Evidence map›Paper›PMID 35646047›Full record

ArticleFrontiers in genetics2022

Shared and Cell-Type-Specific Gene Expression Patterns Associated With Autism Revealed by Integrative Regularized Non-Negative Matrix Factorization.

Jinting Guan, Yan Zhuang, Yue Kang, Guoli Ji

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2022. 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 95% 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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 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

4 authors at 1 institution in 1 country.

Jinting GuanDepartment of Automation, Xiamen University, Xiamen, China.
Yan ZhuangDepartment of Automation, Xiamen University, Xiamen, China.
Yue KangDepartment of Automation, Xiamen University, Xiamen, China.
Guoli JiDepartment of Automation, Xiamen University, Xiamen, China.
Xiamen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human brain-related disorders, such as autism spectrum disorder (ASD), are often characterized by cell heterogeneity, as the cell atlas of brains consists of diverse cell types. There are commonality and specificity in gene expression among different cell types of brains; hence, there may also be commonality and specificity in dysregulated gene expression affected by ASD among brain cells. Moreover, as genes interact together, it is important to identify shared and cell-type-specific ASD-related gene modules for studying the cell heterogeneity of ASD. To this end, we propose integrative regularized non-negative matrix factorization (iRNMF) by imposing a new regularization based on integrative non-negative matrix factorization. Using iRNMF, we analyze gene expression data of multiple cell types of the human brain to obtain shared and cell-type-specific gene modules. Based on ASD risk genes, we identify shared and cell-type-specific ASD-associated gene modules. By analyzing these gene modules, we study the commonality and specificity among different cell types in dysregulated gene expression affected by ASD. The shared ASD-associated gene modules are mostly relevant to the functioning of synapses, while in different cell types, different kinds of gene functions may be specifically dysregulated in ASD, such as inhibitory extracellular ligand-gated ion channel activity in GABAergic interneurons and excitatory postsynaptic potential and ionotropic glutamate receptor signaling pathway in glutamatergic neurons. Our results provide new insights into the molecular mechanism and pathogenesis of ASD. The identification of shared and cell-type-specific ASD-related gene modules can facilitate the development of more targeted biomarkers and treatments for ASD.

Indexed as

ASDcell-type-specific gene modulegene functionintegrative regularized non-negative matrix factorizationshared gene module

Identifiers

PMID35646047
PMCPMC9130660
OpenAlexW4280615846

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.