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Large, Diverse Population Cohorts of hiPSCs and Derived Hepatocyte-like Cells Reveal Functional Genetic Variation at Blood Lipid-Associated Loci

Overview of attention for article published in Cell Stem Cell, April 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

news
7 news outlets
blogs
1 blog
twitter
45 X users
patent
1 patent
facebook
1 Facebook page

Citations

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135 Dimensions

Readers on

mendeley
160 Mendeley
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Title
Large, Diverse Population Cohorts of hiPSCs and Derived Hepatocyte-like Cells Reveal Functional Genetic Variation at Blood Lipid-Associated Loci
Published in
Cell Stem Cell, April 2017
DOI 10.1016/j.stem.2017.03.017
Pubmed ID
Authors

Evanthia E. Pashos, YoSon Park, Xiao Wang, Avanthi Raghavan, Wenli Yang, Deepti Abbey, Derek T. Peters, Juan Arbelaez, Mayda Hernandez, Nicolas Kuperwasser, Wenjun Li, Zhaorui Lian, Ying Liu, Wenjian Lv, Stacey L. