Evidence map›Paper›PMID 36448305›Full record

ReviewBrain : a journal of neurology2023

Cryptic mutations of PLC family members in brain disorders: recent discoveries and a deep-learning-based approach.

Key-Hwan Lim, Sumin Yang, Sung-Hyun Kim, Euiseong Ko, Mingon Kang, Jae-Yeol Joo

Open access · bronzeAbstract readReview
In one paragraph

Review in Brain : a journal of neurology, 2023. 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
3.0field-weighted citation impact, top 8% 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, 17 citations in OpenAlex.

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  7. Unraveling sex differences in Alzheimer's disease and related endophenotypes with brain proteomes.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
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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

6 authors at 3 institutions in 2 countries.

Key-Hwan LimNeurodegenerative Disease Research Group, Korea Brain Research Institute, Daegu 41062, Republic of Korea.
Sumin YangDepartment of Pharmacy, College of Pharmacy, Hanyang University, Ansan, Gyeonggi-do 15588, Republic of Korea.
Sung-Hyun KimDepartment of Pharmacy, College of Pharmacy, Hanyang University, Ansan, Gyeonggi-do 15588, Republic of Korea.
Euiseong KoDepartment of Computer Science, University of Nevada, Las Vegas, NV 89154, USA.
Mingon KangDepartment of Computer Science, University of Nevada, Las Vegas, NV 89154, USA.ORCID 0000-0002-9565-9523
Jae-Yeol JooDepartment of Pharmacy, College of Pharmacy, Hanyang University, Ansan, Gyeonggi-do 15588, Republic of Korea.ORCID 0000-0003-2571-3173
Hanyang University · KRUniversity of Nevada, Las Vegas · USChungbuk National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Phospholipase C (PLC) is an essential isozyme involved in the phosphoinositide signalling pathway, which maintains cellular homeostasis. Gain- and loss-of-function mutations in PLC affect enzymatic activity and are therefore associated with several disorders. Alternative splicing variants of PLC can interfere with complex signalling networks associated with oncogenic transformation and other diseases, including brain disorders. Cells and tissues with various mutations in PLC contribute different phosphoinositide signalling pathways and disease progression, however, identifying cryptic mutations in PLC remains challenging. Herein, we review both the mechanisms underlying PLC regulation of the phosphoinositide signalling pathway and the genetic variation of PLC in several brain disorders. In addition, we discuss the present challenges associated with the potential of deep-learning-based analysis for the identification of PLC mutations in brain disorders.

Indexed as

Brain DiseasesDeep LearningHumansMutationPhosphatidylinositolsPhosphoinositide Phospholipase CType C PhospholipasesPhosphatidylinositolsPhosphoinositide Phospholipase CType C Phospholipasesbrain disordersdeep learninggenetic variationhigh-throughput analysisPLCs

Identifiers

PMID36448305
PMCPMC10115239
OpenAlexW4310398084

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.