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Isogenic Cellular Systems Model the Impact of Genetic Risk Variants in the Pathogenesis of Type 1 Diabetes

Overview of attention for article published in Frontiers in endocrinology, October 2017
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  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

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Title
Isogenic Cellular Systems Model the Impact of Genetic Risk Variants in the Pathogenesis of Type 1 Diabetes
Published in
Frontiers in endocrinology, October 2017
DOI 10.3389/fendo.2017.00276
Pubmed ID
Authors

Mark A. Wallet, Katherine E. Santostefano, Naohiro Terada, Todd M. Brusko

Abstract

At least 57 independent loci within the human genome confer varying degrees of risk for the development of type 1 diabetes (T1D). The majority of these variants are thought to contribute to overall genetic risk by modulating host innate and adaptive immune responses, ultimately resulting in a loss of immunological tolerance to β cell antigens. Early efforts to link specific risk variants with functional alterations in host immune responses have employed animal models or genotype-selected individuals from clinical bioresource banks. While some notable genotype:phenotype associations have been described, there remains an urgent need to accelerate the discovery of causal variants and elucidate the molecular mechanisms by which susceptible alleles alter immune functions. One significant limitation has been the inability to study human T1D risk loci on an isogenic background. The advent of induced pluripotent stem cells (iPSCs) and genome-editing technologies have made it possible to address a number of these outstanding questions. Specifically, the ability to drive multiple cell fates from iPSC under isogenic conditions now facilitates the analysis of causal variants in multiple cellular lineages. Bioinformatic analyses have revealed that T1D risk genes cluster within a limited number of immune signaling pathways, yet the relevant immune cell subsets and cellular activation states in which candidate risk genes impact cellular activities remain largely unknown. In this review, we summarize the functional impact of several candidate risk variants on host immunity in T1D and present an isogenic disease-in-a-dish model system for interrogating risk variants, with the goal of expediting precision therapeutics in T1D.

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The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 7 19%
Student > Master 7 19%
Researcher 5 14%
Student > Ph. D. Student 3 8%
Professor > Associate Professor 3 8%
Other 3 8%
Unknown 8 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 19%
Agricultural and Biological Sciences 6 17%
Medicine and Dentistry 5 14%
Computer Science 2 6%
Engineering 2 6%
Other 6 17%
Unknown 8 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 November 2017.
All research outputs
#7,151,813
of 25,382,440 outputs
Outputs from Frontiers in endocrinology
#1,987
of 13,018 outputs
Outputs of similar age
#107,965
of 336,554 outputs
Outputs of similar age from Frontiers in endocrinology
#26
of 117 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 13,018 research outputs from this source. They receive a mean Attention Score of 4.9. 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 336,554 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 117 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.