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

Overview of attention for article published in The Journal of Clinical Endocrinology & Metabolism, April 2016
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  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

Mentioned by

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9 tweeters

Citations

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12 Dimensions

Readers on

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17 Mendeley
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Title
Tissue-Specific and Genetic Regulation of Insulin Sensitivity-Associated Transcripts in African Americans
Published in
The Journal of Clinical Endocrinology & Metabolism, April 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.

Twitter Demographics

The data shown below were collected from the profiles of 9 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 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 6%
Unknown 16 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 24%
Student > Bachelor 3 18%
Professor 2 12%
Student > Ph. D. Student 2 12%
Student > Master 2 12%
Other 2 12%
Unknown 2 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 35%
Biochemistry, Genetics and Molecular Biology 3 18%
Medicine and Dentistry 2 12%
Immunology and Microbiology 1 6%
Nursing and Health Professions 1 6%
Other 0 0%
Unknown 4 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 27 January 2016.
All research outputs
#4,691,709
of 15,484,740 outputs
Outputs from The Journal of Clinical Endocrinology & Metabolism
#3,950
of 12,043 outputs
Outputs of similar age
#100,465
of 342,168 outputs
Outputs of similar age from The Journal of Clinical Endocrinology & Metabolism
#44
of 127 outputs
Altmetric has tracked 15,484,740 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 12,043 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.8. This one has gotten more attention than average, scoring higher than 66% 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 342,168 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 69% of its contemporaries.
We're also able to compare this research output to 127 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 62% of its contemporaries.