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The impact of micronutrient status on health: correlation network analysis to understand the role of micronutrients in metabolic-inflammatory processes regulating homeostasis and phenotypic…

Overview of attention for article published in Genes & Nutrition, February 2017
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  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

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Title
The impact of micronutrient status on health: correlation network analysis to understand the role of micronutrients in metabolic-inflammatory processes regulating homeostasis and phenotypic flexibility
Published in
Genes & Nutrition, February 2017
DOI 10.1186/s12263-017-0553-7
Pubmed ID
Authors

Tim J. van den Broek, Bas H. A. Kremer, Marisa Marcondes Rezende, Femke P. M. Hoevenaars, Peter Weber, Ulrich Hoeller, Ben van Ommen, Suzan Wopereis

Abstract

Vitamins and carotenoids are key micronutrients facilitating the maintenance of health, as evidenced by the increased risk of disease with low intake. Optimal phenotypic flexibility, i.e., the ability to respond to a physiological challenge, is an essential indicator of health status. Therefore, health can be measured by applying a challenge test and monitoring the response of relevant phenotypic processes. In this study, we assessed the correlation of three fat-soluble vitamins, (i.e., vitamin A or retinol, vitamin D3, two homologues of vitamin E) and four carotenoids (i.e., α-carotene, β-carotene, β-cryptoxanthin, and lycopene), with characteristics of metabolic and inflammatory parameters at baseline and in response to a nutritional challenge test (NCT) in a group of 36 overweight and obese male subjects, using proteomics and metabolomics platforms. The phenotypic flexibility concept implies that health can be measured by the ability to adapt to a NCT, which may offer a more sensitive way to assess changes in health status of healthy subjects. Correlation analyses of results after overnight fasting revealed a rather evenly distributed network in a number of relatively strong correlations per micronutrient, with minor overlap between correlation profiles of each compound. Correlation analyses of challenge response profiles for metabolite and protein parameters with micronutrient status revealed a network that is more skewed towards α-carotene and γ-tocopherol suggesting a more prominent role for these micronutrients in the maintenance of phenotypic flexibility. Comparison of the networks revealed that there is merely overlap of two parameters (inositol and oleic acid (C18:1)) affirming that there is a specific biomarker response profile upon NCT. Our study shows that applying the challenge test concept is able to reveal previously unidentified correlations between specific micronutrients and health-related processes, with potential relevance for maintenance of health that were not observed by correlating homeostatic measurements. This approach will contribute to insights on the influence of micronutrients on health and help to create efficient micronutrient intervention programs.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 1%
Unknown 84 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 22%
Student > Ph. D. Student 15 18%
Student > Master 11 13%
Student > Bachelor 10 12%
Student > Doctoral Student 3 4%
Other 5 6%
Unknown 22 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 14%
Biochemistry, Genetics and Molecular Biology 11 13%
Nursing and Health Professions 10 12%
Medicine and Dentistry 8 9%
Business, Management and Accounting 4 5%
Other 12 14%
Unknown 28 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 14 January 2020.
All research outputs
#13,187,574
of 22,953,506 outputs
Outputs from Genes & Nutrition
#177
of 388 outputs
Outputs of similar age
#202,853
of 420,438 outputs
Outputs of similar age from Genes & Nutrition
#3
of 9 outputs
Altmetric has tracked 22,953,506 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 388 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. 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 420,438 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 51% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.