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Saykin, Andrew J

0000-0002-1376-8532

Mayo Clinic

No affiliation available

Citations 45

Overview of Alzheimer's Disease Neuroimaging Initiative and future clinical trials
Weiner, Michael W. , Kanoria, Shaveta , Miller, Melanie J. , Aisen, Paul , Conti, Catherine , Diaz, Adam , Flenniken, Derek , Harvey, Danielle , Jack, Clifford R. , Jagust, William J. , Morris, John C. , Nosheny, Rachel L. , Okonkwo, Ozioma C. , Perrin, Richard J. , Petersen, Ronald C. , Saykin, Andrew J. , Shaw, Leslie M. , Tosun, Duygu , Initiative, for the Alzheimer's Disease Neuroimaging, Jack, Clifford R , Saykin, Andrew J , Morris, John C , Harvey, Danielle J , Tosun, Duygu , Weiner, Michael W , Beckett, Laurel , Green, Robert C. , Lee, Edward B. , Nho, Kwangsik T. , Mindt, Mónica Rivera , Toga, Arthur W. , Veitch, Dallas P. , Initiative, for the Alzheimer's Disease Neuroimaging

Alzheimer's & Dementia | December 23, 2024 | Volume: 21 | Issue: 1 | Pages: No page available

10.1002/alz.14321 Get It

Abstract The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to optimize and validate biomarkers for clinical trials while sharing all data and biofluid samples with the global scientific community. ADNI has been instrumental in standardizing and validating amyloid beta (Aβ) and tau positron emission tomography (PET) imaging. ADNI data were used for the US Food and Drug Administration (FDA) approval of the Fujirebio and Roche Elecsys cerebrospinal fluid diagnostic tests. Additionally, ADNI provided data for the trials of the FDA‐approved treatments aducanumab, lecanemab, and donanemab. More than 6000 scientific papers have been published using ADNI data, reflecting ADNI's promotion of open science and data sharing. Despite its enormous success, ADNI has some limitations, particularly in generalizing its data and findings to the entire US/Canadian population. This introduction provides a historical overview of ADNI and highlights its significant accomplishments and future vision to pioneer “the clinical trial of the future” focusing on demographic inclusivity. Highlights The Alzheimer's Disease Neuroimaging Initiative (ADNI) introduced a novel model for public‐private partnerships and data sharing. It successfully validated amyloid and Tau PET imaging, as well as CSF and plasma biomarkers, for diagnosing Alzheimer's disease. ADNI generated and disseminated vital data for designing AD clinical trials.
Presenilin‐1 mutation position influences amyloidosis, small vessel disease, and dementia with disease stage
Joseph‐Mathurin, Nelly , Feldman, Rebecca L. , Lu, Ruijin , Shirzadi, Zahra , Toomer, Carmen, Clair, Junie R. Saint, Ma, Yinjiao , Strain, Jeremy F. , Kilgore, Collin , Chen, Charles D., Gordon, Brian A. , Chen, Gengsheng , Hornbeck, Russ C. , Massoumzadeh, Parinaz , Wang, Qing , Li, Yan , Wang, Guoqiao , Keefe, Sarah , Schultz, Stephanie A. , Preboske, Gregory M., Jack, Clifford R. , Ances, Beau M. , Berman, Sarah , Day, Gregory S. , Fox, Nick C. , Fulham, Michael , Ghetti, Bernardino , Johnson, Keith A. , Xiong, Chengjie , Oh, Hwamee , Perrin, Richard J. , Ringman, John M. , Saykin, Andrew J. , Supnet, Charlene , Vöglein, Jonathan , Yakushev, Igor , Morris, John C. , Chhatwal, Jasmeer P. , Network, for the Dominantly Inherited Alzheimer, Jack, Clifford R , Gordon, Brian A , Saykin, Andrew J , Day, Gregory S , Vöglein, Jonathan , Joseph-Mathurin, Nelly , Xiong, Chengjie , Chen, Charles D , Ances, Beau M , Fox, Nick C , Morris, John C , Ghetti, Bernardino F , Supnet-Bell, Charlene , Berman, Sarah , Clair, Junie Saint, McKay, Nicole S. , Friedrichsen, Karl A. , McCullough, Austin , Li, Yan, Cruchaga, Carlos , Llibre‐Guerra, Jorge J. , Allegri, Ricardo , Brooks, William S. , Cash, David M. , Jucker, Mathias , Klunk, William E. , Fougère, Christian la , Niimi, Yoshiki , Reischl, Gerald , Schofield, Peter R. , Su, Yi , Brickman, Adam M. , McDade, Eric , Xiong, Chengjie , Bateman, Randall J. , Benzinger, Tammie L.S. , Network, for the Dominantly Inherited Alzheimer

