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Chadwick, Trevor

Mayo Clinic

University of California, Berkeley

Citations 6

Correlation between in vivo 18 F‐flortaucipir PET and whole‐brain postmortem histological tau signals in Alzheimer's disease
Chao, Yishu , Chen, Y., Chadwick, Trevor A., Harrison, Theresa M., Iaccarino, Leonardo, Heinsen, Helmut, Ushizima, Daniela, Tosun, Duygu, Jagust, William J., Grinberg, Lea T. , Chen, Yuheng, Grinberg, Lea , Chadwick, Trevor, Harrison, Theresa M. , Iaccarino, Leonardo , Heinsen, Helmut, Ushizima, Daniela Mayumi , Jagust, William J.

Alzheimer's & Dementia | May 11, 2026 | Volume: 22 | Issue: 5 | Pages: No page available

10.1002/alz.71453 Get It

Abstract INTRODUCTION Clinicopathological studies offer crucial interpretations of 18 F‐flortaucipir (FTP) tau positron emission tomography (PET) signal but are limited by methods. We leveraged whole‐brain, quantitative immunohistochemical (IHC) Alzheimer's Disease (AD) tau density maps to comprehensively evaluate the FTP tracer. METHODS We generated IHC maps for three AD‐tau antibodies—AT8, AT100, and MC1—using two human brains histologically staged at Braak IV and VI. FTP‐PET scans were acquired 6 and 10 weeks prior to death. Using region‐wise and voxelwise methods, we correlated FTP‐PET with IHC signals. RESULTS Only AT8 (p‐tau Ser202/Thr205; neuronal and neuritic tau pathology) showed a notable correlation with FTP standardized uptake value ratios (SUVRs) in the Braak VI case (Spearman's rank correlation coefficient [r s ] = 0.461, p < 0.001). FTP SUVRs failed to capture medial temporal lobe (MTL) tau burden, whereas neocortical regions showed lower IHC burden but more variability in FTP uptake. DISCUSSION Although FTP signals correlate well with AT8‐positive tau in the more advanced case, they underestimate the severity of MTL burden, potentially confounding assessments of tau‐targeted therapies.
Brain Imaging Biomarkers and Cognitive Outcomes in a Multidomain Lifestyle Intervention
Harrison, Theresa M., Harvey, Danielle J., Chadwick, Trevor, Chao, Yishu , Taggett, Jacinda , Maillard, Pauline, Lovato, Laura, Farias, Sarah, Papp, Kathryn V., Lockhart, Samuel N., Toga, Arthur W., Koeppe, Robert A., Jagust, William J., Whitmer, Rachel A., Snyder, Heather M. , Carrillo, Maria C., Baker, Laura D. , Espeland, Mark A., Vemuri, Prashanthi, DeCarli, Charles, Landau, Susan M., Harvey, Danielle , Carrillo, María C. , Harvey, Danielle J , Harrison, Theresa M. , Maillard, Pauline , Lovato, Laura, Farias, Sarah Tomaszewski , Papp, Kathryn V. , Lockhart, Samuel N. , Toga, Arthur W. , Koeppe, Robert A. , Jung, Youngkyoo , Jagust, William J. , Whitmer, Rachel A. , Espeland, Mark Andrew , Vemuri, Prashanthi , DeCarli, Charles , Landau, Susan

