Comparing progression biomarkers in clinical trials of early Alzheimer's disease

Nicholas C Cullen, Henrik Zetterberg, Philip S Insel, Bob Olsson, Ulf Andreasson, Alzheimer's Disease Neuroimaging Initiative, Kaj Blennow, Oskar Hansson, Niklas Mattsson-Carlgren
2020 Annals of Clinical and Translational Neurology  
To investigate the statistical power of plasma, imaging, and cognition biomarkers as Alzheimer's disease (AD) clinical trial outcome measures. Plasma neurofilament light, structural magnetic resonance imaging, and cognition were measured longitudinally in the Alzheimer's Disease Neuroimaging Initiative (ADNI) in control (amyloid PET or CSF Aβ42 negative [Aβ-] with Clinical Dementia Rating scale [CDR] = 0; n = 330), preclinical AD (Aβ + with CDR = 0; n = 218) and mild AD (Aβ + with CDR = 0.5-1;
more » ... = 697) individuals. A statistical power analysis was performed across biomarkers and groups based on longitudinal mixed effects modeling and using several different clinical trial designs. For a 30-month trial of preclinical AD, both the temporal composite and hippocampal volumes were superior to plasma neurofilament light and cognition. For an 18-month trial of mild AD, hippocampal volume was superior to all other biomarkers. Plasma neurofilament light became more effective with increased trial duration or sampling frequency. Imaging biomarkers were characterized by high slope and low within-subject variability, while plasma neurofilament light and cognition were characterized by higher within-subject variability. MRI measures had properties that made them preferable to cognition and pNFL as outcome measures in clinical trials of early AD, regardless of cognitive status. However, pNfL and cognition can still be effective depending on inclusion criteria, sampling frequency, and response to therapy. Future trials will help to understand how sensitive pNfL and MRI are to detect downstream effects on neurodegeneration of drugs targeting amyloid and tau pathology in AD.
doi:10.1002/acn3.51158 pmid:32779869 fatcat:3r5tnbemxvecrjog7dni7gy2ee