Alzheimer's & Dementia | February 21, 2024 | Volume: 20 | Issue: 4 | Pages: 2680-2697

10.1002/alz.13729 Get It

AbstractINTRODUCTIONAmyloidosis, including cerebral amyloid angiopathy, and markers of small vessel disease (SVD) vary across dominantly inherited Alzheimer's disease (DIAD) presenilin‐1 (PSEN1) mutation carriers. We investigated how mutation position relative to codon 200 (pre‐/postcodon 200) influences these pathologic features and dementia at different stages.METHODSIndividuals from families with known PSEN1 mutations (n = 393) underwent neuroimaging and clinical assessments. We cross‐sectionally evaluated regional Pittsburgh compound B‐positron emission tomography uptake, magnetic resonance imaging markers of SVD (diffusion tensor imaging‐based white matter injury, white matter hyperintensity volumes, and microhemorrhages), and cognition.RESULTSPostcodon 200 carriers had lower amyloid burden in all regions but worse markers of SVD and worse Clinical Dementia Rating® scores compared to precodon 200 carriers as a function of estimated years to symptom onset. Markers of SVD partially mediated the mutation position effects on clinical measures.DISCUSSIONWe demonstrated the genotypic variability behind spatiotemporal amyloidosis, SVD, and clinical presentation in DIAD, which may inform patient prognosis and clinical trials.Highlights Mutation position influences Aβ burden, SVD, and dementia. PSEN1 pre‐200 group had stronger associations between Aβ burden and disease stage. PSEN1 post‐200 group had stronger associations between SVD markers and disease stage. PSEN1 post‐200 group had worse dementia score than pre‐200 in late disease stage. Diffusion tensor imaging‐based SVD markers mediated mutation position effects on dementia in the late stage.
The Alzheimer's Disease Neuroimaging Initiative in the era of Alzheimer's disease treatment: A review of ADNI studies from 2021 to 2022
Veitch, Dallas P. , Weiner, Michael W. , Miller, Melanie J. , Aisen, Paul, Ashford, Miriam A., Harvey, Danielle , Jack, Clifford R. , Jagust, William J. , Landau, Susan, Morris, John C. , Nosheny, Rachel L. , Okonkwo, Ozioma C. , Perrin, Richard J. , Petersen, Ronald C. , Saykin, Andrew J. , Shaw, Leslie M. , Tosun, Duygu , Initiative, for the Alzheimer's Disease Neuroimaging, Jack, Clifford R , Saykin, Andrew J , Morris, John C , Harvey, Danielle J , Tosun, Duygu , Ashford, Miriam T. , Beckett, Laurel , Green, Robert C. , Nho, Kwangsik T. , Mindt, Mónica Rivera , Toga, Arthur W. , Initiative, for the Alzheimer's Disease Neuroimaging

Alzheimer's & Dementia | September 12, 2023 | Volume: 20 | Issue: 1 | Pages: 652-694

