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Attention Score in Context
| Title |
Plasma metabolomic profiles in association with type 2 diabetes risk and prevalence in Chinese adults
|
|---|---|
| Published in |
Metabolomics, November 2015
|
| DOI | 10.1007/s11306-015-0890-8 |
| Pubmed ID | |
| Authors |
Danxia Yu, Steven C. Moore, Charles E. Matthews, Yong-Bing Xiang, Xianglan Zhang, Yu-Tang Gao, Wei Zheng, Xiao-Ou Shu |
| Abstract |
Metabolomic studies have identified several metabolites associated with type 2 diabetes (T2D) in populations of European ancestry. East Asians, a population of particular susceptibility to T2D, were generally not included in previous studies. We examined the associations of plasma metabolites with risk and prevalence of T2D in 976 Chinese men and women (40-74 years of age) who were participants of two prospective cohort studies and had no cardiovascular disease or cancer at baseline. Sixty-eight prevalent and 73 incident T2D cases were included. Non-targeted metabolomics was conducted that detected 689 metabolites with known identities and 690 unknown metabolites. Multivariable logistic and Cox regressions were used to evaluate the associations of standardized metabolites with diabetes risk and prevalence. We identified 36 known metabolites and 10 unknown metabolites associated with prevalent and/or incident T2D at false discovery rate <0.05. The known metabolites are involved in metabolic pathways of glycolysis/gluconeogenesis, branched-chain amino acids, other amino acids, fatty acids, glycerophospholipids, androgen, and bradykinin. Six metabolites showed independent associations with incident T2D: 1,5-anhydroglucitol, mannose, valine, 3-methoxytyrosine, docosapentaenoate (22:5n3), and bradykinin-hydroxy-pro(3). Each standard deviation increase in these metabolites was associated with a 40-150 % change in risk of developing diabetes (30-80 % after further adjustment for glucose). Risk prediction was significantly improved by adding these metabolites in addition to known T2D risk factors, including central obesity and glucose. These findings suggest that hexoses, branched-chain amino acids, and yet to be validated novel plasma metabolites may improve risk prediction and mechanistic understanding of T2D in Chinese populations. |
Mendeley readers
The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 3% |
| Spain | 1 | 1% |
| Unknown | 73 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 21% |
| Researcher | 15 | 20% |
| Student > Master | 9 | 12% |
| Other | 5 | 7% |
| Professor | 4 | 5% |
| Other | 9 | 12% |
| Unknown | 18 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 16 | 21% |
| Agricultural and Biological Sciences | 12 | 16% |
| Biochemistry, Genetics and Molecular Biology | 10 | 13% |
| Chemistry | 4 | 5% |
| Unspecified | 2 | 3% |
| Other | 10 | 13% |
| Unknown | 22 | 29% |
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 31 May 2018.
All research outputs
#7,540,801
of 23,005,189 outputs
Outputs from Metabolomics
#470
of 1,299 outputs
Outputs of similar age
#97,395
of 286,459 outputs
Outputs of similar age from Metabolomics
#9
of 16 outputs
Altmetric has tracked 23,005,189 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,299 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 57% 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 286,459 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 56% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.