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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; Aisen, Paul S; Ashford, Miriam A; Beckett, Laurel A; Green, Robert C; Harvey, Danielle; Jack, Clifford R; Jagust, William; Landau, Susan M; Morris, John C; Nho, Kwangsik T; Nosheny, Rachel; Okonkwo, Ozioma; Perrin, Richard J; Petersen, Ronald C; Rivera Mindt, Monica; Saykin, Andrew; Shaw, Leslie M; Toga, Arthur W; Tosun, Duygu.
Afiliação
  • Veitch DP; Department of Veterans Affairs Medical Center, Northern California Institute for Research and Education (NCIRE), San Francisco, California, USA.
  • Weiner MW; Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, California, USA.
  • Miller M; Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, California, USA.
  • Aisen PS; Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA.
  • Ashford MA; Department of Medicine, University of California, San Francisco, California, USA.
  • Beckett LA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, California, USA.
  • Green RC; Department of Neurology, University of California, San Francisco, California, USA.
  • Harvey D; Department of Veterans Affairs Medical Center, Northern California Institute for Research and Education (NCIRE), San Francisco, California, USA.
  • Jack CR; Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, California, USA.
  • Jagust W; Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, California, USA.
  • Landau SM; Department of Veterans Affairs Medical Center, Northern California Institute for Research and Education (NCIRE), San Francisco, California, USA.
  • Morris JC; Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, California, USA.
  • Nho KT; Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Broad Institute Ariadne Labs and Harvard Medical School, Boston, Massachusetts, USA.
  • Nosheny R; Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, California, USA.
  • Okonkwo O; Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA.
  • Perrin RJ; Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California, USA.
  • Petersen RC; Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California, USA.
  • Rivera Mindt M; Knight Alzheimer's Disease Research Center, Washington University School of Medicine, Saint Louis, Missouri, USA.
  • Saykin A; Department of Neurology, Washington University School of Medicine, Saint Louis, Missouri, USA.
  • Shaw LM; Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, Missouri, USA.
  • Toga AW; Department of Radiology and Imaging Sciences and the Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA.
  • Tosun D; Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Alzheimers Dement ; 20(1): 652-694, 2024 Jan.
Article em En | MEDLINE | ID: mdl-37698424
ABSTRACT
The 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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doença de Alzheimer / Disfunção Cognitiva Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Alzheimers Dement Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doença de Alzheimer / Disfunção Cognitiva Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Alzheimers Dement Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos