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Biomarker Variability Limits Individualized Amyloid Time Estimation in Alzheimer Disease
Wisch JK, Jiao Z, Millar PR, McKay NS, Beric A, Lin W, Baker B, Stauber J et al.. bioRxiv, 2026-07-13
Topic: Plasma and spinal-fluid biomarkers
Objective Disease progression modeling (DPM) or “amyloid time” is increasingly used to stage Alzheimer disease (AD). DPM performance depends on within-individual heterogeneity in rates of pathological accumulation as well as test-retest reliability of the biomarker. The relative contributions of these variabilities have not been systematically assessed. This would be particularly relevant if extrapolations from DPM were to be used to make individual-level predictions for research, clinical trials, or potentially future clinical practice. Methods We conducted simulation studies incorporating empirically-derived noise properties from amyloid biomarkers to assess the contributions of inter- and intra-individual variability. Findings generalized in an autosomal dominant AD cohort with amyloid positron emission tomography (PET), cerebrospinal fluid (CSF), and plasma biomarkers and in a sporadic AD cohort with both amyloid PET and plasma biomarkers. We assessed group level DPM performance via mean average error (MAE) and root mean squared error (RMSE). At the individual level, we evaluated distinctness of distributions of biomarker levels associated with specific disease timings. Results Inter-individual variability was the dominant source of error in temporal estimates. Intra-individual variability reduced estimate stability. Optimal performance occurred in biomarkers with positive average accumulation rates where a subset of individuals had exceptionally high levels of accumulation. In research study data, amyloid PET outperformed CSF and plasma biomarkers. Interpretation DPM is fundamentally constrained by dynamic range, variability, and test–retest reliability of the biomarker of interest. Current DPM approaches are more robust at the group level, particularly when applied to biomarkers with more than 10-15% variability like fluid biomarkers. Funding National Institute on Aging, Alzheimer’s Association, German Center for Neurodegenerative Diseases, Raul Carrea Institute for Neurological Research, Japan Agency for Medical Research and Development, Korean Ministry of Health & Welfare and Ministry of Science and ICT, Spanish Institute of Health.
Key findings
- At the individual level, we evaluated distinctness of distributions of biomarker levels associated with specific disease timings.
- Results Inter-individual variability was the dominant source of error in temporal estimates.
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Study details
- Evidence strengthModerate
How this study scored 16/100
Preprint — not yet peer-reviewed. It scored 24 on the same rubric, but non-peer-reviewed sources are capped at 16, so it shows as 16. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it. We have no data on times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 15 of the 62 points we could judge it on, which is 24 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 2 / 10 | Tier 4 — not a peer-reviewed journal (bioRxiv) |
| Journal's citation record | 0 / 4 | Not a journal article, so the journal's record does not count |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 3 / 5 | Rated “moderate” in our summary |
| Peer-review validation | 4 / 10 | Preprint — not yet peer-reviewed. Hosted on a preprint server. |
| How recent | 5 / 5 | 2026 — within 1 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 1 / 2 | Not in PubMed, but has a DOI |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Points | 15 / 62 | Scored on 12 of 20 parts. We have no data for the rest, so they are left out: 15 of the 62 points we could judge it on is 24 out of 100. |
| Total | 24 / 100 | Capped to 16 because this is not a peer-reviewed article. |
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Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.
APA 7th
Wisch, J. K., Jiao, Z., Millar, P. R., McKay, N. S., Beric, A., Lin, W., et al. (2026). Biomarker Variability Limits Individualized Amyloid Time Estimation in Alzheimer Disease. bioRxiv. https://doi.org/10.64898/2026.07.08.737258
Vancouver
Wisch JK, Jiao Z, Millar PR, McKay NS, Beric A, Lin W, et al. Biomarker Variability Limits Individualized Amyloid Time Estimation in Alzheimer Disease. bioRxiv. 2026. doi:10.64898/2026.07.08.737258.
BibTeX
@article{wisch2026-d4682f47,
author = {Wisch, J. K. and Jiao, Z. and Millar, P. R. and McKay, N. S. and Beric, A. and Lin, W. and Baker, B. and Stauber, J. and others},
title = {{Biomarker Variability Limits Individualized Amyloid Time Estimation in Alzheimer Disease}},
journal = {bioRxiv},
year = {2026},
doi = {10.64898/2026.07.08.737258},
url = {https://doi.org/10.64898/2026.07.08.737258}
}