10.1002/alz.13449 Get It

AbstractThe Alzheimer's Disease Neuroimaging Initiative (ADNI) aims to improve Alzheimer's disease (AD) clinical trials. Since 2006, ADNI has shared clinical, neuroimaging, and cognitive data, and biofluid samples. We used conventional search methods to identify 1459 publications from 2021 to 2022 using ADNI data/samples and reviewed 291 impactful studies. This review details how ADNI studies improved disease progression understanding and clinical trial efficiency. Advances in subject selection, detection of treatment effects, harmonization, and modeling improved clinical trials and plasma biomarkers like phosphorylated tau showed promise for clinical use. Biomarkers of amyloid beta, tau, neurodegeneration, inflammation, and others were prognostic with individualized prediction algorithms available online. Studies supported the amyloid cascade, emphasized the importance of neuroinflammation, and detailed widespread heterogeneity in disease, linked to genetic and vascular risk, co‐pathologies, sex, and resilience. Biological subtypes were consistently observed. Generalizability of ADNI results is limited by lack of cohort diversity, an issue ADNI‐4 aims to address by enrolling a diverse cohort.
Increasing participant diversity in AD research: Plans for digital screening, blood testing, and a community‐engaged approach in the Alzheimer's Disease Neuroimaging Initiative 4
Weiner, Michael W. , Veitch, Dallas P. , Miller, Melanie J. , Aisen, Paul, Albala, Bruce, Harvey, Danielle , Jagust, William J. , Landau, Susan , Morris, John C. , Nosheny, Rachel L. , Okonkwo, Ozioma C. , Perrin, Richard J. , Petersen, Ronald C. , Saykin, Andrew J. , Shaw, Leslie M. , Tosun, Duygu , Trojanowski, John Q. , Initiative, Alzheimer's Disease Neuroimaging, Tosun, Duygu , Saykin, Andrew J , Morris, John C , Harvey, Danielle J , Tosun, Duygu , Beckett, Laurel , Green, Robert C. , Jack, Clifford R. , Mindt, Mónica Rivera , Toga, Arthur W. , Initiative, Alzheimer's Disease Neuroimaging

Alzheimer's & Dementia | October 9, 2022 | Volume: 19 | Issue: 1 | Pages: 307-317

10.1002/alz.12797 Get It

AbstractIntroductionThe Alzheimer's Disease Neuroimaging Initiative (ADNI) aims to validate biomarkers for Alzheimer's disease (AD) clinical trials. To improve generalizability, ADNI4 aims to enroll 50‐60% of its new participants from underrepresented populations (URPs) using new biofluid and digital technologies. ADNI4 has received funding from the National Institute on Aging beginning September 2022.MethodsADNI4 will recruit URPs using community‐engaged approaches. An online portal will screen 20,000 participants, 4000 of whom (50‐60% URPs) will be tested for plasma biomarkers and APOE. From this, 500 new participants will undergo in‐clinic assessment joining 500 ADNI3 rollover participants. Remaining participants (∼3500) will undergo longitudinal plasma and digital cognitive testing. ADNI4 will add MRI sequences and new PET tracers. Project 1 will optimize biomarkers in AD clinical trials.Results and DiscussionADNI4 will improve generalizability of results, use remote digital and blood screening, and continue providing longitudinal clinical, biomarker, and autopsy data to investigators.
Traumatic brain injury and post‐traumatic stress disorder are not associated with Alzheimer's disease pathology measured with biomarkers
Weiner, Michael W. , Harvey, Danielle , Landau, Susan, Veitch, Dallas P. , Aisen, Paul, Petersen, Ronald C. , Tosun, Duygu , Shaw, Leslie M. , Trojanowski, John Q. , Saykin, Andrew J. , Carli, Charles De, DeCarli, Charles , Tosun, Duygu , DeCarli, Charles , Saykin, Andrew J , Harvey, Danielle J , Tosun, Duygu , Neylan, Thomas C. , Grafman, Jordan Henry , Jack, Clifford R. , Hayes, Jacqueline