JAMA Neurology | April 20, 2026 | Volume: 83 | Issue: 6 | Pages: 521

10.1001/jamaneurol.2026.0832 Get It

Importance Brain imaging biomarkers may (1) identify underlying mechanisms of intervention effects and (2) define brain characteristics of those most likely to benefit cognitively from the intervention. Objective To test whether (1) a lifestyle intervention is related to brain changes, (2) brain changes are correlated with intervention-specific cognition changes, and (3) brain imaging biomarkers provide information about who is likely to benefit from a lifestyle intervention. Design, Setting, and Participants In this randomized clinical trial, the POINTER Imaging study was an ancillary study of the 2-year, single-blind multicenter US POINTER clinical trial in which neuroimaging data were collected on eligible enrolled participants. The study was conducted from May 2019 to March 2023 (final follow-up, May 14, 2025). Participants were enrolled into the POINTER Imaging study following a standard procedure at 5 clinical sites in the US. Participant eligibility criteria included an age of 60 to 79 years, sedentary lifestyle, and suboptimal diet, plus at least 2 additional risk criteria for cognitive decline and no contraindications for neuroimaging. Interventions Participants were randomly assigned to receive the structured or self-guided intervention. Both interventions emphasized increased physical and cognitive activity, healthy nutrition, social engagement, and cardiovascular health monitoring, but they differed in intensity and accountability. Main Outcomes and Measures There were 4 primary imaging outcomes: global β-amyloid (Aβ) burden, tau burden in the entorhinal cortex (ERC), hippocampal (HC) volume, and white matter hyperintensity volume. The primary cognitive measure was a global cognitive composite. Results Among 1943 parent trial participants who were assessed for eligibility, 983 underwent at least 1 magnetic resonance imaging or positron emission tomography scanning session. The mean (SD) age was 68.4 (5.2) years; 605 participants (61.5%) were female and 378 male (38.5%). Five hundred sixteen participants received the structured intervention and 467 the self-guided intervention. There were no intervention group differences in longitudinal cognitive or imaging outcomes. Intervention group differences were not associated with or moderated by Aβ status or accumulation. There was a negative association between change in ERC tau and change in global cognition in the self-guided group that was attenuated in the structured group (difference in association: 0.289; 95% CI, 0.029 to 0.550; interaction P = .03). Lower baseline HC volume was associated with greater cognitive benefit for participants in the structured group vs the self-guided group (lower HC: 0.077 SD; 95% CI, 0.022 to 0.132; higher HC: 0.002 SD; 95% CI, −0.037 to 0.041; interaction P = .03). Conclusion and Relevance This study found that a high-intensity multidomain lifestyle intervention did not affect brain biomarker trajectories and was not associated with Aβ pathology, but older adults with specific at-risk brain characteristics, including lower baseline HC volume, showed a greater cognitive benefit of the structured intervention. Trial Registration ClinicalTrials.gov Identifier: NCT03688126
Sex Differences in Longitudinal Tau-PET in Preclinical Alzheimer Disease
Coughlan, Gillian , Klinger, Hannah M , Boyle, Rory , Binette, Alexa Pichet , Christenson, Luke R., Chadwick, Trevor, Healy, Brian C. , Jonaitis, Erin M. , Jack, Clifford R. , Johnson, Keith A. , Langhough, Rebecca E., Properzi, Michael J , Seto, Mabel , Johnson, Sterling C., Shirzadi, Zahra , Yau, Wai‐Ying Wendy , Initiative, Alzheimer’s Disease Neuroimaging, Hurko, Orest, Black, Sanra E, Doody, Rachelle S., Doraiswamy, Murali, Gamst, Anthony, Scharre, Doug, Sperling, Reisa, Weiner, Michael W. , Green, Robert C, Christenson, Luke, Jack, Clifford R , Pichet Binette, Alexa , Betthauser, Tobey J. , Hansson, Oskar , Harrison, Theresa M. , Jacobs, Heidi I.L. , Hanseeuw, Bernard , Rentz, Dorene M. , Schultz, Aaron P. , Smith, Ruben , Johnson, Sterling C. , Mielke, Michelle M. , Manson, JoAnn E. , Sperling, Reisa Anne , Vemuri, Prashanthi , Buckley, Rachel F. , Initiative, Alzheimer’s Disease Neuroimaging, Black, Sanra E, Kaye, Jeffrey , Obisesan, Thomas O. , Rusinek, Henry

