Evidence map›Paper›PMID 41830135›Full record

ArticleAlzheimer's & dementia : the journal of the Alzheimer's Association2026

Multivariate patterns of plasma biomarkers predict region-specific Alzheimer's pathology and cognitive decline across independent cohorts.

Jafar Zamani, Amirali Vahid, Edward N Wilson, S M Hadi Hosseini, Alzheimer's Disease Neuroimaging Initiative

Abstract read
In one paragraph

Article in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Jafar ZamaniComputational Brain Research and Intervention (C-Brain) Lab, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California, USA.ORCID 0000-0002-1621-3751
Amirali VahidComputational Brain Research and Intervention (C-Brain) Lab, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California, USA.
Edward N WilsonNeurology & Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA.
S M Hadi HosseiniComputational Brain Research and Intervention (C-Brain) Lab, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California, USA.
Alzheimer's Disease Neuroimaging Initiative

Funding

Microstructural changes in gray and white matter in aging and ADR01AG073362 · NIA · STANFORD UNIVERSITY · PI Hadi Hosseini · 2022 to 2026
$3.7M
Interactive Effects of Aging and AD on Brain NetworksR01AG072470 · NIA · STANFORD UNIVERSITY · PI Hadi Hosseini · 2022 to 2026
$2.9M
NIA NIH HHS R01AG072470NIA NIH HHS R01AG073362
6 · The paper itself

Abstract

introductionAlzheimer's disease (AD) is characterized by the progressive accumulation of amyloid-beta (Aβ) plaques, tau tangles, and neurodegeneration (ATN framework). While neuroimaging detects these changes, it is costly and not widely accessible. Blood-based biomarkers offer scalable alternatives for early detection.

methodsWe integrated plasma biomarkers, neuroimaging, and cognitive data from two large cohorts. We examined multivariate patterns of plasma Aβ42/Aβ40, phosphorylated tau (p-tau) 217, p-tau181, neurofilament light (NfL), and glial fibrillary acidic protein (GFAP) that predict amyloid, tau, neurodegeneration, and memory decline.

resultsSpecific plasma biomarker combinations predicted amyloid burden in the precuneus, tau in the entorhinal cortex, hippocampal atrophy, and memory decline. Models trained in one cohort accurately predicted outcomes in the other, confirming cross-cohort generalizability. DISCUSSION: Distinct plasma signatures reflect underlying AD pathways, supporting the use of blood-based biomarkers as cost-effective, noninvasive tools for early detection, disease monitoring, and individualized risk profiling.

Indexed as

Alzheimer DiseaseBiomarkersBrainCognitive DysfunctionAgedAged, 80 and overAmyloid beta-PeptidesCohort StudiesFemaleGlial Fibrillary Acidic ProteinHumansMaleNeurofilament ProteinsPeptide Fragmentstau ProteinsAmyloid beta-PeptidesBiomarkersGlial Fibrillary Acidic Proteinneurofilament protein LNeurofilament ProteinsPeptide Fragmentstau ProteinsAlzheimer's disease (AD)ATN frameworkpathologyplasma biomarkerspredictive models

Identifiers

PMID41830135
PMCPMC13093725

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.