Alzheimer's & Dementia | June 29, 2022 | Volume: 19 | Issue: 3 | Pages: 884-895

10.1002/alz.12712 Get It

AbstractIntroductionEpidemiological studies report an association between traumatic brain injury (TBI) and post‐traumatic stress disorder (PTSD) and clinically diagnosed Alzheimer's disease (AD). We examined the association between TBI/PTSD and biomarker‐defined AD.MethodsWe identified 289 non‐demented veterans with TBI and/or PTSD and controls who underwent clinical evaluation, cerebrospinal fluid (CSF) collection, magnetic resonance imaging (MRI), amyloid beta (Aβ) and tau positron emission tomography, and apolipoprotein E testing. Participants were followed for up to 5.2 years.ResultsExposure groups (TBI, PTSD, and TBI + PTSD) had higher prevalence of mild cognitive impairment (MCI: P < .0001) and worse Mini‐Mental State Examination scores (PTSD: P = .008; TBI & PTSD: P = .009) than controls. There were no significant differences in other cognitive scores, MRI volumes, Aβ or tau accumulation, or in most longitudinal measures.DiscussionTBI and/or PTSD were not associated with elevated AD biomarkers. The poorer cognitive status of exposed veterans may be due to other comorbid pathologies.
Autosomal dominant and sporadic late onset Alzheimer's disease share a commonin vivopathophysiology
Schofield, Peter R. , Weiner, Michael W. , Xiong, Chengjie , Coble, Dean W. , Saito, Naomi , Aisen, Paul, Berman, Sarah , Cairns, Nigel J., Carrillo, María C. , Chui, Helena C., Chhatwal, Jasmeer P. , Fagan, Anne M. , Farlow, Martin R. , Fox, Nick C. , Goate, Alison , Gordon, Brian A. , Graff‐Radford, Neill R. , Day, Gregory S. , Hassenstab, Jason , Jack, Clifford R. , Jagust, William J. , Massoumzadeh, Parinaz , Masters, Colin L. , Mori, Hiroshi , Noble, James M. , Petersen, Ronald C. , Ringman, John M. , Salloway, Stephen , Saykin, Andrew J. , Shaw, Leslie M. , Trojanowski, John Q. , Vöglein, Jonathan , Weninger, Stacie, Bateman, Randall J. , Buckles, Virginia, Morris, John C. , Schofield, Peter R , Gordon, Brian A , Ikeuchi, T , Jack, Clifford R , Jagust, William J , Masters, Colin L , Vöglein, Jonathan , Saykin, Andrew J , Day, Gregory S , Bateman, Randall J , Xiong, Chengjie , Fox, Nick C , Hassenstab, Jason , Morris, John C , Goate, Alison M , Berman, Sarah , Noble, James M , Xiong, Chengjie , Beckett, Laurel , Allegri, Ricardo , Benzinger, Tammie L.S. , Chui, Helena C. , Cruchaga, Carlos , Ghetti, Bernardino , Ikeuchi, Takeshi , Jucker, Mathias , Martins, Ralph N. , McDade, Eric , Toga, Arthur W.

Brain | May 17, 2022 | Volume: 145 | Issue: 10 | Pages: 3594-3607

10.1093/brain/awac181 Get It

AbstractThe extent to which the pathophysiology of autosomal dominant Alzheimer's disease corresponds to the pathophysiology of ‘sporadic’ late onset Alzheimer's disease is unknown, thus limiting the extrapolation of study findings and clinical trial results in autosomal dominant Alzheimer's disease to late onset Alzheimer's disease.We compared brain MRI and amyloid PET data, as well as CSF concentrations of amyloid-β42, amyloid-β40, tau and tau phosphorylated at position 181, in 292 carriers of pathogenic variants for Alzheimer's disease from the Dominantly Inherited Alzheimer Network, with corresponding data from 559 participants from the Alzheimer’s Disease Neuroimaging Initiative. Imaging data and CSF samples were reprocessed as appropriate to guarantee uniform pipelines and assays. Data analyses yielded rates of change before and after symptomatic onset of Alzheimer's disease, allowing the alignment of the ∼30-year age difference between the cohorts on a clinically meaningful anchor point, namely the participant age at symptomatic onset.Biomarker profiles were similar for both autosomal dominant Alzheimer's disease and late onset Alzheimer's disease. Both groups demonstrated accelerated rates of decline in cognitive performance and in regional brain volume loss after symptomatic onset. Although amyloid burden accumulation as determined by PET was greater after symptomatic onset in autosomal dominant Alzheimer's disease than in late onset Alzheimer's disease participants, CSF assays of amyloid-β42, amyloid-β40, tau and p-tau181 were largely overlapping in both groups. Rates of change in cognitive performance and hippocampal volume loss after symptomatic onset were more aggressive for autosomal dominant Alzheimer's disease participants.These findings suggest a similar pathophysiology of autosomal dominant Alzheimer's disease and late onset Alzheimer's disease, supporting a shared pathobiological construct.
Predictive metabolic networks reveal sex‐ and APOE genotype‐specific metabolic signatures and drivers for precision medicine in Alzheimer's disease
Chang, Rui , Trushina, Eugenia , Zhu, Kuixi , Zaidi, Syed Shujaat Ali , Lau, Branden M, Moein, Sara, He, Qianying, Alamprese, Melissa , Vagnerova, Barbora, Tang, Andrew, Vijayan, Ramachandran , Liu, Yan‐Yun , Saykin, Andrew J. , Young‐Pearse, Tracy L. , Saykin, Andrew J , Trushina, Eugenia , Kueider‐Paisley, Alexandra , Tang, Andrew, Vijayan, Ramachandran, Brinton, Roberta Dı́az , Kaddurah‐Daouk, Rima