JAMA Neurology | March 3, 2025 | Volume: 82 | Issue: 4 | Pages: 364

10.1001/jamaneurol.2025.0013 Get It

Importance Alzheimer disease (AD) predominates in females at almost twice the rate relative to males. Mounting evidence in adults without AD indicates that females exhibit higher tau deposition than age-matched males, particularly in the setting of elevated β-amyloid (Aβ), but the evidence for sex differences in tau accumulation rates is inconclusive. Objective To examine whether female sex is associated with faster tau accumulation in the setting of high Aβ (as measured with positron emission tomography [PET]) and the moderating influence of sex on the association between APOE ε4 carrier status and tau accumulation. Data Sources This meta-analysis used data from 6 longitudinal aging and AD studies, including the Alzheimer’s Disease Neuroimaging Initiative, Berkeley Aging Cohort Study, BioFINDER 1, Harvard Aging Brain Study, Mayo Clinic Study of Aging, and Wisconsin Registry for Alzheimer Prevention. Longitudinal data were collected between November 2004 and May 2022. Study Selection Included studies required available longitudinal [ 18 F]flortaucipir or [ 18 F]-MK-6240 tau-PET scans, as well as baseline [ 11 C] Pittsburgh Compound B, [ 18 F]flutemetamol or [ 18 F]florbetapir Aβ-PET scans. Recruitment criteria varied across studies. Analyses began on August 7, 2023, and were completed on February 5, 2024. Data Extraction and Synthesis In each study, primary analyses extracted estimates for the sex (female or male) and the sex by baseline Aβ-PET status (high or low) association with longitudinal tau-PET using a series of mixed-effects models. Secondary mixed-effects models extracted the interaction estimate for the association of sex by APOE ε4 carrier status with longitudinal tau-PET. Study-specific estimates for each mixed-effects model were then pooled in a meta-analysis, and the global fixed effect (β) and total heterogeneity ( I 2 ) across studies were estimated. This study is reported following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. Main Outcomes and Measures Seven tau-PET outcomes that showed cross-sectional sex differences were examined across temporal, parietal, and occipital lobes. Results Among 6 studies assessed, there were 1376 participants (761 [55%] female; mean [range] age at first tau scan, 71.9 [46-93] years; 401 participants [29%] with high baseline Aβ; 412 APOE ε4 carriers [30%]). Among individuals with high baseline Aβ, female sex was associated with faster tau accumulation localized to inferior temporal (β = −0.14; 95% CI, −0.22 to −0.06; P = .009) temporal fusiform (β = −0.13; 95% CI, −0.23 to −0.04; P = .02), and lateral occipital regions (β = −0.15; 95% CI, −0.24 to −0.06; P = .009) compared with male sex. Among APOE ε4 carriers, female sex was associated with faster inferior-temporal tau accumulation (β = −0.10; 95% CI, −0.16 to −0.03; P = .01). Conclusions and Relevance These findings suggest that sex differences in the pathological progression of AD call for sex-specific timing considerations when administrating anti-Aβ and anti-tau treatments.
Positron emission tomography harmonization in the Alzheimer's Disease Neuroimaging Initiative: A scalable and rigorous approach to multisite amyloid and tau quantification
Landau, Susan, Baker, Suzanne L. , Boswell, Martin S., Lee, JiaQie, Taggett, Jacinda , Ward, Tyler J. , Chadwick, Trevor, Murphy, Alice, DeCarli, Charles, Jack, Clifford R. , Jagust, William J. , Initiative, for the U.S. POINTER Study Group and for the Alzheimer's Disease Neuroimaging, DeCarli, Charles , DeCarli, Charles , Jack, Clifford R , Harrison, Theresa M. , Schwarz, Christopher G. , Vemuri, Prashanthi , Koeppe, Robert A. , Initiative, for the U.S. POINTER Study Group and for the Alzheimer's Disease Neuroimaging

