Browsing by Author "Klein, Gregory"

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    Amyloid-Related Imaging Abnormalities in the DIAN-TU-001 Trial of Gantenerumab and Solanezumab: Lessons from a Trial in Dominantly Inherited Alzheimer Disease
    (Wiley, 2022) Joseph-Mathurin, Nelly; Llibre-Guerra, Jorge J.; Li, Yan; McCullough, Austin A.; Hofmann, Carsten; Wojtowicz, Jakub; Park, Ethan; Wang, Guoqiao; Preboske, Gregory M.; Wang, Qing; Gordon, Brian A.; Chen, Charles D.; Flores, Shaney; Aggarwal, Neelum T.; Berman, Sarah B.; Bird, Thomas D.; Black, Sandra E.; Borowski, Bret; Brooks, William S.; Chhatwal, Jasmeer P.; Clarnette, Roger; Cruchaga, Carlos; Fagan, Anne M.; Farlow, Martin; Fox, Nick C.; Gauthier, Serge; Hassenstab, Jason; Hobbs, Diana A.; Holdridge, Karen C.; Honig, Lawrence S.; Hornbeck, Russ C.; Hsiung, Ging-Yuek R.; Jack, Clifford R., Jr.; Jimenez-Velazquez, Ivonne Z.; Jucker, Mathias; Klein, Gregory; Levin, Johannes; Mancini, Michele; Masellis, Mario; McKay, Nicole S.; Mummery, Catherine J.; Ringman, John M.; Shimada, Hiroyuki; Snider, B. Joy; Suzuki, Kazushi; Wallon, David; Xiong, Chengjie; Yaari, Roy; McDade, Eric; Perrin, Richard J.; Bateman, Randall J.; Salloway, Stephen P.; Benzinger, Tammie L. S.; Clifford, David B.; Dominantly Inherited Alzheimer Network Trials Unit; Neurology, School of Medicine
    Objective: To determine the characteristics of participants with amyloid-related imaging abnormalities (ARIA) in a trial of gantenerumab or solanezumab in dominantly inherited Alzheimer disease (DIAD). Methods: 142 DIAD mutation carriers received either gantenerumab SC (n = 52), solanezumab IV (n = 50), or placebo (n = 40). Participants underwent assessments with the Clinical Dementia Rating® (CDR®), neuropsychological testing, CSF biomarkers, β-amyloid positron emission tomography (PET), and magnetic resonance imaging (MRI) to monitor ARIA. Cross-sectional and longitudinal analyses evaluated potential ARIA-related risk factors. Results: Eleven participants developed ARIA-E, including 3 with mild symptoms. No ARIA-E was reported under solanezumab while gantenerumab was associated with ARIA-E compared to placebo (odds ratio [OR] = 9.1, confidence interval [CI][1.2, 412.3]; p = 0.021). Under gantenerumab, APOE-ɛ4 carriers were more likely to develop ARIA-E (OR = 5.0, CI[1.0, 30.4]; p = 0.055), as were individuals with microhemorrhage at baseline (OR = 13.7, CI[1.2, 163.2]; p = 0.039). No ARIA-E was observed at the initial 225 mg/month gantenerumab dose, and most cases were observed at doses >675 mg. At first ARIA-E occurrence, all ARIA-E participants were amyloid-PET+, 60% were CDR >0, 60% were past their estimated year to symptom onset, and 60% had also incident ARIA-H. Most ARIA-E radiologically resolved after dose adjustment and developing ARIA-E did not significantly increase odds of trial discontinuation. ARIA-E was more frequently observed in the occipital lobe (90%). ARIA-E severity was associated with age at time of ARIA-E. Interpretation: In DIAD, solanezumab was not associated with ARIA. Gantenerumab dose over 225 mg increased ARIA-E risk, with additional risk for individuals APOE-ɛ4(+) or with microhemorrhage. ARIA-E was reversible on MRI in most cases, generally asymptomatic, without additional risk for trial discontinuation.