Alzheimer's & Dementia | April 28, 2022 | Volume: 19 | Issue: 2 | Pages: 518-531

10.1002/alz.12675 Get It

Abstract Introduction Late‐onset Alzheimer's disease (LOAD) is a complex neurodegenerative disease characterized by multiple progressive stages, glucose metabolic dysregulation, Alzheimer's disease (AD) pathology, and inexorable cognitive decline. Discovery of metabolic profiles unique to sex, apolipoprotein E ( APOE ) genotype, and stage of disease progression could provide critical insights for personalized LOAD medicine. Methods Sex‐ and APOE ‐specific metabolic networks were constructed based on changes in 127 metabolites of 656 serum samples from the Alzheimer's Disease Neuroimaging Initiative cohort. Results Application of an advanced analytical platform identified metabolic drivers and signatures clustered with sex and/or APOE ɛ4, establishing patient‐specific biomarkers predictive of disease state that significantly associated with cognitive function. Presence of the APOE ɛ4 shifts metabolic signatures to a phosphatidylcholine‐focused profile overriding sex‐specific differences in serum metabolites of AD patients. Discussion These findings provide an initial but critical step in developing a diagnostic platform for personalized medicine by integrating metabolomic profiling and cognitive assessments to identify targeted precision therapeutics for AD patient subgroups through computational network modeling.
The Worldwide Alzheimer's Disease Neuroimaging Initiative: ADNI‐3 updates and global perspectives
Weber, Christopher J., Carrillo, María C. , Jagust, William J. , Shaw, Leslie M. , Trojanowski, John Q. , Saykin, Andrew J. , Sur, Cyrille, Méndez, Patricio Chrem, Li, Kuncheng , Iwatsubo, Takeshi , Perrin, Richard J. , Morris, John C. , Healan, Amanda M.B., Weiner, Michael W. , Saykin, Andrew J , Morris, John C , Jack, Clifford R. , Beckett, Laurel , Rao, Naren Prahalada , Black, Sandra E. , Chang, Chiung‐Chih , Sosa, Ana Luisa , Rowe, Christopher Cleon , Hall, Stephen E.

Alzheimer's & Dementia: Translational Research & Clinical Interventions | December 31, 2021 | Volume: 7 | Issue: 1 | Pages: No page available

10.1002/trc2.12226 Get It

Abstract The Worldwide Alzheimer's Disease Neuroimaging Initiative (WW‐ADNI) is a collaborative effort to investigate imaging and biofluid markers that can inform Alzheimer's disease treatment trials. It is a public‐private partnership that spans North America, Argentina, Australia, Canada, China, Japan, Korea, Mexico, and Taiwan. In 2004, ADNI researchers began a naturalistic, longitudinal study that continues today around the globe. Through several successive phases (ADNI‐1, ADNI‐GO, ADNI‐2, and ADNI‐3), the study has fueled amyloid and tau phenotyping and refined neuroimaging methodologies. WW‐ADNI researchers have successfully standardized analyses and openly share data without embargo, providing a rich data set for other investigators. On August 26, 2020, the Alzheimer's Association convened WW‐ADNI researchers who shared updates from ADNI‐3 and their vision for ADNI‐4.
Contribution of Alzheimer's biomarkers and risk factors to cognitive impairment and decline across the Alzheimer's disease continuum
Tosun, Duygu , Demir, Zeynep , Aisen, Paul, Jack, Clifford R. , Jagust, William, Petersen, Ronald C. , Saykin, Andrew J. , Shaw, Leslie M. , Trojanowski, John Q. , Weiner, Michael W. , Initiative, for the Alzheimer's Disease Neuroimaging, Jack, Clifford R , Saykin, Andrew J , Tosun, Duygu , Veitch, Dallas P. , Weintraub, Daniel , Initiative, for the Alzheimer's Disease Neuroimaging

