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Metabolomic profiles as reliable biomarkers of dietary composition 1–3

Overview of attention for article published in American Journal of Clinical Nutrition, January 2017
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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 (95th percentile)
  • Good Attention Score compared to outputs of the same age and source (67th percentile)

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2 news outlets
blogs
1 blog
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49 X users
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4 Facebook pages

Citations

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80 Dimensions

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232 Mendeley
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1 CiteULike
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Title
Metabolomic profiles as reliable biomarkers of dietary composition 1–3
Published in
American Journal of Clinical Nutrition, January 2017
DOI 10.3945/ajcn.116.144428
Pubmed ID
Authors

Tõnu Esko, Joel N Hirschhorn, Henry A Feldman, Yu-Han H Hsu, Amy A Deik, Clary B Clish, Cara B Ebbeling, David S Ludwig

Abstract

Clinical nutrition research often lacks robust markers of compliance, complicating the interpretation of clinical trials and observational studies of free-living subjects. We aimed to examine metabolomics profiles in response to 3 diets that differed widely in macronutrient composition during a controlled feeding protocol. Twenty-one adults with a high body mass index (in kg/m(2); mean ± SD: 34.4 ± 4.9) were given hypocaloric diets to promote weight loss corresponding to 10-15% of initial body weight. They were then studied during weight stability while consuming 3 test diets, each for a 4-wk period according to a crossover design: low fat (60% carbohydrate, 20% fat, 20% protein), low glycemic index (40% carbohydrate, 40% fat, 20% protein), or very-low carbohydrate (10% carbohydrate, 60% fat, 30% protein). Plasma samples were obtained at baseline and at the end of each 4-wk period in the fasting state for metabolomics analysis by using liquid chromatography-tandem mass spectrometry. Statistical analyses included adjustment for multiple comparisons. Of 333 metabolites, we identified 152 whose concentrations differed for ≥1 diet compared with the others, including diacylglycerols and triacylglycerols, branched-chain amino acids, and markers reflecting metabolic status. Analysis of groups of related metabolites, with the use of either principal components or pathways, revealed coordinated metabolic changes affected by dietary composition, including pathways related to amino acid metabolism. We constructed a classifier using the metabolites that differed between diets and were able to correctly identify the test diet from metabolite profiles in 60 of 63 cases (>95% accuracy). Analyses also suggest differential effects by diet on numerous cardiometabolic disease risk factors. Metabolomic profiling may be used to assess compliance during clinical nutrition trials and the validity of dietary assessment in observational studies. In addition, this methodology may help elucidate mechanistic pathways linking diet to chronic disease risk. This trial was registered at clinicaltrials.gov as NCT00315354.

X Demographics

X Demographics

The data shown below were collected from the profiles of 49 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 232 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 <1%
Spain 1 <1%
Switzerland 1 <1%
Unknown 228 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 44 19%
Student > Master 39 17%
Researcher 37 16%
Student > Bachelor 24 10%
Student > Doctoral Student 18 8%
Other 26 11%
Unknown 44 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 41 18%
Medicine and Dentistry 33 14%
Biochemistry, Genetics and Molecular Biology 29 13%
Nursing and Health Professions 25 11%
Chemistry 9 4%
Other 29 13%
Unknown 66 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 51. 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 31 December 2021.
All research outputs
#830,940
of 25,377,790 outputs
Outputs from American Journal of Clinical Nutrition
#1,703
of 12,615 outputs
Outputs of similar age
#17,632
of 423,613 outputs
Outputs of similar age from American Journal of Clinical Nutrition
#25
of 76 outputs
Altmetric has tracked 25,377,790 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,615 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 38.2. This one has done well, scoring higher than 86% 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 423,613 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 76 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.