Evidence map›Paper›PMID 36982355›Full record

ReviewInternational journal of molecular sciences2023

Forward Genetics-Based Approaches to Understanding the Systems Biology and Molecular Mechanisms of Epilepsy.

Anton D Shevlyakov, Tatiana O Kolesnikova, Murilo S de Abreu, Elena V Petersen, Konstantin B Yenkoyan, Konstantin A Demin, Allan V Kalueff

Open access · goldFull text readReview
In one paragraph

Review in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
3.4field-weighted citation impact, top 7% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Molecular and Cellular Mechanisms of Epilepsy 2.0.International journal of molecular sciences · 2023
    Article
  9. 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 5 institutions in 2 countries.

Anton D ShevlyakovGraduate Program in Bioinformatics and Genomics, Sirius University of Science and Technology, 354340 Sochi, Russia.
Tatiana O KolesnikovaNeuroscience Program, Sirius University of Science and Technology, 354340 Sochi, Russia.
Murilo S de AbreuMoscow Institute of Physics and Technology, 11730 Moscow, Russia.ORCID 0000-0001-5562-0715
Elena V PetersenMoscow Institute of Physics and Technology, 11730 Moscow, Russia.
Konstantin B YenkoyanNeuroscience Laboratory of COBRAIN Center for Fundamental Brain Research, and Biochemistry Department, Yerevan State Medical University named after M. Heratsi, Yerevan 0025, Armenia.ORCID 0000-0003-3346-4306
Konstantin A DeminInstitute of Translational Biomedicine, St. Petersburg State University, 199034 St. Petersburg, Russia.ORCID 0000-0003-0258-2801
Allan V KalueffNeuroscience Program, Sirius University of Science and Technology, 354340 Sochi, Russia.ORCID 0000-0002-7525-1950
Moscow Institute of Physics and Technology · RUSirius University of Science and Technology · RUSt Petersburg University · RUUral Federal University · RUYerevan State Medical University · AM

Funding

European Union-funded H2020 COBRAIN project 857600Republic of Armenia State Committee of Science 20TTCG-3A012Republic of Armenia State Committee of Science N10-14/I-1
6 · The paper itself

Abstract

Epilepsy is a highly prevalent, severely debilitating neurological disorder characterized by seizures and neuronal hyperactivity due to an imbalanced neurotransmission. As genetic factors play a key role in epilepsy and its treatment, various genetic and genomic technologies continue to dissect the genetic causes of this disorder. However, the exact pathogenesis of epilepsy is not fully understood, necessitating further translational studies of this condition. Here, we applied a computational in silico approach to generate a comprehensive network of molecular pathways involved in epilepsy, based on known human candidate epilepsy genes and their established molecular interactors. Clustering the resulting network identified potential key interactors that may contribute to the development of epilepsy, and revealed functional molecular pathways associated with this disorder, including those related to neuronal hyperactivity, cytoskeletal and mitochondrial function, and metabolism. While traditional antiepileptic drugs often target single mechanisms associated with epilepsy, recent studies suggest targeting downstream pathways as an alternative efficient strategy. However, many potential downstream pathways have not yet been considered as promising targets for antiepileptic treatment. Our study calls for further research into the complexity of molecular mechanisms underlying epilepsy, aiming to develop more effective treatments targeting novel putative downstream pathways of this disorder.

Indexed as

EpilepsySystems BiologyAnticonvulsantsGenomeHumansSeizuresAnticonvulsantsepilepsygenesgenetic basesin silico modelingmolecular network

Identifiers

PMID36982355
PMCPMC10049737
OpenAlexW4323863130

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read2
Read underepoch 390

Registered trials

None linked

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.