Evidence map›Paper›PMID 32519815›Full record

ArticleCNS neuroscience & therapeutics2020

CpG methylation signature defines human temporal lobe epilepsy and predicts drug-resistant.

Wenbiao Xiao, Chaorong Liu, Kuo Zhong, Shangwei Ning, Rui Hou, Na Deng, Yuchen Xu, Zhaohui Luo, Yujiao Fu, Yi Zeng and 3 more

Open access · goldAbstract read
In one paragraph

Article in CNS neuroscience & therapeutics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
0.9field-weighted citation impact, top 27% 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

12 citing papers in PubMed, 19 citations in OpenAlex.

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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

13 authors at 3 institutions in 1 country.

Wenbiao XiaoDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.ORCID 0000-0002-8922-4654
Chaorong LiuDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.
Kuo ZhongTsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, China.
Shangwei NingCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Rui HouShanghai Biotechnology Corporation, Shanghai, China.
Na DengDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.
Yuchen XuDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.
Zhaohui LuoDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.
Yujiao FuDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.
Yi ZengDepartment of Geriatrics, Second Xiangya Hospital, Central South University, Changsha, China.
Bo XiaoDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.ORCID 0000-0001-5204-1902
Hongyu LongDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.ORCID 0000-0001-5641-8850
Lili LongDepartment of Neurology, Xiangya Hospital, Central South University, Changsha, China.
Central South University · CNHarbin Medical University · CNTsinghua–Berkeley Shenzhen Institute · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsTemporal lobe epilepsy (TLE) is the most common focal epilepsy syndrome in adults and frequently develops drug resistance. Studies have investigated the value of peripheral DNA methylation signature as molecular biomarker for diagnosis or prognosis. We aimed to explore methylation biomarkers for TLE diagnosis and pharmacoresistance prediction.

methodsWe initially conducted genome-wide DNA methylation profiling in TLE patients, and then selected candidate CpGs in training cohort and validated in another independent cohort by employing machine learning algorithms. Furthermore, nomogram comprising DNA methylation and clinicopathological data was generated to predict the drug response in the entire patient cohort. Lastly, bioinformatics analysis for CpG-associated genes was performed using Ingenuity Pathway Analysis.

resultsAfter screening and validation, eight CpGs were identified for diagnostic biomarker with an area under the curve (AUC) of 0.81 and six CpGs for drug-resistant prediction biomarker with an AUC of 0.79. The nomogram for drug-resistant prediction comprised methylation risk score, disease course, seizure frequency, and hippocampal sclerosis, with AUC as high as 0.96. Bioinformatics analysis indicated drug response-related CpGs corresponding genes closely related to DNA methylation.

conclusionsThis study demonstrates the ability to use peripheral DNA methylation signature as molecular biomarker for epilepsy diagnosis and drug-resistant prediction.

Indexed as

CpG IslandsDNA MethylationAdolescentAdultBiomarkersChildCohort StudiesDrug Resistant EpilepsyEpilepsy, Temporal LobeFemaleHumansMachine LearningMaleMiddle AgedYoung AdultBiomarkersbiomarkerDNA methylationmachine learningnomogramtemporal lobe epilepsy

Identifiers

PMID32519815
PMCPMC7539843
OpenAlexW3033031598

What OpenQuestion holds

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LicenceCC BY
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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.