Evidence map›Paper›PMID 36658410›Full record

ArticleNeurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology2023

A pilot study on identifying gene signatures as markers for predicting patient response to antiseizure medications.

Yifei Duan, Liyuan Kang, Yujie He, Menglong Li, Ting Li, Zhining Wen, Lei Chen

Abstract read
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In one paragraph

Article in Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 99% of its field
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

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. Article
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

7 authors at 2 institutions in 2 countries.

Yifei Duan *Department of Neurology, West China Hospital, Sichuan University, No. 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China.
Liyuan Kang *College of Chemistry, Sichuan University, Chengdu, 610064, Sichuan, China.
Yujie HeCollege of Chemistry, Sichuan University, Chengdu, 610064, Sichuan, China.
Menglong LiCollege of Chemistry, Sichuan University, Chengdu, 610064, Sichuan, China.
Ting LiUniversity of Arkansas at Little Rock and University of Arkansas for Medical Sciences Joint Bioinformatics Program, Little Rock, AK, 72204, USA.
Zhining WenCollege of Chemistry, Sichuan University, Chengdu, 610064, Sichuan, China. w_zhining@scu.edu.cn.ORCID http://orcid.org/0000-0002-0477-4906
Lei ChenDepartment of Neurology, West China Hospital, Sichuan University, No. 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China. leilei_25@126.com.
Sichuan University · CNUniversity of Arkansas at Little Rock · US

Funding

National Natural Science Foundation of China 21575094National Natural Science Foundation of China 81871018
6 · The paper itself

Abstract

The majority of the biomarkers were associated with the diagnosis of epilepsy and few of them can be applied to predict the response to antiseizure medications (ASMs). In this study, we identified 26 significantly up-regulated genes and 32 down-regulated genes by comparing the gene expression profiles of patients with epilepsy that responded to valproate with those without applying any ASM. The results of gene set enrichment analysis indicated that the ferroptosis pathway was significantly impacted (p = 0.0087) in patients who responded to valproate. Interestingly, the gene NCOA4 in this pathway exhibited significantly different expression levels between the two groups, indicating that NCOA4 could serve as a potential biomarker to better understand the mechanism of valproate resistance. In addition, six up-regulated genes SF3A2, HMGN2, PABPN1, SSBP3, EFTUD2, and CREB3L2 as well as six down-regulated genes ZFP36L1, ACRC, SUB1, CALM2, TLK1, and STX2 also showed significantly different expression patterns between the two groups. Moreover, based on the gene expression profiles of the patients with the treatment of valproate, carbamazepine, and phenytoin, we proposed a strategy for predicting the response to the ASMs by using the Connectivity Map scoring method. Our findings could be helpful for better understanding the mechanisms of drug resistance of ASMs and improving the clinical treatment of epilepsy.

Indexed as

CarbamazepineValproic AcidAnticonvulsantsButyrate Response Factor 1HumansPeptide Elongation FactorsPhenytoinPilot ProjectsPoly(A)-Binding Protein IProtein Serine-Threonine KinasesResearch DesignRibonucleoprotein, U5 Small NuclearRNA Splicing FactorsTranscription FactorsAnticonvulsantsButyrate Response Factor 1CarbamazepineEFTUD2 protein, humanPABPN1 protein, humanPeptide Elongation FactorsPhenytoinPoly(A)-Binding Protein IProtein Serine-Threonine KinasesRibonucleoprotein, U5 Small NuclearRNA Splicing FactorsSF3A2 protein, humanTLK1 protein, humanTranscription FactorsValproic AcidZFP36L1 protein, humanAntiseizure medicationsDrug responseEpilepsyGene expression profilesRNA sequencingValproate

Identifiers

PMID36658410
OpenAlexW4317493537

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.