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Genetics, sleep and memory: a recall-by-genotype study of ZNF804A variants and sleep neurophysiology

Overview of attention for article published in BMC Medical Genomics, October 2015
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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)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

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1 news outlet
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Citations

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10 Dimensions

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82 Mendeley
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Title
Genetics, sleep and memory: a recall-by-genotype study of ZNF804A variants and sleep neurophysiology
Published in
BMC Medical Genomics, October 2015
DOI 10.1186/s12881-015-0244-4
Pubmed ID
Authors

Charlotte Hellmich, Claire Durant, Matthew W. Jones, Nicholas J. Timpson, Ullrich Bartsch, Laura J. Corbin

Abstract

Schizophrenia is a complex, polygenic disorder for which over 100 genetic variants have been identified that correlate with diagnosis. However, the biological mechanisms underpinning the different symptom clusters remain undefined. The rs1344706 single nucleotide polymorphism within ZNF804A was among the first genetic variants found to be associated with schizophrenia. Previously, neuroimaging and cognitive studies have revealed several associations between rs1344706 and brain structure and function. The aim of this study is to use a recall-by-genotype (RBG) design to investigate the biological basis for the association of ZNF804A variants with schizophrenia. A RBG study, implemented in a population cohort, will be used to evaluate the impact of genetic variation at rs1344706 on sleep neurophysiology and procedural memory consolidation in healthy participants. Participants will be recruited from the Avon Longitudinal Study of Parents and Children (ALSPAC) on the basis of genotype at rs1344706 (n = 24). Each participant will be asked to take part in two nights of in-depth sleep monitoring (polysomnography) allowing collection of neurophysiological sleep data in a manner not amenable to large-scale study. Sleep questionnaires will be used to assess general sleep quality and subjective sleep experience after each in-house recording. A motor sequencing task (MST) will be performed before and after the second night of polysomnography. In order to gather additional data about habitual sleep behaviour participants will be asked to wear a wrist worn activity monitor (actiwatch) and complete a sleep diary for two weeks. This study will explore the biological function of ZNF804A genotype (rs1344706) in healthy volunteers by examining detailed features of sleep architecture and physiology in relation to motor learning. Using a RBG approach will enable us to collect precise and detailed phenotypic data whilst achieving an informative biological gradient. It would not be feasible to collect such data in the large sample sizes that would be required under a random sampling scheme. By dissecting the role of individual variants associated with schizophrenia in this way, we can begin to unravel the complex genetic mechanisms of psychiatric disorders and pave the way for future development of novel therapeutic approaches.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 1%
Unknown 81 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 17%
Student > Master 13 16%
Researcher 11 13%
Student > Bachelor 10 12%
Student > Doctoral Student 5 6%
Other 9 11%
Unknown 20 24%
Readers by discipline Count As %
Psychology 14 17%
Medicine and Dentistry 13 16%
Neuroscience 7 9%
Biochemistry, Genetics and Molecular Biology 6 7%
Agricultural and Biological Sciences 5 6%
Other 14 17%
Unknown 23 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 24 August 2023.
All research outputs
#3,621,328
of 25,371,288 outputs
Outputs from BMC Medical Genomics
#225
of 2,444 outputs
Outputs of similar age
#48,514
of 294,719 outputs
Outputs of similar age from BMC Medical Genomics
#5
of 50 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,444 research outputs from this source. They receive a mean Attention Score of 4.4. This one has done particularly well, scoring higher than 90% 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 294,719 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 50 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 90% of its contemporaries.