Associations of 18F‐RO‐948 Tau PET with Fluid AD Biomarkers, Centiloid, and Cognition in the Early AD Continuum
Authors: Shekari Mahnaz , Escalante Armand González , Milà‐Alomà Marta , Falcon Carles , López‐Martos David , Sánchez‐Benavides Gonzalo , Brugulat‐Serrat Anna , Niñerola‐Baizán Aida , Ashton Nicholas J. , Karikari Thomas K , Rodriguez Juan Lantero , Snellman Anniina , Day Theresa A. , Dage Jeffrey L. , Ortiz‐Romero Paula , Tonietto Matteo , Borroni Edilio , Klein Gregory , Kollmorgen Gwendlyn , Quijano‐Rubio Clara , Vanmechelen Eugeen , Minguillón Carolina , Fauria Karine , Perissinotti Andrés , Molinuevo Jose Luis , Zetterberg Henrik , Blennow Kaj , Grau‐Rivera Oriol , Suárez‐Calvet Marc , Gispert Juan Domingo 
Published: January 2025

Background

Fluid biomarkers provide a convenient way to predict AD pathophysiology. However, few studies have focused on determining associations with tau neurofibrillary tangle pathology in the early preclinical AD continuum, relevant to prevention strategies.

Methods

Ninety‐nine cognitively unimpaired individuals from the ALFA+ cohort with valid 18F‐RO‐948 and 18F‐flutemetamol PET, T1‐weighted MRI, cognition, CSF, and plasma biomarkers were included. Participants were initially categorized into AT stages using CSF‐based pre‐established cut‐off values [1]. Regional SUVR of 18F‐RO‐948 PET was calculated in entorhinal (BraakI/II), limbic (BraakIII/IV), and neocortical (BraakV/VI) regions using the inferior cerebellum as reference region as well as with the CenTAURz. Regional positivity thresholds per Braak stage were calculated as the median+2SD of the CSF A‐T‐ group. Amyloid PET was quantified using Centiloids. Pearson correlations were calculated between regional 18F‐RO‐948 SUVRs and AD biomarkers. ROC analyses adjusted for age, sex, and APOE‐e4 performed to evaluate the capacity of biomarkers in predicting BraakI/IIPositive. Four progressive PET‐derived AT groups were defined using Centiloid and tau PET positivity cut‐offs (A‐T‐, AGZT‐, A+T‐ and A+T+; with A‐ CL<12, 12=AGZ<38 and A+ CL=38 [2], and T+ BraakI/II>1.35) and between‐stage differences in z‐scored biomarkers evaluated using a Kruskal‐Wallis tests.

Results

Table 1 shows demographic information of participants. Nine(9.09%) participants were BraakI/IIPositive, seven(7.07%) BraakIII/IVPositive and one(1.01%) BraakV/VIPositive. Two BraakIII/IVPositive participants were BraakI/IINegative, deviating from the Braak hierarchical model. CSF biomarker correlations with BraakI/II SUVR (Figure 1‐A) ranged from r=0.24(ttau) to r=0.57(ptau217) and plasma (Figure 1‐B) from r=0.30(ptau217) to r=0.49(ptau181). Correlations survived adding age+sex+APOE‐e4 in the model (Figure 1‐C&D). CSF ptau181/Aß42, ptau217 and ptau205 showed an AUC=0.93 to predict BraakI/IIPositive, and plasma ptau181, ptau181/Aß42 and ptau217 had an AUC=0.84. Centiloid positivity threshold for BraakI/IIPositive was 38.14CL. Plasma ptau181, ptau181/Aß42, and CSF ptau205, ptau217, and ptau235 reached a mean z‐score>2 for the PET‐derived A+T+ group (Figure 2) which was associated with lower cognitive scores for executive function (p=0.03), attention (p=0.05), and the PACC (p=0.01).

Conclusion

18F‐RO‐948 PET conformed to the Braak hierarchical model for most tau‐positive participants. Fluid AD biomarkers showed moderate associations with tau PET SUVR. Plasma biomarkers showed good capacity to predict BraakI/IIPositive and track fibrillary amyloid and tau pathological changes in the early preclinical AD continuum.