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Characterization of cross-tissue genetic-epigenetic effects and their patterns in schizophrenia

Overview of attention for article published in Genome Medicine, February 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • Average Attention Score compared to outputs of the same age and source

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Title
Characterization of cross-tissue genetic-epigenetic effects and their patterns in schizophrenia
Published in
Genome Medicine, February 2018
DOI 10.1186/s13073-018-0519-4
Pubmed ID
Authors

Dongdong Lin, Jiayu Chen, Nora Perrone-Bizzozero, Juan R. Bustillo, Yuhui Du, Vince D. Calhoun, Jingyu Liu

Abstract

One of the major challenges in current psychiatric epigenetic studies is the tissue specificity of epigenetic changes since access to brain samples is limited. Peripheral tissues have been studied as surrogates but the knowledge of cross-tissue genetic-epigenetic characteristics remains largely unknown. In this work, we conducted a comprehensive investigation of genetic influence on DNA methylation across brain and peripheral tissues with the aim to characterize cross-tissue genetic-epigenetic effects and their roles in the pathophysiology of psychiatric disorders. Genome-wide methylation quantitative trait loci (meQTLs) from brain prefrontal cortex, whole blood, and saliva were identified separately and compared. Focusing on cis-acting effects, we tested the enrichment of cross-tissue meQTLs among cross-tissue expression QTLs and genetic risk loci of various diseases, including major psychiatric disorders. CpGs targeted by cross-tissue meQTLs were also tested for genomic distribution and functional enrichment as well as their contribution to methylation correlation across tissues. Finally, a consensus co-methylation network analysis on the cross-tissue meQTL targeted CpGs was performed on data of the three tissues collected from schizophrenia patients and controls. We found a significant overlap of cis meQTLs (45-73 %) and targeted CpG sites (31-68 %) among tissues. The majority of cross-tissue meQTLs showed consistent signs of cis-acting effects across tissues. They were significantly enriched in genetic risk loci of various diseases, especially schizophrenia, and also enriched in cross-tissue expression QTLs. Compared to CpG sites not targeted by any meQTLs, cross-tissue targeted CpGs were more distributed in CpG island shores and enhancer regions, and more likely had strong correlation with methylation levels across tissues. The targeted CpGs were also annotated to genes enriched in multiple psychiatric disorders and neurodevelopment-related pathways. Finally, we identified one co-methylation network shared between brain and blood showing significant schizophrenia association (p = 5.5 × 10-6). Our results demonstrate prevalent cross-tissue meQTL effects and their contribution to the correlation of CpG methylation across tissues, while at the same time a large portion of meQTLs show tissue-specific characteristics, especially in brain. Significant enrichment of cross-tissue meQTLs in expression QTLs and genetic risk loci of schizophrenia suggests the potential of these cross-tissue meQTLs for studying the genetic effect on schizophrenia. The study provides compelling motivation for a well-designed experiment to further validate the use of surrogate tissues in the study of psychiatric disorders.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 81 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 21%
Researcher 10 12%
Student > Master 7 9%
Student > Postgraduate 6 7%
Student > Bachelor 6 7%
Other 15 19%
Unknown 20 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 18 22%
Agricultural and Biological Sciences 10 12%
Medicine and Dentistry 8 10%
Neuroscience 7 9%
Computer Science 4 5%
Other 13 16%
Unknown 21 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 27 March 2018.
All research outputs
#2,623,014
of 24,162,843 outputs
Outputs from Genome Medicine
#605
of 1,495 outputs
Outputs of similar age
#55,250
of 333,853 outputs
Outputs of similar age from Genome Medicine
#12
of 22 outputs
Altmetric has tracked 24,162,843 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,495 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.6. This one has gotten more attention than average, scoring higher than 59% of its peers.
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 333,853 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.