Alzheimer's & Dementia | November 19, 2024 | Volume: 21 | Issue: 1 | Pages: No page available

10.1002/alz.14378 Get It

Abstract INTRODUCTION A key goal of the Alzheimer's Disease NeuroImaging Initiative (ADNI) positron emission tomography (PET) Core is to harmonize quantification of β‐amyloid (Aβ) and tau PET image data across multiple scanners and tracers. METHODS We developed an analysis pipeline (Berkeley PET Imaging Pipeline, B‐PIP) for ADNI Aβ and tau PET images and applied it to PET data from other multisite studies. Steps include image pre‐processing, refacing, magnetic resonance imaging (MRI)/PET co‐registration, visual quality control (QC), quantification of tracer uptake, and standardization of Aβ and tau standardized uptake value ratios (SUVrs) across tracers. RESULTS Measurements from 10,105 cross‐sectional and longitudinal Aβ and tau PET scans acquired in several studies between 2010 and 2024 can be processed, harmonized, and directly merged across tracers and cohorts. DISCUSSION The B‐PIP developed in ADNI is a scalable image harmonization approach used in several observational studies and clinical trials that facilitates rigorous Aβ and tau PET quantification and data sharing. Highlights Quantitative results from ADNI Aβ and tau PET data are generated using a rigorous, scalable image processing pipeline This pipeline has been applied to PET data from several other large, multisite studies and trials Quantitative outcomes are harmonizable across studies and are shared with the scientific community
Harmonization of amyloid and tau PET tracers in a multi‐center cohort from NIA Alzheimer’s disease research centers in the United States
Landau, Susan , Baker, Suzanne L. , Lee, JiaQie, Ward, Tyler J. , Murphy, Alice, Chadwick, Trevor, Mormino, Elizabeth C. , Rogalskı, Emily , DeCarli, Charles, Biber, Sarah , Jagust, William J. , Harrison, Theresa M. , Johnson, Sterling C. , Koeppe, Robert A. , Toga, Arthur W. , Kukull, Walter A. , Jack, Clifford R.

Alzheimer's & Dementia | December 25, 2023 | Volume: 19 | Issue: S16 | Pages: No page available

10.1002/alz.079015 Get It

AbstractBackgroundThe Standardized Centralized Alzheimer’s & related dementias Neuroimaging (SCAN) project harmonizes processing of prospectively acquired PET and MRI scans from Alzheimer’s disease research centers (ADRCs) across the USA. SCAN data will be integrated with other ADRC data streams within the National Alzheimer’s Coordinating Center (NACC), including the Uniform Data Set which includes rich longitudinal demographic, cognitive, and neuropathological data, resulting in a large, potentially representative cohort. The project has sought to accommodate site‐to‐site variation in image acquisition while permitting harmonization of imaging data, necessitating new analytic approaches for different PET tracers and PET scans without MRIs.MethodPET scans underwent preprocessing for quality control and smoothing to a uniform resolution. MRI‐free processing pipelines and positivity thresholds were developed for each beta‐amyloid (Aβ)‐PET tracer: [11C]PiB, [18F]florbetaben (FBB), [18F]florbetapir (FBP) and [18F]flutafuranol (NAV). A generic Aβ‐PET template was used for spatial normalization and cortical summary SUVRs were calculated in template space. Aβ‐positivity thresholds were determined by examining both MRI‐dependent thresholds transformed into MRI‐free units and a young control mean+2SD. Centiloid (CL) conversions were completed for each Aβ‐PET tracer. Tau‐PET tracers ([18F]flortaucipir (FTP) and [18F]MK‐6240) required tracer‐specific warping templates for best performance relative to gold‐standard MRI‐dependent processing. Demographic and clinical data were obtained from NACC.Result15 ADRCs have contributed data to SCAN as of January 2023. 477 participants had preprocessed, SCAN‐compliant (https://scan.naccdata.org/) Aβ‐PET scans and NACC data; 219 of these participants (46%) also had tau‐PET scans (Table 1). This cohort included 18% of individuals from underrepresented groups. Clinical diagnostic groups ranged from cognitively unimpaired to MCI and dementia (74% of whom had AD dementia). Using pooled Aβ‐PET data across 4 tracers in CLs, there were expected differences in Aβ burden by diagnosis group (Fig. 1) and positive associations with tau (Fig. 2).ConclusionSCAN has successfully harmonized PET data from more than a dozen US ADRCs yielding a large, clinically heterogeneous cohort of deeply phenotyped research participants. SCAN data will be compatible with ADNI data allowing for further pooling of data and greater statistical power to drive critical questions in AD and related dementias research.
Harmonization of amyloid and tau PET tracers in a multi‐center cohort from NIA Alzheimer’s disease research centers in the United States
Landau, Susan , Baker, Suzanne L. , Lee, JiaQie, Murphy, Alice, Chadwick, Trevor, Mormino, Elizabeth C. , Rogalskı, Emily , Biber, Sarah , Jagust, William J. , Harrison, Theresa M. , Ward, Tyler J. , Johnson, Sterling C. , Koeppe, Robert A. , DeCarli, Charles , Toga, Arthur W. , Kukull, Walter A. , Jack, Clifford R.

