Evidence map›Paper›PMID 32648482›Full record

ArticleCanadian journal of psychiatry. Revue canadienne de psychiatrie2020

A Combined Analysis of Genetically Correlated Traits Identifies Genes and Brain Regions for Insomnia.

Kezhi Liu, Ling Zhu, Minglan Yu, Xuemei Liang, Jin Zhang, Youguo Tan, Chaohua Huang, Wenying He, Wei Lei, Jing Chen and 2 more

Open access · bronzeAbstract read
In one paragraph

Article in Canadian journal of psychiatry. Revue canadienne de psychiatrie, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 33% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

12 authors at 3 institutions in 1 country.

Kezhi LiuDepartment of Psychiatry, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
Ling ZhuDepartment of Psychiatry, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
Minglan YuMedical Laboratory Center, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
Xuemei LiangDepartment of Psychiatry, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
Jin ZhangDepartment of Psychiatry, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
Youguo TanZigong Mental Health Center, Zigong, Sichuan, China.
Chaohua HuangDepartment of Psychiatry, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
Wenying HeDepartment of Psychiatry, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
Wei LeiDepartment of Psychiatry, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
Jing ChenDepartment of Psychiatry, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
Xiaochu GuClinical Laboratory, Suzhou Guangji Hospital, Suzhou, Jiangsu, China.
Bo XiangDepartment of Psychiatry, Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.ORCID 0000-0001-8341-2286
Affiliated Hospital of Southwest Medical University · CNSuzhou Guangji Hospital · CNZigong First People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsPrevious studies have inferred that there is a strong genetic component in insomnia. However, the etiology of insomnia is still unclear. This study systematically analyzed multiple genome-wide association study (GWAS) data sets with core human pathways and functional networks to detect potential gene pathways and networks associated with insomnia.

methodsWe used a novel method, multitrait analysis of genome-wide association studies (MTAG), to combine 3 large GWASs of insomnia symptoms/complaints and sleep duration. The i-Gsea4GwasV2 and Reactome FI programs were used to analyze data from the result of MTAG analysis and the nominally significant pathways, respectively.

resultsThrough analyzing data sets using the MTAG program, our sample size increased from 113,006 subjects to 163,188 subjects. A total of 17 of 1,816 Reactome pathways were identified and showed to be associated with insomnia. We further revealed 11 interconnected functional and topologically interacting clusters (Clusters 0 to 10) that were associated with insomnia. Based on the brain transcriptome data, it was found that the genes in Cluster 4 were enriched for the transcriptional coexpression profile in the prenatal dorsolateral prefrontal cortex (

conclusionsThe findings provided new genes, pathways, and brain regions to understand the pathology of insomnia.

Indexed as

Genetic Predisposition to DiseaseGenome-Wide Association StudyBrainHumansSleep Initiation and Maintenance DisordersGWASimaging geneticsinsomnianetwork analysis

Identifiers

PMID32648482
PMCPMC7658420
OpenAlexW3108277634

What OpenQuestion holds

Textmetadata
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.