A Multi-Dimensional Comparison of Alzheimer’s Disease Neurodegenerative Biomarkers

Article type: Research Article

Authors: Liu, Ying^a | Han, Pei-Ran^b | Hu, Hao^c | Wang, Zuo-Teng^c | Guo, Yu^d | Ou, Ya-Nan^c | Cao, Xi-Peng^b | Tan, Lan^{a; c; *} | Yu, Jin-Tai^{c; *} | Alzheimer’s Disease Neuroimaging Initiative¹

Affiliations: [a] Department of Neurology, Qingdao Municipal Hospital, Nanjing Medical University, Nanjing, China | [b] Clinical Research Center, Qingdao Municipal Hospital, Qingdao University, Qingdao, China | [c] Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China | [d] Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China

Correspondence: [*] Corresponding Authors: Jin-Tai Yu, MD, PhD, Department of Neurology and Institute of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, 12th Wulumuqi Zhong Road, Shanghai 200040, China. Tel.: +86 21 52888160; Fax: +86 21 62483421; E-mail: [email protected]. Lan Tan, MD, PhD, Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao 266071, China. E-mail: [email protected].

Note: [1] Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) data-base (http://adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI inves-tigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf

Abstract: Background:In the 2018 AT(N) framework, neurodegenerative (N) biomarkers plays an essential role in the research and staging of Alzheimer’s disease (AD); however, the different choice of N may result in discordances. Objective:We aimed to compare different potential N biomarkers. Methods:We examined these N biomarkers among 1,238 participants from Alzheimer’s Disease Neuroimaging Initiative (ADNI) in their 1) diagnostic utility, 2) cross-sectional and longitudinal correlations between different N biomarkers and clinical variables, and 3) the conversion risk of different N profiles. Results:Six neurodegenerative biomarkers changed significantly from preclinical AD, through prodromal AD to AD dementia stage, thus they were chosen as the candidate N biomarkers: hippocampal volume (HV), 18F-fluorodeoxyglucose-positron emission tomography (FDG-PET), cerebrospinal fluid (CSF), total tau (T-tau), plasma neurofilament light chain (NFL), CSF NFL, and CSF neurogranin (Ng). Results indicated that FDG-PET not only had the greatest diagnostic utility in differentiating AD from controls (area under the curve: FDG-PET, 0.922), but also had the strongest association with cognitive scores. Furthermore, FDG-PET positive group showed the fastest memory decline (hazard ratio: FDG-PET, 3.45), which was also true even in the presence of amyloid-β pathology. Moreover, we observed great discordances between three valuable N biomarkers (FDG-PET, HV, and T-tau). Conclusion:These results underline the importance of using FDG-PET as N in terms of cognitive decline and AD conversion, followed by HV, and could be a great complement to the AT(N) framework.

Keywords: Alzheimer’s disease, Alzheimer’s disease neuroimaging initiative, AT(N), biomarker, FDG, neurodegeneration

DOI: 10.3233/JAD-215724

Journal: Journal of Alzheimer's Disease, vol. 87, no. 1, pp. 197-209, 2022