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Tissue-Specific and Genetic Regulation of Insulin Sensitivity-Associated Transcripts in African Americans

Overview of attention for article published in JCEM, January 2016
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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 (87th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

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6 X users
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3 patents

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Title
Tissue-Specific and Genetic Regulation of Insulin Sensitivity-Associated Transcripts in African Americans
Published in
JCEM, January 2016
DOI 10.1210/jc.2015-3336
Pubmed ID
Authors

Neeraj K Sharma, Satria P Sajuthi, Jeff W Chou, Jorge Calles-Escandon, Jamehl Demons, Samantha Rogers, Lijun Ma, Nicholette D Palmer, David R McWilliams, John Beal, Mary E Comeau, Kristina Cherry, Gregory A Hawkins, Lata Menon, Ethel Kouba, Donna Davis, Marcie Burris, Sara J Byerly, Linda Easter, Donald W Bowden, Barry I Freedman, Carl D Langefeld, Swapan K Das

Abstract

Compared with European Americans, African Americans (AAs) are more insulin-resistant, have a higher insulin secretion response to glucose, and more often develop type 2 diabetes. Molecular processes and/or genetic variations contributing to altered glucose homeostasis in high-risk AAs remain uncharacterized. Adipose and muscle transcript expression profiling and genotyping were performed in 260 AAs to identify genetic regulatory mechanisms associated with insulin sensitivity (SI). We hypothesized that: 1) transcription profiles would reveal tissue-specific modulation of physiologic pathways with SI, and 2) a subset of SI-associated transcripts would be controlled by DNA sequence variants as expression quantitative traits, and these variants in turn would be associated with SI. Clinical research unit-based cross-sectional study. Unrelated non-diabetic AAs. SI measured by FSIGT. The expression levels of 2,212 transcripts in adipose and 145 transcripts in muscle were associated with SI. Genes involved in eIF2, eIF4-p70S6K, and mTOR signaling were modulated with SI in both tissues. Genes involved in leukocyte extravasation signaling showed adipose-specific regulation, and genes involved in oxidative phosphorylation had discordant regulation between tissues. Intersecting cis-eQTL results with data from transcript-SI association analysis identified cis-regulatory SNPs for 363 and 42 SI-associated transcripts in adipose and muscle, respectively. Cis-eSNPs for three SI-associated adipose transcripts, NINJ1, AGA, and CLEC10A were associated with SI. Abrogation of NINJ1 induction in THP1 macrophages modulated expression of genes in chemokine signaling, cell adhesion, and angiogenesis pathways. This study identified multiple pathways associated with SI; particularly discordant tissue-specific regulation of the oxidative phosphorylation pathway, and adipose-specific regulation of transcripts in the leukocyte extravasation signaling pathway that appear to be important in insulin resistance. Identification of SNPs associated with SI and with modulation of expression of SI-associated transcripts, including NINJ1, reveals novel genetic regulatory mechanisms of insulin resistance in AAs.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Unknown 29 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 17%
Student > Bachelor 4 13%
Professor 3 10%
Student > Master 3 10%
Student > Doctoral Student 2 7%
Other 6 20%
Unknown 7 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 27%
Agricultural and Biological Sciences 6 20%
Medicine and Dentistry 2 7%
Immunology and Microbiology 1 3%
Nursing and Health Professions 1 3%
Other 0 0%
Unknown 12 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 03 January 2024.
All research outputs
#2,899,940
of 25,621,213 outputs
Outputs from JCEM
#2,308
of 15,510 outputs
Outputs of similar age
#48,301
of 404,788 outputs
Outputs of similar age from JCEM
#31
of 141 outputs
Altmetric has tracked 25,621,213 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 15,510 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.7. This one has done well, scoring higher than 84% 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 404,788 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 87% of its contemporaries.
We're also able to compare this research output to 141 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.