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Prediction of mild cognitive impairment progression using time-sensitive multimodal biomarkers
Jonathan Gallego-Rudolf, Alex I. Wiesman, Yara Yakoub, Henrik Zetterberg, Kaj Blennow, Sylvain Baillet, Sylvia Villeneuve. Science Advances, 2026-08-12
Topic: Risk, prevention and care in population studies
Alzheimer's disease (AD) develops over a prolonged asymptomatic phase marked by silent pathology. Identifying cognitively unimpaired individuals likely to progress to mild cognitive impairment (MCI) is essential for early intervention. We investigated whether multimodal combinations of biomarkers, including frequency-specific neurophysiological activity, enhance prediction beyond demographic and genetic factors in older adults (n = 102; 31 progressors; mean follow-up = 5.9 years). Biomarkers included MEG-derived alpha power, MRI-derived hippocampal volume, plasma Aβ42/40 ratio and p-tau217, and neocortical Aβ and entorhinal tau PET. Cox regression models estimated progression risk and tested time-varying prognostic effects. Neurophysiological and proteinopathy biomarkers improved prediction beyond clinical and genetic factors. Elevated alpha power predicted short-term risk, but its predictive value weakened over time, whereas high neocortical Aβ became increasingly predictive with longer follow-up. Plasma Aβ42/40, p-tau217, and tau PET each conferred higher risk, while hippocampal volume did not. Findings support a multimodal, time-sensitive framework for individualized risk prediction in preclinical AD.
Key findings
- Plasma Aβ42/40, p-tau217, and tau PET each conferred higher risk, while hippocampal volume did not.
Why it matters
In 102 older adults followed for about 5.9 years, this study found that blood and imaging biomarkers including plasma Aβ42/40, p-tau217, and tau PET each predicted higher risk of progressing to MCI, while hippocampal volume did not. Elevated alpha power predicted short-term risk but weakened over time, supporting a time-sensitive framework for individualized risk prediction in preclinical Alzheimer's disease.
Study details
- Participants102
- Evidence strengthLow
How this study scored 46/100
Published in a peer-reviewed journal. Scored zero for study design, effect reported and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Science Advances) |
| Journal's citation record | 3 / 4 | Science Advances: journal h-index 378 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 5 / 5 | 2026 — within 1 year(s) of the newest study here |
| Sample size | 2 / 4 | 102 participants |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 1 / 7 | Cited 1 times (OpenAlex, 2026-10-10) |
| Citations per year | 0 / 5 | 0.5 citations a year over 2 year(s) since 2026 |
| Impact for its field and year | 3 / 6 | Cited 4.7× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 0 / 4 | Cited 1 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 2 / 4 | Last-listed author Sylvia Villeneuve: h-index 48 (OpenAlex, whole career) |
| Institution's track record | 2 / 3 | University College London: institution h-index 2,029 (OpenAlex) |
| Multi-centre collaboration | 3 / 3 | OpenAlex lists 15 institution(s) in 6 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 41040687) |
| Free to read | 2 / 2 | Free to read |
| Total | 46 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
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 names 7 authors; APA and Vancouver show the first six, BibTeX and the downloads carry all of them. Check the citation against the original before you use it.
APA 7th
Gallego-Rudolf, J., Wiesman, A. I., Yakoub, Y., Zetterberg, H., Blennow, K., Baillet, S., et al. (2026). Prediction of mild cognitive impairment progression using time-sensitive multimodal biomarkers. Science Advances. https://doi.org/10.1126/sciadv.aee2305
Vancouver
Gallego-Rudolf J, Wiesman AI, Yakoub Y, Zetterberg H, Blennow K, Baillet S, et al. Prediction of mild cognitive impairment progression using time-sensitive multimodal biomarkers. Science Advances. 2026. doi:10.1126/sciadv.aee2305. PMID: 41040687.
BibTeX
@article{gallegorudolf2026-41040687,
author = {Gallego-Rudolf, Jonathan and Wiesman, Alex I. and Yakoub, Yara and Zetterberg, Henrik and Blennow, Kaj and Baillet, Sylvain and Villeneuve, Sylvia},
title = {{Prediction of mild cognitive impairment progression using time-sensitive multimodal biomarkers}},
journal = {Science Advances},
year = {2026},
doi = {10.1126/sciadv.aee2305},
pmid = {41040687},
url = {https://doi.org/10.1126/sciadv.aee2305}
}
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