Back to Authors

Soleimani‐Meigooni, David N.

Mayo Clinic

University of California, San Francisco

Citations 2

Aβ‐dependent trajectories of Braak stages for MK6240 and Flortaucipir tau PET
Bellaver, Bruna, Povala, Guilherme, Ferreira, Pamela C.L., Amaral, Lívia , Rocha, Andreia, Masdeu, Joseph C. , Tudorascu, DL, Karikari, Thomas K, Soleimani‐Meigooni, David N., Fortea, Juan M., Lowe, VJ, Oh, Hwamee, Pascual, Belen, Gordon, Brian A., Rosa‐Neto, Pedro, Baker, Suzanne L. , Pascoal, Tharick A, Pascual, Belén , Rocha, Andréia Silva da , Pascual, Belen , Bellaver, Bruna , Povala, Guilherme , Ferreira, Pâmela C.L. , Bauer‐Negrini, Guilherme , Lussier, Firoza Zubeida , Rocha, Andreia, Masdeu, Joseph C , Tudorascu, Dana , Karikari, Thomas K. , Soleimani‐Meigooni, David N. , Fortea, Juan , Oh, Hwamee , Gordon, Brian A. , Rosa-Neto, Pedro , Pascoal, Tharick Ali

Alzheimer's & Dementia | January 10, 2026 | Volume: 21 | Issue: S2 | Pages: No page available

10.1002/alz70856_107040 Get It

Abstract Background Tau accumulation in the brain is postulated to follow a hierarchical pattern, known as Braak staging, originally defined in postmortem brains. PET‐based Braak stages have since been proposed, however, tau PET tracers exhibit distinct binding characteristics that might influence the detectable trajectories of tau accumulation and its relationship with other biomarkers across the AD continuum. In a head‐to‐head study, we investigated the emergence of tau positivity in each Braak region, along with plasma p ‐tau217 and GFAP, as a function of Aβ PET deposition. Method We evaluated 352 individuals from the HEAD study (205 cognitively unimpaired and 147 cognitively impaired) with head‐to‐head Aβ PET, MK6240 and Flortaucipir tau PET, and plasma p ‐tau217 (ALZpath) and GFAP (Quanterix) measures. Tau PET Braak regions, plasma p ‐tau217 and GFAP trajectories were modeled as functions of Aβ burden (Centiloid scale) using the Lowess method. Biomarkers were z‐scored anchored on young individuals ( n = 19, <28 years old). Positivity for plasma biomarkers and for each Braak region was determined when values surpassed 2.5 z‐score from the mean. Result Among the tested markers, plasma GFAP was the earliest to show abnormality as a function of Centiloid, occurring at 11 Centiloids. For MK6240, Braak I was the first regions to became positive (at 22 Centiloids), followed by Braak II (at 32 Centiloids), Braak IV (at 42 Centiloids), Braak III (at 52 Centiloids), Braak V (at 70 Centiloids) and Braak VI (at 123 Centiloid; Figure 1A). For Flortaucipir the first region to became positive was Braak IV (at 50 Centiloids), followed by Braak I and II (both at 56 Centiloids), Braak III (at 85 Centiloids) and Braak V (at 92 Centiloids). Braak VI region did not reach the threshold for positivity in our population (Figure 1B). Plasma p ‐tau217 reached the positivity threshold at 38 Centiloids. Conclusion MK6240 follows a Braak stage‐like pattern of abnormality as a function of Aβ burden, whereas for Flortaucipir, Braak IV is the first region to became abnormal. MK6240 becomes abnormal at lower Aβ burden levels compared to plasma p ‐tau217 and Flortaucipir but after plasma GFAP. Our findings suggest that MK6240 might detect tau pathology in earlier disease stages than Flortaucipir.
Head‐to‐head in vivo Braak staging with MK6240 and Flortaucipir
Rocha, Andreia, Bellaver, Bruna, Madeiros, Marina Scop, Soares, Carolina, Ferreira, Pamela C.L., Povala, Guilherme, Amaral, Lívia , Masdeu, Joseph C. , Tudorascu, DL, Soleimani‐Meigooni, David N., Fortea, Juan M., Lowe, VJ, Oh, Hwamee, Pascual, Belen, Gordon, Brian A., Rosa‐Neto, Pedro, Baker, Suzanne L. , Pascoal, Tharick A, Pascual, Belén , Medeiros, Marina Scop , Pascual, Belen , Rocha, Andreia, Bellaver, Bruna , Ruppert, Emma Patrice , Madeiros, Marina Scop, Soares, Carolina , Ferreira, Pâmela C.L. , Povala, Guilherme , Bauer‐Negrini, Guilherme , Lussier, Firoza Zubeida , Rodrigues, Matheus Scarpatto , Masdeu, Joseph C , Tudorascu, Dana , Soleimani‐Meigooni, David N. , Fortea, Juan , Oh, Hwamee , Gordon, Brian A. , Rosa-Neto, Pedro , Pascoal, Tharick Ali

Alzheimer's & Dementia | January 9, 2026 | Volume: 21 | Issue: S2 | Pages: No page available

10.1002/alz70856_107534 Get It

Abstract Background In vivo Braak staging stratifies patients across the AD spectrum and has the potential to harmonize tau PET tracer staging. This study aims to compare and test harmonization procedures for Braak staging individuals using MK6240 and Flortaucipir tau PET tracers. Methods We assessed 437 participants across the AD spectrum (245 cognitively unimpaired (CU) and 192 cognitively impaired; mean age 68.5 ± 8.6) using head‐to‐head MK6240 and Flortaucipir scans. We computed SUVRs in Braak regions of interest (ROIs) and assessed four cut‐off methods for Braak positivity: (a) mean + 2.5 SD of young controls (age <28 years), (b) mean + 2.5 SD of elderly CU Aβ−, (c) Gaussian mixture modeling (GMM), and (d) the Youden index. Braak stages were assigned using seven (0 to VI) or four (0, I–II, III–IV, V–VI) categories. We evaluated inter‐ and intra‐tracer concordance (intra‐tracer, i.e., whether it follows the sequential Braak pattern). Results The intra‐tracer seven‐class Braak staging concordance ranged from 63% to 94%. With the highest intra‐tracer Braak concordance being achieved when using GMM cutoffs: 94% (MK6240) and 89% (Flortaucipir; Figure 1). Inter‐tracer agreement concordance ranged from 56% to 76%. The highest concordance emerged from the CU Elderly Aβ– cutoff optimizing the Braak II region for spill‐off (Figure 2). Using the Braak staging simplified version improved intra‐tracer concordance in both tracers (MK6240as well as inter‐tracer agreement (86.5%). Most inter‐tracer discrepancies were observed at Braak stages II–IV. Despite showing staging discordances, the distribution of cognitive status across the Braak stages is similar for both tracers (Figure 3). Conclusion These preliminary findings reveal some discrepancies in Braak staging when comparing MK6240 and Flortaucipir. Our results also suggest that adjustments in cutoffs and regions of interest can partially mitigate both inter‐ and intra‐tracer divergences. Finally, our analysis suggests robust concordance after adjustment and using 4 classes (0, I‐II, III‐IV, V‐VI).