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Using coordinate-based meta-analyses to explore structural imaging genetics

Overview of attention for article published in Brain Structure and Function, May 2018
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  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

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35 Mendeley
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Article details
Title
Using coordinate-based meta-analyses to explore structural imaging genetics
Published in
Brain Structure and Function, May 2018
DOI 10.1007/s00429-018-1670-9
Pubmed ID
Authors
Abstract

Imaging genetics has become a highly popular approach in the field of schizophrenia research. A frequently reported finding is that effects from common genetic variation are associated with a schizophrenia-related structural endophenotype. Genetic contributions to a structural endophenotype may be easier to delineate, when referring to biological rather than diagnostic criteria. We used coordinate-based meta-analyses, namely the anatomical likelihood estimation (ALE) algorithm on 30 schizophrenia-related imaging genetics studies, representing 44 single-nucleotide polymorphisms at 26 gene loci investigated in 4682 subjects. To test whether analyses based on biological information would improve the convergence of results, gene ontology (GO) terms were used to group the findings from the published studies. We did not find any significant results for the main contrast. However, our analysis enrolling studies on genotype × diagnosis interaction yielded two clusters in the left temporal lobe and the medial orbitofrontal cortex. All other subanalyses did not yield any significant results. To gain insight into possible biological relationships between the genes implicated by these clusters, we mapped five of them to GO terms of the category "biological process" (AKT1, CNNM2, DISC1, DTNBP1, VAV3), then five to "cellular component" terms (AKT1, CNNM2, DISC1, DTNBP1, VAV3), and three to "molecular function" terms (AKT1, VAV3, ZNF804A). A subsequent cluster analysis identified representative, non-redundant subsets of semantically similar terms that aided a further interpretation. We regard this approach as a new option to systematically explore the richness of the literature in imaging genetics.

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X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 5 14%
Student > Master 3 9%
Student > Doctoral Student 2 6%
Student > Ph. D. Student 2 6%
Student > Postgraduate 2 6%
Other 2 6%
Unknown 19 54%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 11%
Psychology 3 9%
Neuroscience 3 9%
Agricultural and Biological Sciences 2 6%
Environmental Science 1 3%
Other 2 6%
Unknown 20 57%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 16 May 2018.
All research outputs
#10,708,918
of 34,571,987 outputs
Outputs from Brain Structure and Function
#602
of 1,978 outputs
Outputs of similar age
#133,024
of 372,695 outputs
Outputs of similar age from Brain Structure and Function
#14
of 36 outputs
Altmetric has tracked 34,571,987 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 1,978 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one has gotten more attention than average, scoring higher than 69% 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 372,695 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 64% of its contemporaries.
We're also able to compare this research output to 36 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 61% of its contemporaries.