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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 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

news
3 news outlets
twitter
9 tweeters

Citations

dimensions_citation
187 Dimensions

Readers on

mendeley
315 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 9 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 315 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%
Korea, Republic of 1 <1%
Italy 1 <1%
Netherlands 1 <1%
Germany 1 <1%
Switzerland 1 <1%
Spain 1 <1%
Other 1 <1%
Unknown 301 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 59 19%
Student > Ph. D. Student 48 15%
Student > Master 48 15%
Student > Bachelor 36 11%
Other 20 6%
Other 65 21%
Unknown 39 12%
Readers by discipline Count As %
Medicine and Dentistry 62 20%
Agricultural and Biological Sciences 56 18%
Neuroscience 45 14%
Psychology 43 14%
Biochemistry, Genetics and Molecular Biology 25 8%
Other 30 10%
Unknown 54 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 28. 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
#1,263,150
of 23,864,146 outputs
Outputs from Genome Medicine
#278
of 1,477 outputs
Outputs of similar age
#14,643
of 311,031 outputs
Outputs of similar age from Genome Medicine
#7
of 35 outputs
Altmetric has tracked 23,864,146 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,477 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.3. This one has done well, scoring higher than 81% 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 311,031 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 95% of its contemporaries.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.