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Multivariate blood biomarkers capture resilience and resistance phenotypes across the Alzheimer’s disease spectrum
Mavromati K, Dalby C, Dibble A, Leonenko G, Birditt K, Lamprou S, Tvrda L, Konstantinidis I et al.. medRxiv, 2026-08-05
Topic: Genetics and APOE
Alzheimer’s disease pathology and cognitive outcomes frequently diverge, yet current single-axis definitions cannot identify resilient (high pathology, preserved cognition) and resistant (high risk, low pathology) subgroups reliably at scale, obscuring the mechanisms that uncouple pathological burden from cognitive decline. Here, we developed a multivariate blood-based framework integrating 19 molecular assays and six risk instruments in the Bio-Hermes-001 cohort (n=1,009). Unsupervised clustering identified resilient (n=91) and resistant (n=81) subgroups, together comprising 17% of the cohort, with distinct amyloid, tau, and neurodegeneration profiles. Amyloid-PET yielded convergent but only partially overlapping classifications. Proteomic, cytokine, and polygenic profiling further distinguished resistance through an APOE-centred genomic signature and resilience through neuroinflammatory markers associated with progression toward clinical Alzheimer’s disease. A four-biomarker panel (Aβ40, p-tau217, p-tau181, NfL) reproduced subgroup assignments with 83% accuracy. These findings support resilience and resistance as molecularly distinct subgroups and provide a scalable framework for pathology-informed stratification and mechanistic investigation.
Key findings
- Proteomic, cytokine, and polygenic profiling further distinguished resistance through an APOE-centred genomic signature and resilience through neuroinflammatory markers associated with progression toward clinical Alzheimer’s disease.
- These findings support resilience and resistance as molecularly distinct subgroups and provide a scalable framework for pathology-informed stratification and mechanistic investigation.
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Study details
- Participants1,009
- Evidence strengthModerate
How this study scored 16/100
Preprint — not yet peer-reviewed. It scored 37 on the same rubric, but non-peer-reviewed sources are capped at 16, so it shows as 16. Scored zero for study design, effect reported 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 23 of the 62 points we could judge it on, which is 37 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 2 / 10 | Tier 4 — not a peer-reviewed journal (medRxiv) |
| 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 | 3 / 4 | 1,009 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 | — / 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 | 2 / 2 | Free to read |
| Points | 23 / 62 | Scored on 12 of 20 parts. We have no data for the rest, so they are left out: 23 of the 62 points we could judge it on is 37 out of 100. |
| Total | 37 / 100 | Capped to 16 because this is not a peer-reviewed article. |
What each of these 20 components measures, and what this score is not →
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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
Mavromati, K., Dalby, C., Dibble, A., Leonenko, G., Birditt, K., Lamprou, S., et al. (2026). Multivariate blood biomarkers capture resilience and resistance phenotypes across the Alzheimer’s disease spectrum. medRxiv. https://doi.org/10.64898/2026.08.03.26359415
Vancouver
Mavromati K, Dalby C, Dibble A, Leonenko G, Birditt K, Lamprou S, et al. Multivariate blood biomarkers capture resilience and resistance phenotypes across the Alzheimer’s disease spectrum. medRxiv. 2026. doi:10.64898/2026.08.03.26359415.
BibTeX
@article{mavromati2026-0f2be5f0,
author = {Mavromati, K. and Dalby, C. and Dibble, A. and Leonenko, G. and Birditt, K. and Lamprou, S. and Tvrda, L. and Konstantinidis, I. and others},
title = {{Multivariate blood biomarkers capture resilience and resistance phenotypes across the Alzheimer’s disease spectrum}},
journal = {medRxiv},
year = {2026},
doi = {10.64898/2026.08.03.26359415},
url = {https://doi.org/10.64898/2026.08.03.26359415}
}
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