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Genomic insights into the overlap between psychiatric disorders: implications for research and clinical practice

Overview of attention for article published in Genome Medicine, January 2014
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

news
3 news outlets
twitter
11 tweeters

Citations

dimensions_citation
165 Dimensions

Readers on

mendeley
288 Mendeley
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Title
Genomic insights into the overlap between psychiatric disorders: implications for research and clinical practice
Published in
Genome Medicine, January 2014
DOI 10.1186/gm546
Pubmed ID
Authors

Joanne L Doherty, Michael J Owen

Abstract

Psychiatric disorders such as schizophrenia, bipolar disorder, major depressive disorder, attention-deficit/hyperactivity disorder and autism spectrum disorder are common and result in significant morbidity and mortality. Although currently classified into distinct disorder categories, they show clinical overlap and familial co-aggregation, and share genetic risk factors. Recent advances in psychiatric genomics have provided insight into the potential mechanisms underlying the overlap between these disorders, implicating genes involved in neurodevelopment, synaptic plasticity, learning and memory. Furthermore, evidence from copy number variant, exome sequencing and genome-wide association studies supports a gradient of neurodevelopmental psychopathology indexed by mutational load or mutational severity, and cognitive impairment. These findings have important implications for psychiatric research, highlighting the need for new approaches to stratifying patients for research. They also point the way for work aiming to advance our understanding of the pathways from genotype to clinical phenotype, which will be required in order to inform new classification systems and to develop novel therapeutic strategies.

Twitter Demographics

The data shown below were collected from the profiles of 11 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 288 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 1%
United States 2 <1%
Sweden 2 <1%
Italy 1 <1%
Korea, Republic of 1 <1%
Australia 1 <1%
Netherlands 1 <1%
Switzerland 1 <1%
Spain 1 <1%
Other 1 <1%
Unknown 274 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 61 21%
Student > Master 47 16%
Student > Ph. D. Student 46 16%
Student > Bachelor 34 12%
Other 18 6%
Other 58 20%
Unknown 24 8%
Readers by discipline Count As %
Medicine and Dentistry 60 21%
Agricultural and Biological Sciences 56 19%
Neuroscience 45 16%
Psychology 41 14%
Biochemistry, Genetics and Molecular Biology 24 8%
Other 23 8%
Unknown 39 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 29. 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 21 July 2018.
All research outputs
#824,487
of 17,349,416 outputs
Outputs from Genome Medicine
#172
of 1,156 outputs
Outputs of similar age
#10,494
of 196,848 outputs
Outputs of similar age from Genome Medicine
#2
of 17 outputs
Altmetric has tracked 17,349,416 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,156 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.4. This one has done well, scoring higher than 85% 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 196,848 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% 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 has done particularly well, scoring higher than 94% of its contemporaries.