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    Comparison of Pittsburgh compound B and florbetapir in cross-sectional and longitudinal studies
    (Elsevier, 2019-02-22) Su, Yi; Flores, Shaney; Wang, Guoqiao; Hornbeck, Russ C.; Speidel, Benjamin; Joseph-Mathurin, Nelly; Vlassenko, Andrei G.; Gordon, Brian A.; Koeppe, Robert A.; Klunk, William E.; Clifford, R. Jack, Jr.; Farlow, Martin R.; Salloway, Stephen; Snider, Barbara J.; Berman, Sarah B.; Roberson, Erik D.; Broschi, Jared; Jimenez-Velazques, Ivonne; van Dyck, Christopher H.; Galasko, Douglas; Yuan, Shauna H.; Jayadev, Suman; Honig, Lawrence S.; Gauthier, Serge; Hsiung, Ging-Yuek R.; Masellis, Mario; Brooks, William S.; Fulham, Michael; Clarnette, Roger; Masters, Colin L.; Wallon, David; Hannequin, Didier; Dubois, Bruno; Pariente, Jeremie; Sanchez-Valle, Raquel; Mummery, Catherine; Ringman, John M.; Bottlaender, Michel; Klein, Gregory; Milosavljevic-Ristic, Smiljana; McDade, Eric; Xiong, Chengjie; Morris, John C.; Bateman, Randall J.; Benzinger, Tammie L.S.; Neurology, School of Medicine
    Introduction: Quantitative in vivo measurement of brain amyloid burden is important for both research and clinical purposes. However, the existence of multiple imaging tracers presents challenges to the interpretation of such measurements. This study presents a direct comparison of Pittsburgh compound B-based and florbetapir-based amyloid imaging in the same participants from two independent cohorts using a crossover design. Methods: Pittsburgh compound B and florbetapir amyloid PET imaging data from three different cohorts were analyzed using previously established pipelines to obtain global amyloid burden measurements. These measurements were converted to the Centiloid scale to allow fair comparison between the two tracers. The mean and inter-individual variability of the two tracers were compared using multivariate linear models both cross-sectionally and longitudinally. Results: Global amyloid burden measured using the two tracers were strongly correlated in both cohorts. However, higher variability was observed when florbetapir was used as the imaging tracer. The variability may be partially caused by white matter signal as partial volume correction reduces the variability and improves the correlations between the two tracers. Amyloid burden measured using both tracers was found to be in association with clinical and psychometric measurements. Longitudinal comparison of the two tracers was also performed in similar but separate cohorts whose baseline amyloid load was considered elevated (i.e., amyloid positive). No significant difference was detected in the average annualized rate of change measurements made with these two tracers. Discussion: Although the amyloid burden measurements were quite similar using these two tracers as expected, difference was observable even after conversion into the Centiloid scale. Further investigation is warranted to identify optimal strategies to harmonize amyloid imaging data acquired using different tracers.
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    Genome sequencing analysis identifies new loci associated with Lewy body dementia and provides insights into its genetic architecture
