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A metabolomic study of biomarkers of meat and fish intake

Overview of attention for article published in American Journal of Clinical Nutrition, January 2017
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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9 tweeters
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2 Facebook pages

Citations

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47 Dimensions

Readers on

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95 Mendeley
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Title
A metabolomic study of biomarkers of meat and fish intake
Published in
American Journal of Clinical Nutrition, January 2017
DOI 10.3945/ajcn.116.146639
Pubmed ID
Authors

William Cheung, Pekka Keski-Rahkonen, Nada Assi, Pietro Ferrari, Heinz Freisling, Sabina Rinaldi, Nadia Slimani, Raul Zamora-Ros, Milena Rundle, Gary Frost, Helena Gibbons, Eibhlin Carr, Lorraine Brennan, Amanda J Cross, Valeria Pala, Salvatore Panico, Carlotta Sacerdote, Domenico Palli, Rosario Tumino, Tilman Kühn, Rudolf Kaaks, Heiner Boeing, Anna Floegel, Francesca Mancini, Marie-Christine Boutron-Ruault, Laura Baglietto, Antonia Trichopoulou, Androniki Naska, Philippos Orfanos, Augustin Scalbert

Abstract

Meat and fish intakes have been associated with various chronic diseases. The use of specific biomarkers may help to assess meat and fish intake and improve subject classification according to the amount and type of meat or fish consumed. A metabolomic approach was applied to search for biomarkers of meat and fish intake in a dietary intervention study and in free-living subjects from the European Prospective Investigation into Cancer and Nutrition (EPIC) study. In the dietary intervention study, 4 groups of 10 subjects consumed increasing quantities of chicken, red meat, processed meat, and fish over 3 successive weeks. Twenty-four-hour urine samples were collected during each period and analyzed by high-resolution liquid chromatography-mass spectrometry. Signals characteristic of meat or fish intake were replicated in 50 EPIC subjects for whom a 24-h urine sample and 24-h dietary recall were available and who were selected for their exclusive intake or no intake of any of the 4 same foods. A total of 249 mass spectrometric features showed a positive dose-dependent response to meat or fish intake in the intervention study. Eighteen of these features best predicted intake of the 4 food groups in the EPIC urine samples on the basis of partial receiver operator curve analyses with permutation testing (areas under the curve ranging between 0.61 and 1.0). Of these signals, 8 metabolites were identified. Anserine was found to be specific for chicken intake, whereas trimethylamine-N-oxide showed good specificity for fish. Carnosine and 3 acylcarnitines (acetylcarnitine, propionylcarnitine, and 2-methylbutyrylcarnitine) appeared to be more generic indicators of meat and meat and fish intake, respectively. The meat and fish biomarkers identified in this work may be used to study associations between meat and fish intake and disease risk in epidemiologic studies. This trial was registered at clinicaltrials.gov as NCT01684917.

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 95 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 1%
France 1 1%
New Zealand 1 1%
Unknown 92 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 23 24%
Student > Ph. D. Student 20 21%
Unspecified 16 17%
Student > Master 10 11%
Student > Bachelor 6 6%
Other 20 21%
Readers by discipline Count As %
Unspecified 26 27%
Medicine and Dentistry 20 21%
Agricultural and Biological Sciences 16 17%
Chemistry 9 9%
Nursing and Health Professions 7 7%
Other 17 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 23 July 2019.
All research outputs
#3,412,507
of 13,652,000 outputs
Outputs from American Journal of Clinical Nutrition
#4,451
of 9,639 outputs
Outputs of similar age
#96,806
of 346,620 outputs
Outputs of similar age from American Journal of Clinical Nutrition
#61
of 91 outputs
Altmetric has tracked 13,652,000 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 9,639 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.7. This one has gotten more attention than average, scoring higher than 53% 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 346,620 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 91 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.