Evidence map›Paper›PMID 42792961›Full record

ArticleGenes2026

Integrative Identification of Candidate Protein Targets and Compounds for Dystonia Using Mendelian Randomization, Single-Cell RNA Sequencing, and Network Pharmacology.

Lin Chen, Ming-Juan Fang, Nan Cheng, Yin Xu

Abstract read
In one paragraph

Article in Genes, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Lin ChenAnhui University of Chinese Medicine, Hefei 230061, China.
Ming-Juan FangInstitute of Neurology, Anhui University of Chinese Medicine, Hefei 230061, China.
Nan ChengAnhui University of Chinese Medicine, Hefei 230061, China.
Yin XuInstitute of Neurology, Anhui University of Chinese Medicine, Hefei 230061, China.ORCID 0000-0002-3123-5617

Funding

Anhui University of Traditional Chinese Medicine 2023rcyb020Anhui University of Traditional Chinese Medicine SYSPY2025YNGG02Natural Science Foundation of Anhui Province 2308085QH290University Natural Science Research Project of Anhui Province 2025AHGXZK31011University Natural Science Research Project of Anhui Province No. 2024AH050984
6 · The paper itself

Abstract

backgroundDystonia is a severe neurological disorder with enigmatic pathogenesis. Current treatment options are limited in preventing the disease progression, underscoring the urgent need for new targeted therapeutic agents to develop more effective therapies.

methodsWe performed a proteome-wide Mendelian randomization (MR) study and sensitivity analyses to evaluate the causal relationships between dystonia and proteins. GO and KEGG enrichment analysis of dystonia-associated proteins was conducted. Then, we built PPI network and identified the expression of hub-genes in specific brain neurons in single-cell sequencing data. Additionally, we performed drug enrichment analysis of hub-genes, and employed network pharmacology and molecular docking methods to identify potential drugs for dystonia.

resultsOur study identified genetically predicted associations consistent with a potential causal effect between 51 proteins and risk of dystonia. GO and KEGG enrichment analyses revealed that these proteins are involved cellular response to transforming growth factor-β stimulation and cytokine-cytokine receptor interaction. Notably, the PPI network exhibited 21 community relationships within the regulatory network among the 51 dystonia-associated proteins identified. The single-cell RNA annotations for brain cluster specificity revealed Tumor necrosis factor (TNF) was highly expressed in microglia cells. Drug enrichment analysis identified five traditional Chinese medicine monomers (paeoniflorin, artesunate, ginsenoside Rh1, psoralen, and quercetin dihydrate) as candidates for molecular docking analysis. Among these, paeoniflorin-TNF, quercetin dihydrate-TNF, and artesunate-TNF exhibited the highest binding energy (-9.1 kcal/mol).

conclusionsOur molecular-docking analysis suggested that traditional Chinese medicine monomers including paeoniflorin, quercetin dihydrate, and artesunate may serve as promising candidates for future drug development.

Indexed as

DystoniaGene Regulatory NetworksHumansMolecular Docking SimulationNetwork PharmacologyProtein Interaction MapsSequence Analysis, RNASingle-Cell AnalysisSingle-Cell Gene Expression Analysisdrug targetdystonianetwork pharmacologyproteome-wide mendelian randomizationsingle-cell RNA

Identifiers

PMID42792961
PMCPMC13606691

What Socratic holds

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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.