Alzheimer's & Dementia | December 25, 2023 | Volume: 19 | Issue: S10 | Pages: No page available

10.1002/alz.081867 Get It

AbstractBackgroundThe Standardized Centralized Alzheimer’s & related dementias Neuroimaging (SCAN) project harmonizes processing of prospectively acquired PET and MRI scans from Alzheimer’s disease research centers (ADRCs) across the USA. SCAN data will be integrated with other ADRC data streams within the National Alzheimer’s Coordinating Center (NACC), including the Uniform Data Set which includes rich longitudinal demographic, cognitive, and neuropathological data, resulting in a large, potentially representative cohort. The project has sought to accommodate site‐to‐site variation in image acquisition while permitting harmonization of imaging data, necessitating new analytic approaches for different PET tracers and PET scans without MRIs.MethodPET scans underwent preprocessing for quality control and smoothing to a uniform resolution. MRI‐free processing pipelines and positivity thresholds were developed for each beta‐amyloid (Aß)‐PET tracer: [11C]PiB, [18F]florbetaben (FBB), [18F]florbetapir (FBP) and [18F]flutafuranol (NAV). A generic Aß‐PET template was used for spatial normalization and cortical summary SUVRs were calculated in template space. Aß‐positivity thresholds were determined by examining both MRI‐dependent thresholds transformed into MRI‐free units and a young control mean+2SD. Centiloid (CL) conversions were completed for each Aß‐PET tracer. Tau‐PET tracers ([18F]flortaucipir (FTP) and [18F]MK‐6240) required tracer‐specific warping templates for best performance relative to gold‐standard MRI‐dependent processing. Demographic and clinical data were obtained from NACC.Result15 ADRCs have contributed data to SCAN as of January 2023. 477 participants had preprocessed, SCAN‐compliant (https://scan.naccdata.org/) Aß‐PET scans and NACC data; 219 of these participants (46%) also had tau‐PET scans (Table 1). This cohort included 18% of individuals from underrepresented groups. Clinical diagnostic groups ranged from cognitively unimpaired to MCI and dementia (74% of whom had AD dementia). Using pooled Aß‐PET data across 4 tracers in CLs, there were expected differences in Aß burden by diagnosis group (Fig. 1) and positive associations with tau (Fig. 2).ConclusionSCAN has successfully harmonized PET data from more than a dozen US ADRCs yielding a large, clinically heterogeneous cohort of deeply phenotyped research participants. SCAN data will be compatible with ADNI data allowing for further pooling of data and greater statistical power to drive critical questions in AD and related dementias research.