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MicroRNA-derived network analysis of differentially methylated genes in schizophrenia, implicating GABA receptor B1 [GABBR1] and protein kinase B [AKT1]

Overview of attention for article published in Biology Direct, October 2015
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Title
MicroRNA-derived network analysis of differentially methylated genes in schizophrenia, implicating GABA receptor B1 [GABBR1] and protein kinase B [AKT1]
Published in
Biology Direct, October 2015
DOI 10.1186/s13062-015-0089-y
Pubmed ID
Authors

Vadim Gumerov, Hedi Hegyi

Abstract

While hundreds of genes have been implicated already in the etiology of schizophrenia, the exact cause is not known or the disease is considered multigenic in origin. Recent discoveries of new types of RNAs and the gradual elimination of the "junk DNA" hypothesis refocused the attention on the noncoding part of the human genome. Here we re-analyzed a recent dataset of differentially methylated genes from schizophrenic patients and cross-tabulated them with cis regulatory and repetitive elements and microRNAs known to be involved in schizophrenia. We found that the number of schizophrenia-related (SZ) microRNA targets follows a scale-free distribution with several microRNA hubs and that schizophrenia-related microRNAs with shared targets form a small-world network. The top ten microRNAs with the highest number of SZ gene targets regulate approximately 80 % of all microRNA-regulated genes whereas the top two microRNAs regulate 40-52 % of all such genes. We also found that genes that are regulated by the same microRNAs tend to have more protein-protein interactions than randomly selected schizophrenia genes. This highlights the role microRNAs possibly play in coordinating the abundance of interacting proteins, an important function that has not been sufficiently explored before. The analysis revealed that GABBR1 is regulated by both of the top two microRNAs and acts as a hub by interacting with many schizophrenia-related genes and sharing several types of transcription-binding sites with its interactors. We also found that differentially methylated repetitive elements are significantly more methylated in schizophrenia, pointing out their potential role in the disease. We find that GABBR1 has a central importance in schizophrenia, even if no direct cause and effect have been shown for it for the time. In addition to being a hub in microRNA-derived regulatory pathways and protein-protein interactions, its centrality is also supported by the high number of cis regulatory elements and transcription factor-binding sites that regulate its transcription. These findings are in line with several genome-wide association studies that repeatedly find the major histocompatibility region (where GABBR1 is located) to have the highest number of single nucleotide polymorphisms in schizophrenics. Our model also offers an explanation for the downregulation of protein kinase B, another consistent finding in schizophrenic patients. Our observations support the notion that microRNAs fine-tune the amount of proteins acting in the same biological pathways in schizophrenia, giving further support to the emerging theory of competing endogenous RNAs. The manuscript was reviewed by Jaap Heringa, Sandor Pongor and Zoltan Gaspari.

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Mendeley readers

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The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 40 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 20%
Researcher 8 20%
Student > Master 6 15%
Student > Bachelor 3 8%
Student > Doctoral Student 2 5%
Other 6 15%
Unknown 7 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 20%
Neuroscience 7 18%
Medicine and Dentistry 5 13%
Psychology 4 10%
Biochemistry, Genetics and Molecular Biology 3 8%
Other 4 10%
Unknown 9 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 09 June 2016.
All research outputs
#13,448,755
of 22,829,683 outputs
Outputs from Biology Direct
#308
of 487 outputs
Outputs of similar age
#131,734
of 278,190 outputs
Outputs of similar age from Biology Direct
#11
of 17 outputs
Altmetric has tracked 22,829,683 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 487 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one is in the 33rd percentile – i.e., 33% 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 278,190 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.