Evidence map›Paper›PMID 40217529›Full record

ArticleActa epileptologica2024

Characteristic spatial and frequency distribution of mutations in SCN1A.

Mengwen Zhang, Jing Guo, Bin Li, Kang Liu, Jiayuan Zhao, Jiayuan Zhang, Xuqing Lin, Bin Tang, Jie Wang, Weiping Liao and 1 more

Abstract read
In one paragraph

Article in Acta epileptologica, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

11 authors.

Mengwen Zhang *Department of Neurology, Institute of Neuroscience, Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510260, China.
Jing Guo *Department of Neurology, The Guangdong 999 Brain Hospital, Guangzhou, 510510, China.
Bin LiDepartment of Neurology, Institute of Neuroscience, Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510260, China.
Kang LiuGuangzhou Medical University, Guangzhou, 511436, China.
Jiayuan ZhaoGuangzhou Medical University, Guangzhou, 511436, China.
Jiayuan ZhangGuangzhou Medical University, Guangzhou, 511436, China.
Xuqing LinGuangzhou Medical University, Guangzhou, 511436, China.
Bin TangDepartment of Neurology, Institute of Neuroscience, Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510260, China.
Jie WangDepartment of Neurology, Institute of Neuroscience, Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510260, China.
Weiping LiaoDepartment of Neurology, Institute of Neuroscience, Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510260, China. wpliao@163.net.ORCID http://orcid.org/0000-0001-9929-9185
Na HeDepartment of Neurology, Institute of Neuroscience, Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, The Second Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510260, China. henachilli@163.com.ORCID http://orcid.org/0000-0002-9712-7782

Funding

Guangzhou Medical University Student Innovation Ability Promoting Program 02-408-240603131135Guangzhou Medical University Student Innovation Ability Promoting Program 2022A045Medical Scientific Research Foundation of Guangdong Province A2024536National Natural Science Foundation of China 82071548National Natural Science Foundation of China 82201609National Natural Science Foundation of China 82301639Research Foundation of China Association Against Epilepsy CU-2024-042
6 · The paper itself

Abstract

backgroundSCN1A is the most well-recognized and commonly mutated gene related to epilepsy. This study analyzed the characteristic spatial and frequency distributions of SCN1A mutations, aiming to provide important insight into the mutagenesis etiopathology of SCN1A-associated epilepsy.

methodsEpilepsy-associated SCN1A variants were retrieved from the SCN1A mutation database, the HGMD database, and literature reviews. The base substitutions, mutation frequencies in CpG dinucleotides, and spatial distributions of mutations in terms of exons and structural domains were analyzed.

resultsA total of 2621 SCN1A variants were identified in 5106 unrelated cases. The most common type was missense mutation, followed by frameshift mutations and splice site mutations. Among the missense mutations, transitions within CpG dinucleotides were much more recurrently identified than transitions within non-CpG dinucleotides, and the most common type was the G > A transition. Among the nonsense mutations, the most predominant type of single-base substitution was the C > T transition, among which 75.3% (235/312) were within CpG sites. The most common "hotspot" codons for missense mutations were codons 101, 946, and 1783; while for nonsense mutations it was codon 712. One-base deletion or insertion was the most common type of frameshift mutation, causing protein truncation. The three most common frameshift mutations were c.5536_5539delAAAC, c.4554dupA, and c.5010_5013delGTTT. Splice mutations were the most frequently identified in exon 4 with a hotspot site c.602 + 1G > A. The spatial distribution of missense mutations showed that exons 22 and 4 had the highest mutation density (111 and 84 mutations per 100 bp, respectively), and exon 12 had the lowest mutation density, with 4 mutations per 100 bp. Further distribution analysis of the protein domains revealed that missense mutations were more common in the pore region and voltage sensor (231 mutations per 100 amino acids, respectively), and the protein truncation mutations were distributed evenly among the domains.

conclusionsSCN1A mutations tend to cluster at distinct sites, depending on the characteristic CpG dinucleotides, exons, and functional domains. Higher mutation density in particular regions, such as exon 22 and exon 4, offers promising targets for therapeutic genetic interventions.

Indexed as

CpG dinucleotidesEpilepsyMutation hotspotSCN1ASpatial and frequency distribution

Identifiers

PMID40217529
PMCPMC11960241

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.