Baseline structural MRI and plasma biomarkers predict longitudinal structural atrophy and cognitive decline in early AD. (31st December 2021)

• Record Type: Journal Article
• Authors: Xie, Long; Das, Sandhitsu R.; Wisse, Laura; Ittyerah, Ranjit; de Flores, Robin; Yushkevich, Paul A.; Wolk, David A.
• Is Part Of: Alzheimer's & dementia. Volume 17(2021)Supplement 1
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-12-31
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.056164
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: In clinical trials targeting early Alzheimer's disease (AD), recruiting participants that are more likely to progress over the course of the trials is crucial to success. Molecular and neurodegenerative markers obtained through PET or in cerebrospinal fluid have significant prognostic value, but they are costly or invasive. In this study, we hypothesize that a combination of plasma and structural MRI biomarkers, which overcome these limitations, are predictive of longitudinal progression measured by atrophy and cognitive decline in early AD, providing a more feasible solution. Methods: Longitudinal 3 Tesla T1‐weighted MRI and cognitive measurements [logical memory, delayed recall and clinical dementia rating sum‐of‐boxes] of 662 cognitively normal (CN) and MCI participants [divided into β‐amyloid positive/negative (A+/A‐)] from ADNI were included (Table 1). Anterior/posterior hippocampus, entorhinal cortex, Brodmann areas (BA) 35 and 36, and parahippocampal cortex were segmented in baseline MRI. Annualized change rates of BA35 thickness [the first region of neurofibrillary tangle pathology] and cognitive measurements were estimated using linear modeling. In each diagnostic group and A+/A‐ subgroups, stepwise linear regression model with age, gender, education and intracranial volume as fixed variables and all baseline MRI and plasma measurements [neurofilament light chain (NfL), pTau‐181] was implemented to investigate their predictive power for each longitudinal measure. In addition, the area under the curve (AUC) of each model in discriminating the first and last terciles of each longitudinal measurement was reported. Results: Baseline plasma and structural biomarkers provided complementary information in predicting longitudinal atrophy and cognitive decline in controls and MCI (Table 2, Figure 1). These relationships were maintained (albeit with some differences in most predicted measures) when limited to A+ subgroups (preclinical and prodromal AD, Table 4) with AUCs ranging from 0.70‐0.84. Interestingly, baseline structural measures are consistently included in all the models. Conclusions: We demonstrated that baseline plasma and MRI biomarkers provide complementary information in predicting brain atrophy and cognitive decline. This indicates the combination of these biomarkers, which are relatively easy to obtain, may have important use for recruitment in clinical trials and practice. Additionally, the effect in A‐ CN indicates the potential use of our structural biomarker in predicting normal age‐related decline.