Browsing by Author "Zeltzer, Ehud"

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    Amyloid and tau-PET in early-onset AD: Baseline data from the Longitudinal Early-onset Alzheimer's Disease Study (LEADS)
    (Wiley, 2023) Cho, Hanna; Mundada, Nidhi S.; Apostolova, Liana G.; Carrillo, Maria C.; Shankar, Ranjani; Amuiri, Alinda N.; Zeltzer, Ehud; Windon, Charles C.; Soleimani-Meigooni, David N.; Tanner, Jeremy A.; Heath, Courtney Lawhn; Lesman-Segev, Orit H.; Aisen, Paul; Eloyan, Ani; Lee, Hye Sun; Hammers, Dustin B.; Kirby, Kala; Dage, Jeffrey L.; Fagan, Anne; Foroud, Tatiana; Grinberg, Lea T.; Jack, Clifford R.; Kramer, Joel; Kukull, Walter A.; Murray, Melissa E.; Nudelman, Kelly; Toga, Arthur; Vemuri, Prashanthi; Atri, Alireza; Day, Gregory S.; Duara, Ranjan; Graff-Radford, Neill R.; Honig, Lawrence S.; Jones, David T.; Masdeu, Joseph; Mendez, Mario; Musiek, Erik; Onyike, Chiadi U.; Riddle, Meghan; Rogalski, Emily J.; Salloway, Stephen; Sha, Sharon; Turner, Raymond Scott; Wingo, Thomas S.; Wolk, David A.; Koeppe, Robert; Iaccarino, Leonardo; Dickerson, Bradford C.; La Joie, Renaud; Rabinovici, Gil D.; LEADS Consortium; Neurology, School of Medicine
    Introduction: We aimed to describe baseline amyloid-beta (Aβ) and tau-positron emission tomograrphy (PET) from Longitudinal Early-onset Alzheimer's Disease Study (LEADS), a prospective multi-site observational study of sporadic early-onset Alzheimer's disease (EOAD). Methods: We analyzed baseline [18F]Florbetaben (Aβ) and [18F]Flortaucipir (tau)-PET from cognitively impaired participants with a clinical diagnosis of mild cognitive impairment (MCI) or AD dementia aged < 65 years. Florbetaben scans were used to distinguish cognitively impaired participants with EOAD (Aβ+) from EOnonAD (Aβ-) based on the combination of visual read by expert reader and image quantification. Results: 243/321 (75.7%) of participants were assigned to the EOAD group based on amyloid-PET; 231 (95.1%) of them were tau-PET positive (A+T+). Tau-PET signal was elevated across cortical regions with a parietal-predominant pattern, and higher burden was observed in younger and female EOAD participants. Discussion: LEADS data emphasizes the importance of biomarkers to enhance diagnostic accuracy in EOAD. The advanced tau-PET binding at baseline might have implications for therapeutic strategies in patients with EOAD. Highlights: 72% of patients with clinical EOAD were positive on both amyloid- and tau-PET. Amyloid-positive patients with EOAD had high tau-PET signal across cortical regions. In EOAD, tau-PET mediated the relationship between amyloid-PET and MMSE. Among EOAD patients, younger onset and female sex were associated with higher tau-PET.
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    Amyloid‐PET in patients with a clinical diagnosis of sporadic early‐ versus late‐onset AD: comparison of the LEADS and ADNI cohorts
    (Wiley, 2025-01-09) Lagarde, Julien; Maiti, Piyush; Schonhaut, Daniel R.; Zhang, Jiaxiuxiu; Soleimani-meigooni, David N.; Zeltzer, Ehud; Windon, Charles; Raya, Maison Abu; Vrillon, Agathe; Hammers, Dustin B.; Dage, Jeffrey L.; Nudelman, Kelly N.; Eloyan, Ani; Koeppe, Robert A.; Landau, Susan M.; Carrillo, Maria C.; Touroutoglou, Alexandra; Vemuri, Prashanthi; Dickerson, Bradford C.; Apostolova, Liana G.; Rabinovici, Gil D.; La Joie, Renaud; LEADS Consortium, Alzheimer’s Disease Neuroimaging Initiative; Neurology, School of Medicine
    Background: Large‐scale studies comparing sporadic early‐onset AD (EOAD, age<65) and late‐onset AD (LOAD, age≥65) are lacking. We compared amyloid‐PET outcomes (positivity rate and amyloid burden) between patients clinically diagnosed with sporadic EOAD vs LOAD, leveraging data from the Longitudinal Early‐Onset AD Study (LEADS) and the Alzheimer’s Disease Neuroimaging Initiative 3 (ADNI3). Method: 731 patients meeting the 2011 NIA‐AA criteria for AD dementia or MCI were included (505 early‐onset from LEADS, 226 late‐onset from ADNI3, Table 1). All participants underwent amyloid‐PET with [18F]Florbetaben or [18F]Florbetapir. Amyloid positivity was centrally determined by a process involving a visual read by a trained expert and PET‐only quantification; in case of a discrepancy, a read from an independent physician acted as a tiebreaker. Logistic regressions in each cohort examined relations between amyloid positivity and