↓ Skip to main content

A Weighted Gene Co-expression Network Analysis Reveals lncRNA Abnormalities in the Peripheral Blood Associated With Ultra-High-Risk for Psychosis

Overview of attention for article published in Frontiers in Psychiatry, December 2020
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
20 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
A Weighted Gene Co-expression Network Analysis Reveals lncRNA Abnormalities in the Peripheral Blood Associated With Ultra-High-Risk for Psychosis
Published in
Frontiers in Psychiatry, December 2020
DOI 10.3389/fpsyt.2020.580307
Pubmed ID
Authors

Yan Ren, Wei Li, Sha Liu, Zhi Li, Jiaying Wang, Hong Yang, Yong Xu

Abstract

Objective: The primary study aim was to identify long non-coding RNA (lncRNA) abnormalities associated with ultra-high-risk (UHR) for psychosis based on a weighted gene co-expression network analysis. Methods: UHR patients were screened by the structured interview for prodromal syndromes (SIPS). We performed a WGCNA analysis on lncRNA and mRNA microarray profiles generated from the peripheral blood samples in 14 treatment-seeking patients with UHR who never received psychiatric medication and 18 demographically matched typically developing controls. Gene Ontology (GO) analysis and canonical correlation analysis were then applied to reveal functions and correlation between lncRNAs and mRNAs. Results: The lncRNAs were organized into co-expressed modules by WGCNA, two modules of which were strongly associated with UHR. The mRNA networks were constructed and two disease-associated mRNA modules were identified. A functional enrichment analysis showed that mRNAs were highly enriched for immune regulation and inflammation. Moreover, a significant correlation between lncRNAs and mRNAs were verified by a canonical correlation analysis. Conclusion: We identified novel lncRNA modules related to UHR. These results contribute to our understanding of the molecular basis of UHR from the perspective of systems biology and provide a theoretical basis for early intervention in the assumed development of schizophrenia.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 15%
Other 2 10%
Student > Bachelor 1 5%
Student > Doctoral Student 1 5%
Researcher 1 5%
Other 1 5%
Unknown 11 55%
Readers by discipline Count As %
Medicine and Dentistry 2 10%
Psychology 2 10%
Chemical Engineering 1 5%
Biochemistry, Genetics and Molecular Biology 1 5%
Nursing and Health Professions 1 5%
Other 2 10%
Unknown 11 55%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 January 2021.
All research outputs
#20,676,689
of 23,271,751 outputs
Outputs from Frontiers in Psychiatry
#7,971
of 10,377 outputs
Outputs of similar age
#431,237
of 506,170 outputs
Outputs of similar age from Frontiers in Psychiatry
#416
of 512 outputs
Altmetric has tracked 23,271,751 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,377 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 506,170 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 512 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.