomarkers were good but lower for Aβ1‐42/Aβ1‐40. Conclusion: We established internal cutoffs to discriminate AD patients from amyloid‐negative SCD individuals. Results obtained by both methods are not interchangeable but showed good agreement. We propose automated CLEIA as a good alternative to manual ELISA together with Aβ1‐42/Aβ1‐40 to classify amyloidosis.