age, sex, MMSE and APOE4 genotype. Amyloid burden was independently quantified in Centiloids using an MRI‐based pipeline. Mean Centiloids in LEADS and ADNI were compared with two‐way ANOVA, for visually positive and visually negative scans. Result: Amyloid positivity rate was higher in LEADS (76%) than ADNI (64%, p<0.001, Figure 1A). Lower MMSE and APOE4 genotype increased odds of amyloid positivity in both cohorts, although the APOE4 effect was stronger in ADNI than LEADS (OR=10.1 versus 2.4, p=0.007, Table 2). Amyloid positivity was more common in females across cohorts, but this effect was only statistically significant in LEADS (Table 2). Centiloids were bimodally distributed in both cohorts, although the separation between positive and negative scans was more prominent in LEADS (Figure 1B). Visually positive scans had significantly higher Centiloids in LEADS than in ADNI, whereas no cohort difference was observed for visually negative scans (Figure 1C). Sensitivity analyses showed that this effect was driven by patients with MCI (CDR≤0.5; Figure 1D‐E). Conclusion: The lower amyloid positivity rate in ADNI might be due to AD‐mimicking pathologies being more common at an older age. The higher amyloid burden in early‐onset, amyloid‐positive patients could reflect younger patients being diagnosed later in the disease course compared to typical, late‐onset patients. Alternatively, younger patients might tolerate higher neuropathology burden due to higher brain reserve or fewer co‐pathologies.
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    Reproducibility of Centiloid Values in Real‐World Amyloid PET Data: Comparison of the Imaging Dementia‐Evidence for Amyloid Scanning (IDEAS) to Four Large Research Datasets
    (Wiley, 2025-01-09) Blazhenets, Ganna; Zeltzer, Ehud; Lagarde, Julien; Landau, Susan M.; Koeppe, Robert A.; Carrillo, Maria C.; Dickerson, Bradford C.; Apostolova, Liana G.; Jagust, William J.; Rabinovici, Gil D.; La Joie, Renaud; Alzheimer’s Disease Neuroimaging Initiative (ADNI); Neurology, School of Medicine
    Background: The Centiloid framework was developed to harmonize amyloid‐PET quantification across radiotracers and processing pipelines to facilitate data sharing and merging; it is now widely used across research and clinical trials. As we just completed the quantification of 10,361 amyloid‐PET scans from the largest “real‐world” study of amyloid‐PET (IDEAS) and are about to release the data, we aimed to compare the distribution of IDEAS Centiloid values with other available datasets. Method: In IDEAS, amyloid scans were acquired across 343 facilities and centrally processed at UCSF using a PET‐only pipeline. We also had access to PET data from our own UCSF Alzheimer’s Disease Research Center and the LEADS study. Using the GAAIN platform, we identified two other cohorts with available Centiloids: ADNI and MCSA. For each cohort, we collected Centiloids, demographic, and basic clinical data. Gaussian mixture models (GMM) were fitted to Centiloid values for each cohort, and data‐driven Centiloid cutoffs were calculated as mean + 2SD of the first Gaussian. Finally, we compared Centiloids to PET visual reads (when available) and determined the Centiloid cutoff value maximizing correspondence between visual read and binarized Centiloids based on Cohen’s kappa. Result: The 5 cohorts were heterogeneous in terms of sample characteristics and radiotracers (Table 1). In all cohorts, a two‐Gaussian model was considered the best fit for the data based on the integrated completed likelihood criteria (Figure 1). The first Gaussian peaks were close to zero, with mild variability across studies (from ‐5 in IDEAS to 10 CL in MSCA). The second peak was more heterogeneous across cohorts (from 67 to 102 CL) with a rightward shift in cohorts enriched with clinically impaired patients. Mean Centiloid values in visually negative and positive scans generally matched well with results derived from GMM (Figure 2). Across all cohorts, GMM‐based Centiloid cutoffs tended to be slightly lower (18‐26) compared to those based on visual inspection (25‐31). Conclusion: The availability of Centiloids across cohorts enables a direct comparison of amyloid‐PET results in otherwise different studies. Despite some variability across cohorts and analysis methods, Centiloid cutoffs align well with thresholds from the existing literature.