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DNA hypermethylation of CD3+ T cells from cord blood of infants exposed to intrauterine growth restriction

Overview of attention for article published in Diabetologia, May 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

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Title
DNA hypermethylation of CD3+ T cells from cord blood of infants exposed to intrauterine growth restriction
Published in
Diabetologia, May 2016
DOI 10.1007/s00125-016-3983-7
Pubmed ID
Authors

Lyda Williams, Yoshinori Seki, Fabien Delahaye, Alex Cheng, Mamta Fuloria, Francine Hughes Einstein, Maureen J. Charron

Abstract

Intrauterine growth restriction (IUGR) is associated with increased susceptibility to obesity, metabolic syndrome and type 2 diabetes. Although the mechanisms underlying the developmental origins of metabolic disease are poorly understood, evidence suggests that epigenomic alterations play a critical role. We sought to identify changes in DNA methylation patterns that are associated with IUGR in CD3(+) T cells purified from umbilical cord blood obtained from male newborns who were appropriate for gestational age (AGA) or who had been exposed to IUGR. CD3(+) T cells were isolated from cord blood obtained from IUGR and AGA infants. The genome-wide methylation profile in eight AGA and seven IUGR samples was determined using the HELP tagging assay. Validation analysis using targeted bisulfite sequencing and bisulfite massARRAY was performed on the original cohort as well as biological replicates consisting of two AGA and four IUGR infants. The Segway algorithm was used to identify methylation changes within regulatory regions of the genome. A global shift towards hypermethylation in IUGR was seen compared with AGA (89.8% of 4,425 differentially methylated loci), targeted to regulatory regions of the genome, specifically promoters and enhancers. Pathway analysis identified dysregulation of pathways involved in metabolic disease (type 2 diabetes mellitus, insulin signalling, mitogen-activated protein kinase signalling) and T cell development, regulation and activation (T cell receptor signalling), as well as transcription factors (TCF3, LEF1 and NFATC) that regulate T cells. Furthermore, bump-hunting analysis revealed differentially methylated regions in PRDM16 and HLA-DPB1, genes important for adipose tissue differentiation, stem cell maintenance and function and T cell activation. Our findings suggest that the alterations in methylation patterns observed in IUGR CD3(+) T cells may have functional consequences in targeted genes, regulatory regions and transcription factors. These may serve as biomarkers to identify those at 'high risk' for diminished attainment of full health potential who can benefit from early interventions. HELP tagging data: Gene Expression Omnibus database (GSE77268), scheduled to be released on 25 January 2019.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Korea, Republic of 1 1%
Unknown 69 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 21%
Student > Bachelor 11 16%
Researcher 6 9%
Student > Doctoral Student 5 7%
Student > Master 5 7%
Other 11 16%
Unknown 17 24%
Readers by discipline Count As %
Medicine and Dentistry 22 31%
Biochemistry, Genetics and Molecular Biology 11 16%
Nursing and Health Professions 6 9%
Agricultural and Biological Sciences 3 4%
Pharmacology, Toxicology and Pharmaceutical Science 1 1%
Other 6 9%
Unknown 21 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 09 January 2020.
All research outputs
#5,666,453
of 22,870,727 outputs
Outputs from Diabetologia
#2,397
of 5,037 outputs
Outputs of similar age
#87,539
of 326,819 outputs
Outputs of similar age from Diabetologia
#41
of 94 outputs
Altmetric has tracked 22,870,727 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,037 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.7. This one has gotten more attention than average, scoring higher than 52% 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 326,819 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 73% of its contemporaries.
We're also able to compare this research output to 94 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 56% of its contemporaries.