    (Springer Nature, 2021-03) Chia, Ruth; Sabir, Marya S.; Bandres-Ciga, Sara; Saez-Atienzar, Sara; Reynolds, Regina H.; Gustavsson, Emil; Walton, Ronald L.; Ahmed, Sarah; Viollet, Coralie; Ding, Jinhui; Makarious, Mary B.; Diez-Fairen, Monica; Portley, Makayla K.; Shah, Zalak; Abramzon, Yevgeniya; Hernandez, Dena G.; Blauwendraat, Cornelis; Stone, David J.; Eicher, John; Parkkinen, Laura; Ansorge, Olaf; Clark, Lorraine; Honig, Lawrence S.; Marder, Karen; Lemstra, Afina; St. George-Hyslop, Peter; Londos, Elisabet; Morgan, Kevin; Lashley, Tammaryn; Warner, Thomas T.; Jaunmuktane, Zane; Galasko, Douglas; Santana, Isabel; Tienari, Pentti J.; Myllykangas, Liisa; Oinas, Minna; Cairns, Nigel J.; Morris, John C.; Halliday, Glenda M.; Van Deerlin, Vivianna M.; Trojanowski, John Q.; Grassano, Maurizio; Calvo, Andrea; Mora, Gabriele; Canosa, Antonio; Floris, Gianluca; Bohannan, Ryan C.; Brett, Francesca; Gan-Or, Ziv; Geiger, Joshua T.; Moore, Anni; May, Patrick; Krüger, Rejko; Goldstein, David S.; Lopez, Grisel; Tayebi, Nahid; Sidransky, Ellen; Norcliffe-Kaufmann, Lucy; Palma, Jose-Alberto; Kaufmann, Horacio; Shakkottai, Vikram G.; Perkins, Matthew; Newell, Kathy L.; Gasser, Thomas; Schulte, Claudia; Landi, Francesco; Salvi, Erika; Cusi, Daniele; Masliah, Eliezer; Kim, Ronald C.; Caraway, Chad A.; Monuki, Edwin S.; Brunetti, Maura; Dawson, Ted M.; Rosenthal, Liana S.; Albert, Marilyn S.; Pletnikova, Olga; Troncoso, Juan C.; Flanagan, Margaret E.; Mao, Qinwen; Bigio, Eileen H.; Rodríguez-Rodríguez, Eloy; Infante, Jon; Lage, Carmen; González-Aramburu, Isabel; Sanchez-Juan, Pascual; Ghetti, Bernardino; Keith, Julia; Black, Sandra E.; Masellis, Mario; Rogaeva, Ekaterina; Duyckaerts, Charles; Brice, Alexis; Lesage, Suzanne; Xiromerisiou, Georgia; Barrett, Matthew J.; Tilley, Bension S.; Gentleman, Steve; Logroscino, Giancarlo; Serrano, Geidy E.; Beach, Thomas G.; McKeith, Ian G.; Thomas, Alan J.; Attems, Johannes; Morris, Christopher M.; Palmer, Laura; Love, Seth; Troakes, Claire; Al-Sarraj, Safa; Hodges, Angela K.; Aarsland, Dag; Klein, Gregory; Kaiser, Scott M.; Woltjer, Randy; Pastor, Pau; Bekris, Lynn M.; Leverenz, James B.; Besser, Lilah M.; Kuzma, Amanda; Renton, Alan E.; Goate, Alison; Bennett, David A.; Scherzer, Clemens R.; Morris, Huw R.; Ferrari, Raffaele; Albani, Diego; Pickering-Brown, Stuart; Faber, Kelley; Kukull, Walter A.; Morenas-Rodriguez, Estrella; Lleó, Alberto; Fortea, Juan; Alcolea, Daniel; Clarimon, Jordi; Nalls, Mike A.; Ferrucci, Luigi; Resnick, Susan M.; Tanaka, Toshiko; Foroud, Tatiana M.; Graff-Radford, Neill R.; Wszolek, Zbigniew K.; Ferman, Tanis; Boeve, Bradley F.; Hardy, John A.; Topol, Eric J.; Torkamani, Ali; Singleton, Andrew B.; Ryten, Mina; Dickson, Dennis W.; Chiò, Adriano; Ross, Owen A.; Gibbs, J. Raphael; Dalgard, Clifton L.; Traynor, Bryan J.; Scholz, Sonja W.; Pathology and Laboratory Medicine, School of Medicine
    The genetic basis of Lewy body dementia (LBD) is not well understood. Here, we performed whole-genome sequencing in large cohorts of LBD cases and neurologically healthy controls to study the genetic architecture of this understudied form of dementia, and to generate a resource for the scientific community. Genome-wide association analysis identified five independent risk loci, whereas genome-wide gene-aggregation tests implicated mutations in the gene GBA. Genetic risk scores demonstrate that LBD shares risk profiles and pathways with Alzheimer's disease and Parkinson's disease, providing a deeper molecular understanding of the complex genetic architecture of this age-related neurodegenerative condition.
