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Meta-analysis of human genome-microbiome association studies: the MiBioGen consortium initiative

Overview of attention for article published in Microbiome, June 2018
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)

Citations

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62 Dimensions

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235 Mendeley
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Title
Meta-analysis of human genome-microbiome association studies: the MiBioGen consortium initiative
Published in
Microbiome, June 2018
DOI 10.1186/s40168-018-0479-3
Pubmed ID
Authors

Jun Wang, Alexander Kurilshikov, Djawad Radjabzadeh, Williams Turpin, Kenneth Croitoru, Marc Jan Bonder, Matthew A. Jackson, Carolina Medina-Gomez, Fabian Frost, Georg Homuth, Malte Rühlemann, David Hughes, Han-na Kim, Tim D. Spector, Jordana T. Bell, Claire J. Steves, Nicolas Timpson, Andre Franke, Cisca Wijmenga, Katie Meyer, Tim Kacprowski, Lude Franke, Andrew D. Paterson, Jeroen Raes, Robert Kraaij, Alexandra Zhernakova

Abstract

In recent years, human microbiota, especially gut microbiota, have emerged as an important yet complex trait influencing human metabolism, immunology, and diseases. Many studies are investigating the forces underlying the observed variation, including the human genetic variants that shape human microbiota. Several preliminary genome-wide association studies (GWAS) have been completed, but more are necessary to achieve a fuller picture. Here, we announce the MiBioGen consortium initiative, which has assembled 18 population-level cohorts and some 19,000 participants. Its aim is to generate new knowledge for the rapidly developing field of microbiota research. Each cohort has surveyed the gut microbiome via 16S rRNA sequencing and genotyped their participants with full-genome SNP arrays. We have standardized the analytical pipelines for both the microbiota phenotypes and genotypes, and all the data have been processed using identical approaches. Our analysis of microbiome composition shows that we can reduce the potential artifacts introduced by technical differences in generating microbiota data. We are now in the process of benchmarking the association tests and performing meta-analyses of genome-wide associations. All pipeline and summary statistics results will be shared using public data repositories. We present the largest consortium to date devoted to microbiota-GWAS. We have adapted our analytical pipelines to suit multi-cohort analyses and expect to gain insight into host-microbiota cross-talk at the genome-wide level. And, as an open consortium, we invite more cohorts to join us (by contacting one of the corresponding authors) and to follow the analytical pipeline we have developed.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 235 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 235 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 59 25%
Student > Ph. D. Student 42 18%
Student > Master 29 12%
Student > Bachelor 18 8%
Student > Doctoral Student 11 5%
Other 35 15%
Unknown 41 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 64 27%
Agricultural and Biological Sciences 44 19%
Immunology and Microbiology 19 8%
Medicine and Dentistry 17 7%
Chemistry 6 3%
Other 24 10%
Unknown 61 26%

Attention Score in Context

This research output has an Altmetric Attention Score of 90. 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 2021.
All research outputs
#360,324
of 21,436,792 outputs
Outputs from Microbiome
#92
of 1,293 outputs
Outputs of similar age
#9,254
of 298,844 outputs
Outputs of similar age from Microbiome
#1
of 1 outputs
Altmetric has tracked 21,436,792 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,293 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 40.7. This one has done particularly well, scoring higher than 92% 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 298,844 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them