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Many obesity-associated SNPs strongly associate with DNA methylation changes at proximal promoters and enhancers

Overview of attention for article published in Genome Medicine, October 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
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Title
Many obesity-associated SNPs strongly associate with DNA methylation changes at proximal promoters and enhancers
Published in
Genome Medicine, October 2015
DOI 10.1186/s13073-015-0225-4
Pubmed ID
Authors

Sarah Voisin, Markus Sällman Almén, Galina Y. Zheleznyakova, Lina Lundberg, Sanaz Zarei, Sandra Castillo, Fia Ence Eriksson, Emil K. Nilsson, Matthias Blüher, Yvonne Böttcher, Peter Kovacs, Janis Klovins, Mathias Rask-Andersen, Helgi B. Schiöth

Abstract

The mechanisms by which genetic variants, such as single nucleotide polymorphisms (SNPs), identified in genome-wide association studies act to influence body mass remain unknown for most of these SNPs, which continue to puzzle the scientific community. Recent evidence points to the epigenetic and chromatin states of the genome as having important roles. We genotyped 355 healthy young individuals for 52 known obesity-associated SNPs and obtained DNA methylation levels in their blood using the Illumina 450 K BeadChip. Associations between alleles and methylation at proximal cytosine residues were tested using a linear model adjusted for age, sex, weight category, and a proxy for blood cell type counts. For replication in other tissues, we used two open-access datasets (skin fibroblasts, n = 62; four brain regions, n = 121-133) and an additional dataset in subcutaneous and visceral fat (n = 149). We found that alleles at 28 of these obesity-associated SNPs associate with methylation levels at 107 proximal CpG sites. Out of 107 CpG sites, 38 are located in gene promoters, including genes strongly implicated in obesity (MIR148A, BDNF, PTPMT1, NR1H3, MGAT1, SCGB3A1, HOXC12, PMAIP1, PSIP1, RPS10-NUDT3, RPS10, SKOR1, MAP2K5, SIX5, AGRN, IMMP1L, ELP4, ITIH4, SEMA3G, POMC, ADCY3, SSPN, LGR4, TUFM, MIR4721, SULT1A1, SULT1A2, APOBR, CLN3, SPNS1, SH2B1, ATXN2L, and IL27). Interestingly, the associated SNPs are in known eQTLs for some of these genes. We also found that the 107 CpGs are enriched in enhancers in peripheral blood mononuclear cells. Finally, our results indicate that some of these associations are not blood-specific as we successfully replicated four associations in skin fibroblasts. Our results strongly suggest that many obesity-associated SNPs are associated with proximal gene regulation, which was reflected by association of obesity risk allele genotypes with differential DNA methylation. This study highlights the importance of DNA methylation and other chromatin marks as a way to understand the molecular basis of genetic variants associated with human diseases and traits.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 167 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 1%
Portugal 1 <1%
Uruguay 1 <1%
Unknown 163 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 39 23%
Researcher 28 17%
Student > Bachelor 20 12%
Student > Master 14 8%
Student > Doctoral Student 11 7%
Other 35 21%
Unknown 20 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 44 26%
Biochemistry, Genetics and Molecular Biology 40 24%
Medicine and Dentistry 28 17%
Psychology 4 2%
Neuroscience 4 2%
Other 18 11%
Unknown 29 17%
Attention Score in Context

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 16 October 2015.
All research outputs
#4,066,045
of 22,829,683 outputs
Outputs from Genome Medicine
#822
of 1,442 outputs
Outputs of similar age
#54,699
of 278,190 outputs
Outputs of similar age from Genome Medicine
#18
of 31 outputs
Altmetric has tracked 22,829,683 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,442 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.6. This one is in the 42nd percentile – i.e., 42% of its peers scored the same or lower than it.
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 278,190 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 31 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.