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    Longitudinal head-to-head comparison of 11C-PiB and 18F-florbetapir PET in a Phase 2/3 clinical trial of anti-amyloid-β monoclonal antibodies in dominantly inherited Alzheimer disease
    (Springer, 2023) Chen, Charles D.; McCullough, Austin; Gordon, Brian; Joseph-Mathurin, Nelly; Flores, Shaney; McKay, Nicole S.; Hobbs, Diana A.; Hornbeck, Russ; Fagan, Anne M.; Cruchaga, Carlos; Goate, Alison M.; Perrin, Richard J.; Wang, Guoqiao; Li, Yan; Shi, Xinyu; Xiong, Chengjie; Pontecorvo, Michael J.; Klein, Gregory; Su, Yi; Klunk, William E.; Jack, Clifford; Koeppe, Robert; Snider, B. Joy; Berman, Sarah B.; Roberson, Erik D.; Brosch, Jared; Surti, Ghulam; Jiménez-Velázquez, Ivonne Z.; Galasko, Douglas; Honig, Lawrence S.; Brooks, William S.; Clarnette, Roger; Wallon, David; Dubois, Bruno; Pariente, Jérémie; Pasquier, Florence; Sanchez-Valle, Raquel; Shcherbinin, Sergey; Higgins, Ixavier; Tunali, Ilke; Masters, Colin L.; van Dyck, Christopher H.; Masellis, Mario; Hsiung, Robin; Gauthier, Serge; Salloway, Steve; Clifford, David B.; Mills, Susan; Supnet-Bell, Charlene; McDade, Eric; Bateman, Randall J.; Benzinger, Tammie L. S.; DIAN-TU Study Team; Neurology, School of Medicine
    Purpose: Pittsburgh Compound-B (11C-PiB) and 18F-florbetapir are amyloid-β (Aβ) positron emission tomography (PET) radiotracers that have been used as endpoints in Alzheimer's disease (AD) clinical trials to evaluate the efficacy of anti-Aβ monoclonal antibodies. However, comparing drug effects between and within trials may become complicated if different Aβ radiotracers were used. To study the consequences of using different Aβ radiotracers to measure Aβ clearance, we performed a head-to-head comparison of 11C-PiB and 18F-florbetapir in a Phase 2/3 clinical trial of anti-Aβ monoclonal antibodies. Methods: Sixty-six mutation-positive participants enrolled in the gantenerumab and placebo arms of the first Dominantly Inherited Alzheimer Network Trials Unit clinical trial (DIAN-TU-001) underwent both 11C-PiB and 18F-florbetapir PET imaging at baseline and during at least one follow-up visit. For each PET scan, regional standardized uptake value ratios (SUVRs), regional Centiloids, a global cortical SUVR, and a global cortical Centiloid value were calculated. Longitudinal changes in SUVRs and Centiloids were estimated using linear mixed models. Differences in longitudinal change between PET radiotracers and between drug arms were estimated using paired and Welch two sample t-tests, respectively. Simulated clinical trials were conducted to evaluate the consequences of some research sites using 11C-PiB while other sites use 18F-florbetapir for Aβ PET imaging. Results: In the placebo arm, the absolute rate of longitudinal change measured by global cortical 11C-PiB SUVRs did not differ from that of global cortical 18F-florbetapir SUVRs. In the gantenerumab arm, global cortical 11C-PiB SUVRs decreased more rapidly than global cortical 18F-florbetapir SUVRs. Drug effects were statistically significant across both Aβ radiotracers. In contrast, the rates of longitudinal change measured in global cortical Centiloids did not differ between Aβ radiotracers in either the placebo or gantenerumab arms, and drug effects remained statistically significant. Regional analyses largely recapitulated these global cortical analyses. Across simulated clinical trials, type I error was higher in trials where both Aβ radiotracers were used versus trials where only one Aβ radiotracer was used. Power was lower in trials where 18F-florbetapir was primarily used versus trials where 11C-PiB was primarily used. Conclusion: Gantenerumab treatment induces longitudinal changes in Aβ PET, and the absolute rates of these longitudinal changes differ significantly between Aβ radiotracers. These differences were not seen in the placebo arm, suggesting that Aβ-clearing treatments may pose unique challenges when attempting to compare longitudinal results across different Aβ radiotracers. Our results suggest converting Aβ PET SUVR measurements to Centiloids (both globally and regionally) can harmonize these differences without losing sensitivity to drug effects. Nonetheless, until consensus is achieved on how to harmonize drug effects across radiotracers, and since using multiple radiotracers in the same trial may increase type I error, multisite studies should consider potential variability due to different radiotracers when interpreting Aβ PET biomarker data and, if feasible, use a single radiotracer for the best results.