ArticleProceedings of the National Academy of Sciences of the United States of America2025
Multiomics integration prioritizes potential drug targets for multiple sclerosis.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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.
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Who cites it
5 citing papers in PubMed.
- Genetic-Proteomic Integration Identifies Predictive Plasma Proteins for Multiple Sclerosis.Annals of neurology · 2026Article
- Multi-omics integration provides biological insight and prioritizes potential drug targets in multiple sclerosis progression.Journal of neuroinflammation · 2026Article
- Macrophage polarization-related genes with potential causal roles in osteoporosis: a multi-omics Mendelian randomization study.Journal of orthopaedic surgery and research · 2026Article
- Decoding disease and therapy through multiomics integration and systems analysis.Briefings in bioinformatics · 2026Review
- Genetic insights into drug targets for alzheimer's disease: integrative multi-omics analysis.Alzheimer's research & therapy · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Multiple sclerosis (MS) is an immune-mediated disease with no current cure. Drug discovery and repurposing are essential to enhance treatment efficacy and safety. We utilized summary statistics for protein quantitative trait loci (pQTL) of 2,004 plasma and 1,443 brain proteins, a genome-wide association study of MS susceptibility with 14,802 cases and 26,703 controls, both bulk and cell-type specific transcriptome data, and external pQTL data in blood and brain. Our integrative analysis included a proteome-wide association study to identify MS-associated proteins, followed by summary-data-based Mendelian randomization to determine potential causal associations. We used the HEIDI test and Bayesian colocalization analysis to distinguish pleiotropy from linkage. Proteins passing all analyses were prioritized as potential drug targets. We further conducted pathway annotations and protein-protein interaction network analysis (PPI) and verified our findings at mRNA and protein levels. We tested hundreds of MS-associated proteins and confirmed 18 potential causal proteins (nine in plasma and nine in brain). Among these, we found 78 annotated pathways and 16 existing non-MS drugs targeting six proteins. We also identified intricateAQ PPIs among seven potential drug targets and 19 existing MS drug targets, as well as PPIs of four targets across plasma and brain. We identified two targets using bulk mRNA expression data and four targets expressed in MS-related cell types. We finally verified 10 targets using external pQTL data. We prioritized 18 potential drug targets in plasma and brain, elucidating the underlying pathology and providing evidence for potential drug discovery and repurposing in MS.
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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.