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Circadian patterns of gene expression in the human brain and disruption in major depressive disorder

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, May 2013
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

news
23 news outlets
blogs
6 blogs
twitter
45 X users
facebook
12 Facebook pages
googleplus
8 Google+ users
reddit
3 Redditors

Citations

dimensions_citation
475 Dimensions

Readers on

mendeley
572 Mendeley
citeulike
1 CiteULike
Title
Circadian patterns of gene expression in the human brain and disruption in major depressive disorder
Published in
Proceedings of the National Academy of Sciences of the United States of America, May 2013
DOI 10.1073/pnas.1305814110
Pubmed ID
Authors

Jun Z. Li, Blynn G. Bunney, Fan Meng, Megan H. Hagenauer, David M. Walsh, Marquis P. Vawter, Simon J. Evans, Prabhakara V. Choudary, Preston Cartagena, Jack D. Barchas, Alan F. Schatzberg, Edward G. Jones, Richard M. Myers, Stanley J. Watson, Huda Akil, William E. Bunney

Abstract

A cardinal symptom of major depressive disorder (MDD) is the disruption of circadian patterns. However, to date, there is no direct evidence of circadian clock dysregulation in the brains of patients who have MDD. Circadian rhythmicity of gene expression has been observed in animals and peripheral human tissues, but its presence and variability in the human brain were difficult to characterize. Here, we applied time-of-death analysis to gene expression data from high-quality postmortem brains, examining 24-h cyclic patterns in six cortical and limbic regions of 55 subjects with no history of psychiatric or neurological illnesses ("controls") and 34 patients with MDD. Our dataset covered ~12,000 transcripts in the dorsolateral prefrontal cortex, anterior cingulate cortex, hippocampus, amygdala, nucleus accumbens, and cerebellum. Several hundred transcripts in each region showed 24-h cyclic patterns in controls, and >100 transcripts exhibited consistent rhythmicity and phase synchrony across regions. Among the top-ranked rhythmic genes were the canonical clock genes BMAL1(ARNTL), PER1-2-3, NR1D1(REV-ERBa), DBP, BHLHE40 (DEC1), and BHLHE41(DEC2). The phasing of known circadian genes was consistent with data derived from other diurnal mammals. Cyclic patterns were much weaker in the brains of patients with MDD due to shifted peak timing and potentially disrupted phase relationships between individual circadian genes. This transcriptome-wide analysis of the human brain demonstrates a rhythmic rise and fall of gene expression in regions outside of the suprachiasmatic nucleus in control subjects. The description of its breakdown in MDD suggests potentially important molecular targets for treatment of mood disorders.

X Demographics

X Demographics

The data shown below were collected from the profiles of 45 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 572 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 <1%
Germany 3 <1%
United Kingdom 2 <1%
Canada 2 <1%
Portugal 1 <1%
Russia 1 <1%
Croatia 1 <1%
Unknown 557 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 134 23%
Researcher 78 14%
Student > Bachelor 69 12%
Student > Master 49 9%
Student > Doctoral Student 35 6%
Other 105 18%
Unknown 102 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 132 23%
Neuroscience 84 15%
Medicine and Dentistry 77 13%
Biochemistry, Genetics and Molecular Biology 62 11%
Psychology 36 6%
Other 55 10%
Unknown 126 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 266. 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 28 January 2024.
All research outputs
#138,039
of 26,017,215 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#2,821
of 104,451 outputs
Outputs of similar age
#858
of 209,079 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#19
of 993 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 104,451 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 39.5. This one has done particularly well, scoring higher than 96% 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 209,079 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 98% of its contemporaries.
We're also able to compare this research output to 993 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 98% of its contemporaries.