ArticleThe journal of prevention of Alzheimer's disease2026
Bidirectional causal relationships between plasma proteins, neuroimaging metrics and risk of Alzheimer's disease.
Article in The journal of prevention of Alzheimer's disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundChanges in neuroimaging metrics are among the first detectable pathophysiological alterations in Alzheimer's disease (AD). Proteins are closely linked to fluctuations in neuroimaging metrics. Therefore, the analysis of the proteomic signature associated with neuroimaging metrics holds significant promise for uncovering therapeutic targets that contribute to AD.
methodsGWAS data concerning the Brain Imaging Data Structure (BIDs). The AD cohort comprised a total of 401,661 individuals diagnosed with AD, alongside 10,520 control participants. For a bidirectional MR analysis involving neuroimaging metrics, proteomics, and AD, the methods utilized included inverse variance weighted (IVW), MR Egger, weighted median, weighted mode, and the Wald ratio approaches.
resultsWe identified 12 neuroimaging metrics that demonstrate significant relevance to AD (thickness of the left total hemisphere, volume of the right thalamus, and et al.). These metrics are structural magnetic resonance imaging (MRI) biomarkers that remain stable throughout the entire course of AD, from the preclinical stage through mild cognitive impairment (MCI) to dementia. Additionally, we found a substantial number of 1633 proteins that also show a noteworthy causal relationship with AD. Functional enrichment analysis indicated that these proteins were predominantly focused within various pathways linked to AD, encompassing those involved in the synaptic vesicle cycle, synaptic membranes, neurotransmitter release, and the activity of GABA receptors. In addition, our research indicates that the significant relationships observed between the identified proteins and AD are influenced by neuroimaging metrics. Notably, we found that these neuroimaging metrics play a crucial role in mediating a substantial 67% of the inverse relationship that exists between PTPRC and the phenotypic characteristics associated with AD.
conclusionsThis study successfully establishes a connection between proteomic and neuroimaging metrics, as well as the AD that influence them. By creating this relationship, the research offers important information that aids in comprehending the intricate mechanisms involved in AD.
Indexed as
Identifiers
What Socratic holds
Registered trials
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.