Cerebrospinal fluid and plasma biomarker trajectories with increasing amyloid deposition in Alzheimer's disease

Abstract

Failures in Alzheimer's disease (AD) drug trials highlight the need to further explore disease mechanisms and alterations of biomarkers during the development of AD. Using cross-sectional data from 377 participants in the BioFINDER study, we examined seven cerebrospinal fluid (CSF) and six plasma biomarkers in relation to β-amyloid (Aβ) PET uptake to understand their evolution during AD. In CSF, Aβ42 changed first, closely followed by Aβ42/Aβ40, phosphorylated-tau (P-tau), and total-tau (T-tau). CSF neurogranin, YKL-40, and neurofilament light increased after the point of Aβ PET positivity. The findings were replicated using Aβ42, Aβ40, P-tau, and T-tau assays from five different manufacturers. Changes were seen approximately simultaneously for CSF and plasma biomarkers. Overall, plasma biomarkers had smaller dynamic ranges, except for CSF and plasma P-tau which were similar. In conclusion, using state-of-the-art biomarkers, we identified the first changes in Aβ, closely followed by soluble tau. Only after Aβ PET became abnormal, biomarkers of neuroinflammation, synaptic dysfunction, and neurodegeneration were altered. These findings lend in vivo support of the amyloid cascade hypotheses in humans.

Keywords: Alzheimer disease; amyloid positron emission tomography; cerebrospinal fluid biomarkers; plasma biomarkers.

Figure 1. CSF and plasma biomarker trajectories as a function of increasing Aβ accumulation

1. A, B

   The biomarker data were fitted using monotone spline models where Aβ PET SUVR acted as a proxy for time in AD. CSF (A) and plasma (B) biomarkers are shown separately, but selected direct comparisons are shown in Fig 3. Individual spline models with actual data points are shown in Appendix Figs S1 and S2. The threshold for Aβ was established using mixture modeling statistics. Point of change on the trajectory (also referred to as significant biomarker change) is shown as vertical dashed lines. They were defined as a change in 2 SE (derived from 500 bootstrap samples) from the starting point of the modeled trajectory. Note that plasma P‐tau data were missing in 34 cases. To facilitate comparisons between different CSF and plasma biomarkers, the levels have been transformed to z‐scores based on the distribution in the present population (i.e., a z‐score of 0 corresponds to the mean of the study cohort).

Figure 2. Point of significant biomarker change with 95% CIs

Change points (also referred to as a significant biomarker change) with 95% CIs of the modeled biomarker trajectories are shown in Fig 1. Hippocampus volume divided by total intracranial volume was added for reference.

Figure 3. Comparison of selected CSF and plasma biomarker models

1. A

   Same models as in Fig 1A and B for CSF and plasma Aβ40, Aβ42, and Aβ42/40, but now in the same panel for easier comparison.

2. B

   Spline models from the same dataset where there were no missing data for plasma P‐tau (n = 343); i.e., the plasma P‐tau curve is the same as in Fig 1B, but CSF P‐tau is slightly different compared Fig 1A.

Data information: To facilitate comparisons between different CSF and plasma biomarkers, the levels have been transformed to z‐scores based on the distribution in the present population (i.e., a z‐score of 0 corresponds to the mean of the study cohort).

Figure 4. Comparison of CSF biomarker trajectories from five different vendors

1. A–D

   The biomarker data were fitted using monotone spline models for CSF Aβ42 (A), Aβ42/40 (B), P‐tau (C), and T‐tau (D) assays, where Aβ PET SUVR acted as a proxy for time in AD. Point of change on the trajectory (also referred to as significant biomarker change) is shown as vertical dashed lines. Significant changes were identified for all biomarkers, but some were almost identical and are therefore partially hidden (see Fig 5 for a better overview of change points). Note that this analysis was performed on a slightly smaller sample where all participants had a complete dataset of all assays (n = 352 vs. n = 377 in the whole population).

Figure 5. Comparison of change points for the different Aβ42, Aβ42/40, T‐tau, and P‐tau assays

Significant biomarker changes with 95% CIs of the modeled biomarker trajectories are shown in Fig 4. Note that this analysis was performed on a smaller sample (n = 352 vs. n = 377) where all participants had a complete dataset of all assays, which gave slightly different results for the Elecsys® assay compared to the full dataset.