Literature DB >> 26836176

Application of the IWG-2 Diagnostic Criteria for Alzheimer's Disease to the ADNI.

Hui-Fu Wang1, Lan Tan1,2, Lei Cao1, Xi-Chen Zhu1, Teng Jiang3, Meng-Shan Tan2, Ying Liu2, Chong Wang2, Richard M Tsai4, Jian-Ping Jia5, Jin-Tai Yu1,2,4.   

Abstract

BACKGROUND: The International Working Group (IWG) recently proposed the revised diagnostic criteria for Alzheimer's disease (AD) to define and refine several types of AD, and to reclassify AD-related biomarkers into diagnostic and progression markers, but its performance is not known.
OBJECTIVE: This study was designed to describe the application of the revised IWG criteria in the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, and to ascertain whether diagnostic and progression markers show significant differences in their relationships to AD severity and progression.
METHODS: Based on the requirements of the refined criteria, 857 ADNI subjects with memory evaluation and at least one pathophysiological marker (CSF or amyloid imaging biomarkers) were eligible and reclassified in this study, and we calculated the associations of diagnostic (CSF and amyloid PET) and progression markers (MRI and fluorodeoxyglucose-PET) with AD severity and progression respectively.
RESULTS: The majority (84.2% ) of ADNI AD group (n = 117) and 173 MCI (37.4% ) subjects in ADNI met the definition of typical AD; and 105 cognitively normal (41.0% ) individuals were diagnosed as asymptomatic AD. Furthermore, diagnostic and progression markers showed significant differences when correlated to AD severity and progression.
CONCLUSION: A large proportion of AD dementia subjects were categorized as typical AD, and the revised criteria could identify typical AD from MCI status as well as asymptomatic AD at the asymptomatic stage. Moreover, the significant differences between diagnostic and progression markers further supported the new biomarkers categorization in the refined criteria.

Entities:  

Keywords:  Alzheimer’s disease; Alzheimer’s disease neuroimaging Initiative; diagnostic markers; international working group-2 criteria; progression markers

Mesh:

Substances:

Year:  2016        PMID: 26836176     DOI: 10.3233/JAD-150824

Source DB:  PubMed          Journal:  J Alzheimers Dis        ISSN: 1387-2877            Impact factor:   4.472


  6 in total

1.  Clinical and biomarker trajectories in sporadic Alzheimer's disease: A longitudinal study.

Authors:  Hui-Fu Wang; Xue-Ning Shen; Jie-Qiong Li; John Suckling; Chen-Chen Tan; Yan-Jiang Wang; Lei Feng; Can Zhang; Lan Tan; Qiang Dong; Jacques Touchon; Serge Gauthier; Jin-Tai Yu
Journal:  Alzheimers Dement (Amst)       Date:  2020-08-12

Review 2.  PET Imaging in Animal Models of Alzheimer's Disease.

Authors:  Baosheng Chen; Bernadette Marquez-Nostra; Erika Belitzky; Takuya Toyonaga; Jie Tong; Yiyun Huang; Zhengxin Cai
Journal:  Front Neurosci       Date:  2022-05-24       Impact factor: 5.152

3.  Prevalence of preclinical Alzheimer disease: Comparison of current classification systems.

Authors:  Silke Kern; Henrik Zetterberg; Jürgen Kern; Anna Zettergren; Margda Waern; Kina Höglund; Ulf Andreasson; Hanna Wetterberg; Anne Börjesson-Hanson; Kaj Blennow; Ingmar Skoog
Journal:  Neurology       Date:  2018-04-13       Impact factor: 9.910

4.  Association of cerebrospinal fluid neurogranin levels with cognition and neurodegeneration in Alzheimer's disease.

Authors:  Mei Xue; Fu-Rong Sun; Ya-Nan Ou; Xue-Ning Shen; Hong-Qi Li; Yu-Yuan Huang; Qiang Dong; Lan Tan; Jin-Tai Yu
Journal:  Aging (Albany NY)       Date:  2020-05-18       Impact factor: 5.682

5.  Electroacupuncture reduces scopolamine-induced amnesia via mediating the miR-210/SIN3A and miR-183/SIN3A signaling pathway.

Authors:  Fan Ye; Shiming Tian; Huimin Hu; Zhengwen Yu
Journal:  Mol Med       Date:  2020-11-12       Impact factor: 6.354

6.  Reduced Cerebral Glucose Uptake in an Alzheimer's Rat Model With Glucose-Weighted Chemical Exchange Saturation Transfer Imaging.

Authors:  Peidong Chen; Zhiwei Shen; Qianqian Wang; Bingna Zhang; Zerui Zhuang; Jiefen Lin; Yuanyu Shen; Yanzhi Chen; Zhuozhi Dai; Renhua Wu
Journal:  Front Aging Neurosci       Date:  2021-03-17       Impact factor: 5.750

  6 in total

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