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Systems Nutrigenomics Reveals Brain Gene Networks Linking Metabolic and Brain Disorders

Overview of attention for article published in EBioMedicine, April 2016
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580

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#30 of 4,056)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
56 news outlets
blogs
11 blogs
policy
1 policy source
twitter
94 X users
facebook
50 Facebook pages
googleplus
21 Google+ users
reddit
3 Redditors

Citations

dimensions_citation
63 Dimensions

Readers on

mendeley
231 Mendeley
citeulike
1 CiteULike
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Title
Systems Nutrigenomics Reveals Brain Gene Networks Linking Metabolic and Brain Disorders
Published in
EBioMedicine, April 2016
DOI 10.1016/j.ebiom.2016.04.008
Pubmed ID
Authors

Qingying Meng, Zhe Ying, Emily Noble, Yuqi Zhao, Rahul Agrawal, Andrew Mikhail, Yumei Zhuang, Ethika Tyagi, Qing Zhang, Jae-Hyung Lee, Marco Morselli, Luz Orozco, Weilong Guo, Tina M. Kilts, Jun Zhu, Bin Zhang, Matteo Pellegrini, Xinshu Xiao, Marian F. Young, Fernando Gomez-Pinilla, Xia Yang

Abstract

Nutrition plays a significant role in the increasing prevalence of metabolic and brain disorders. Here we employ systems nutrigenomics to scrutinize the genomic bases of nutrient-host interaction underlying disease predisposition or therapeutic potential. We conducted transcriptome and epigenome sequencing of hypothalamus (metabolic control) and hippocampus (cognitive processing) from a rodent model of fructose consumption, and identified significant reprogramming of DNA methylation, transcript abundance, alternative splicing, and gene networks governing cell metabolism, cell communication, inflammation, and neuronal signaling. These signals converged with genetic causal risks of metabolic, neurological, and psychiatric disorders revealed in humans. Gene network modeling uncovered the extracellular matrix genes Bgn and Fmod as main orchestrators of the effects of fructose, as validated using two knockout mouse models. We further demonstrate that an omega-3 fatty acid, DHA, reverses the genomic and network perturbations elicited by fructose, providing molecular support for nutritional interventions to counteract diet-induced metabolic and brain disorders. Our integrative approach complementing rodent and human studies supports the applicability of nutrigenomics principles to predict disease susceptibility and to guide personalized medicine.

X Demographics

X Demographics

The data shown below were collected from the profiles of 94 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 231 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 1%
United Kingdom 1 <1%
Mexico 1 <1%
Singapore 1 <1%
Unknown 225 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 37 16%
Researcher 34 15%
Student > Master 27 12%
Student > Bachelor 26 11%
Other 17 7%
Other 42 18%
Unknown 48 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 39 17%
Medicine and Dentistry 37 16%
Agricultural and Biological Sciences 34 15%
Neuroscience 22 10%
Nursing and Health Professions 15 6%
Other 31 13%
Unknown 53 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 580. 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 15 May 2023.
All research outputs
#40,868
of 25,654,806 outputs
Outputs from EBioMedicine
#30
of 4,056 outputs
Outputs of similar age
#736
of 316,469 outputs
Outputs of similar age from EBioMedicine
#1
of 109 outputs
Altmetric has tracked 25,654,806 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 4,056 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 31.6. This one has done particularly well, scoring higher than 99% 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 316,469 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 99% of its contemporaries.
We're also able to compare this research output to 109 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 99% of its contemporaries.