Alzheimer's & Dementia | October 19, 2021 | Volume: 18 | Issue: 7 | Pages: 1370-1382

10.1002/alz.12480 Get It

Abstract Introduction Amyloid beta (Aβ), tau, and neurodegeneration jointly with the Alzheimer's disease (AD) risk factors affect the severity of clinical symptoms and disease progression. Methods Within 248 Aβ‐positive elderly with and without cognitive impairment and dementia, partial least squares structural equation pathway modeling was used to assess the direct and indirect effects of imaging biomarkers (global Aβ‐positron emission tomography [PET] uptake, regional tau‐PET uptake, and regional magnetic resonance imaging–based atrophy) and risk‐factors (age, sex, education, apolipoprotein E [ APOE ], and white‐matter lesions) on cross‐sectional cognitive impairment and longitudinal cognitive decline. Results Sixteen percent of variance in cross‐sectional cognitive impairment was accounted for by Aβ, 46% to 47% by tau, and 25% to 29% by atrophy, although 53% to 58% of total variance in cognitive impairment was explained by incorporating mediated and direct effects of AD risk factors. The Aβ–tau–atrophy pathway accounted for 50% to 56% of variance in longitudinal cognitive decline while Aβ, tau, and atrophy independently explained 16%, 46% to 47%, and 25% to 29% of the variance, respectively. Discussion These findings emphasize that treatments that remove Aβ and completely stop downstream effects on tau and neurodegeneration would only be partially effective in slowing of cognitive decline or reversing cognitive impairment.
Using the Alzheimer's Disease Neuroimaging Initiative to improve early detection, diagnosis, and treatment of Alzheimer's disease
Weiner, Michael W. , Aisen, Paul, DeCarli, Charles , Harvey, Danielle , Jack, Clifford R. , Jagust, William J. , Landau, Susan, Morris, John C. , Okonkwo, Ozioma C. , Perrin, Richard J. , Petersen, Ronald C. , Mindt, Mónica Rivera , Saykin, Andrew J. , Shaw, Leslie M. , Tosun, Duygu , Trojanowski, John Q. , Initiative, Alzheimer's Disease Neuroimaging, DeCarli, Charles , Jack, Clifford R , Saykin, Andrew J , Morris, John C , Harvey, Danielle J , Tosun, Duygu , Veitch, Dallas P. , Beckett, Laurel , Green, Robert C. , Toga, Arthur W. , Initiative, Alzheimer's Disease Neuroimaging

Alzheimer's & Dementia | September 28, 2021 | Volume: 18 | Issue: 4 | Pages: 824-857

10.1002/alz.12422 Get It

AbstractIntroductionThe Alzheimer's Disease Neuroimaging Initiative (ADNI) has accumulated 15 years of clinical, neuroimaging, cognitive, biofluid biomarker and genetic data, and biofluid samples available to researchers, resulting in more than 3500 publications. This review covers studies from 2018 to 2020.MethodsWe identified 1442 publications using ADNI data by conventional search methods and selected impactful studies for inclusion.ResultsDisease progression studies supported pivotal roles for regional amyloid beta (Aβ) and tau deposition, and identified underlying genetic contributions to Alzheimer's disease (AD). Vascular disease, immune response, inflammation, resilience, and sex modulated disease course. Biologically coherent subgroups were identified at all clinical stages. Practical algorithms and methodological changes improved determination of Aβ status. Plasma Aβ, phosphorylated tau181, and neurofilament light were promising noninvasive biomarkers. Prognostic and diagnostic models were externally validated in ADNI but studies are limited by lack of ethnocultural cohort diversity.DiscussionADNI has had a profound impact in improving clinical trials for AD.