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Integrative network analysis reveals different pathophysiological mechanisms of insulin resistance among Caucasians and African Americans

Overview of attention for article published in BMC Medical Genomics, February 2015
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  • Good Attention Score compared to outputs of the same age (67th percentile)

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1 tweeter
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1 patent

Citations

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14 Dimensions

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31 Mendeley
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Title
Integrative network analysis reveals different pathophysiological mechanisms of insulin resistance among Caucasians and African Americans
Published in
BMC Medical Genomics, February 2015
DOI 10.1186/s12920-015-0078-0
Pubmed ID
Authors

Swapan Kumar Das, Neeraj Kumar Sharma, Bin Zhang

Abstract

African Americans (AA) have more pronounced insulin resistance and higher insulin secretion than European Americans (Caucasians or CA) when matched for age, gender, and body mass index (BMI). We hypothesize that physiological differences (including insulin sensitivity [SI]) between CAs and AAs can be explained by co-regulated gene networks in tissues involved in glucose homeostasis. We performed integrative gene network analyses of transcriptomic data in subcutaneous adipose tissue of 99 CA and 37 AA subjects metabolically characterized as non-diabetic, with a range of SI and BMI values. Transcripts negatively correlated with SI in only the CA or AA subjects were enriched for inflammatory response genes and integrin-signaling genes, respectively. A sub-network (module) with TYROBP as a hub enriched for genes involved in inflammatory response (corrected p = 1.7E-26) was negatively correlated with SI (r = -0.426, p = 4.95E-04) in CA subjects. SI was positively correlated with transcript modules enriched for mitochondrial metabolism in both groups. Several SI-associated co-expressed modules were enriched for genes differentially expressed between groups. Two modules involved in immune response to viral infections and function of adherens junction, are significantly correlated with SI only in CAs. Five modules involved in drug/intracellular transport and oxidoreductase activity, among other activities, are correlated with SI only in AAs. Furthermore, we identified driver genes of these race-specific SI-associated modules. SI-associated transcriptional networks that were deranged predominantly in one ethnic group may explain the distinctive physiological features of glucose homeostasis among AA subjects.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 23%
Student > Bachelor 5 16%
Student > Master 5 16%
Researcher 2 6%
Professor > Associate Professor 2 6%
Other 4 13%
Unknown 6 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 26%
Biochemistry, Genetics and Molecular Biology 7 23%
Medicine and Dentistry 4 13%
Pharmacology, Toxicology and Pharmaceutical Science 2 6%
Unspecified 1 3%
Other 3 10%
Unknown 6 19%

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 December 2018.
All research outputs
#5,934,431
of 18,908,107 outputs
Outputs from BMC Medical Genomics
#289
of 1,003 outputs
Outputs of similar age
#77,265
of 243,657 outputs
Outputs of similar age from BMC Medical Genomics
#1
of 3 outputs
Altmetric has tracked 18,908,107 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 1,003 research outputs from this source. They receive a mean Attention Score of 4.6. This one has gotten more attention than average, scoring higher than 70% 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 243,657 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 67% of its contemporaries.
We're also able to compare this research output to 3 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