| Title |
LC-QTOF/MS metabolomic profiles in human plasma after a 5-week high dietary fiber intake
|
|---|---|
| Published in |
Analytical & Bioanalytical Chemistry, March 2013
|
| DOI | 10.1007/s00216-013-6874-5 |
| Pubmed ID | |
| Authors |
Anna Johansson-Persson, Thaer Barri, Matilda Ulmius, Gunilla Önning, Lars Ove Dragsted |
| Abstract |
The objective was to investigate the alterations of plasma metabolome profiles to identify exposure and effect markers of dietary fiber intake. Subjects (n = 25) aged 58.6 (1.1) years (mean and SD) with a body mass index of 26.6 (0.5) kg/m(2) were given a high fiber (HF) and a low fiber (LF) diet, in a 5-week randomized controlled crossover intervention. The HF diet consisted of oat bran, rye bran, and sugar beet fiber incorporated into test food products, whereas the LF diet was made of equivalent food products to the HF diet, but without adding fibers. Blood plasma samples were collected at the start and end of each intervention period and analyzed by LC-QTOF/MS. In total, 6 features in positive mode and 14 features in negative mode were significantly different between the HF and the LF diet (p < 0.01, q < 0.05). Two markers, 2,6-dihydroxybenzoic acid and 2-aminophenol sulfate, were increased after HF diet, along with a tentatively identified saponin derived from oat avenacosides. The untargeted metabolomics approach enabled the identification of two new markers of dietary fiber intake in human plasma. Further studies will be needed to verify if these markers could serve as compliance markers of fiber intake. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 93 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 2 | 2% |
| Germany | 1 | 1% |
| Denmark | 1 | 1% |
| Belgium | 1 | 1% |
| Japan | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 86 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 23 | 25% |
| Student > Ph. D. Student | 18 | 19% |
| Student > Master | 9 | 10% |
| Student > Doctoral Student | 8 | 9% |
| Student > Bachelor | 6 | 6% |
| Other | 10 | 11% |
| Unknown | 19 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 25 | 27% |
| Medicine and Dentistry | 11 | 12% |
| Chemistry | 10 | 11% |
| Biochemistry, Genetics and Molecular Biology | 9 | 10% |
| Nursing and Health Professions | 6 | 6% |
| Other | 11 | 12% |
| Unknown | 21 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 17 May 2013.
All research outputs
#17,286,379
of 25,374,647 outputs
Outputs from Analytical & Bioanalytical Chemistry
#5,669
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Outputs of similar age
#135,110
of 210,252 outputs
Outputs of similar age from Analytical & Bioanalytical Chemistry
#42
of 69 outputs
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