ReviewProteomics2025
Mining Alzheimer's Interactomes, Macromolecular Complexes and Pathways for Drug Discovery.
Review in Proteomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Network Analysis to Identify MicroRNAs Involved in Alzheimer's Disease and to Improve Drug Prioritization.Biomedicines · 2026Article
- Mining Alzheimer's Interactomes, Macromolecular Complexes and Pathways for Drug Discovery.Proteomics · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that leads to dementia. Many cases are diagnosed annually and there is no currently available cure. Understanding the underlying disease biology of AD through the study of molecular networks, particularly by mapping clinical variants to tissue-specific interactomes and regulatory macromolecular assemblies, offers a promising avenue to elucidate altered disease pathways. In this study, we applied differential interactome analysis using a manually curated AD dataset to identify how disease-associated mutations alter both transient and stable protein interactions. By focussing on variant-specific associations detected in brain-relevant tissues, we mapped disruptions in stable macromolecular assemblies and performed Reactome enrichment analysis to uncover perturbed pathways unique to each variant. Additionally, we explored therapeutic insights through the analysis of amyloid precursor protein (APP) physical interactors, identifying potential intervention points that influence amyloidogenic processing. Complementing protein-level data, we integrated microRNA (miRNA)-mediated regulatory interactions, revealing an additional layer of posttranscriptional control over key AD genes. Together, this multilayered strategy provides a framework for precision therapeutics in AD.
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What OpenQuestion 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 OpenQuestion graph.