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Associations between body mass index-related genetic variants and adult body composition: The Fenland cohort study

Overview of attention for article published in International Journal of Obesity, January 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • Good Attention Score compared to outputs of the same age and source (65th percentile)

Mentioned by

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14 tweeters
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1 Facebook page

Citations

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4 Dimensions

Readers on

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27 Mendeley
Title
Associations between body mass index-related genetic variants and adult body composition: The Fenland cohort study
Published in
International Journal of Obesity, January 2017
DOI 10.1038/ijo.2017.11
Pubmed ID
Authors

E A D Clifton, F R Day, E De Lucia Rolfe, N G Forouhi, S Brage, S J Griffin, N J Wareham, K K Ong

Abstract

Body mass index (BMI) is a surrogate measure of adiposity but does not distinguish fat from lean or bone mass. The genetic determinants of BMI are thought to predominantly influence adiposity but this has not been confirmed. Here we characterise the association between BMI-related genetic variants and body composition in adults. Among 9667 adults aged 29-64 years from the Fenland study, a genetic risk score for BMI (BMI-GRS) was calculated for each individual as the weighted sum of BMI-increasing alleles across 96 reported BMI-related variants. Associations between the BMI-GRS and body composition, estimated by DXA scans, were examined using age-adjusted linear regression models, separately by sex. The BMI-GRS was positively associated with all fat, lean and bone variables. Across body regions, associations of the greatest magnitude were observed for adiposity variables e.g. for each standard deviation (s.d.) increase in BMI-GRS predicted BMI, we observed a 0.90 s.d. (95% CI: 0.71, 1.09) increase in total fat mass for men (P=3.75 × 10(-21)) and a 0.96 s.d. (95% CI: 0.77, 1.16) increase for women (P=6.12 × 10(-22)). Associations of intermediate magnitude were observed with lean variables e.g. total lean mass: men: 0.68 s.d. (95% CI: 0.49, 0.86) (P=1.91 × 10(-12)); women: 0.85 s.d. (95% CI: 0.65, 1.04) (P=2.66 × 10(-17)) and of a lower magnitude with bone variables e.g. total bone mass: men: 0.39 s.d. (95% CI: 0.20, 0.58) (P=5.69 × 10(-5)); women: 0.45 s.d. (95% CI: 0.26, 0.65) (P=3.96 × 10(-6)). Nominally significant associations with BMI were observed for 28 SNPs. All 28 were positively associated with fat mass and 13 showed adipose-specific effects. In adults, genetic susceptibility to elevated BMI influences adiposity more than lean or bone mass. This mirrors the association between BMI and body composition. The BMI-GRS can be used to model the effects of measured BMI and adiposity on health and other outcomes.International Journal of Obesity accepted article preview online, 18 January 2017. doi:10.1038/ijo.2017.11.

Twitter Demographics

The data shown below were collected from the profiles of 14 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 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 26%
Unspecified 5 19%
Student > Bachelor 5 19%
Student > Postgraduate 3 11%
Other 2 7%
Other 5 19%
Readers by discipline Count As %
Medicine and Dentistry 7 26%
Unspecified 7 26%
Biochemistry, Genetics and Molecular Biology 6 22%
Agricultural and Biological Sciences 2 7%
Psychology 1 4%
Other 4 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 15 March 2017.
All research outputs
#1,669,244
of 11,837,326 outputs
Outputs from International Journal of Obesity
#1,111
of 3,011 outputs
Outputs of similar age
#64,666
of 328,123 outputs
Outputs of similar age from International Journal of Obesity
#22
of 64 outputs
Altmetric has tracked 11,837,326 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,011 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.2. This one has gotten more attention than average, scoring higher than 63% 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 328,123 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 64 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 65% of its contemporaries.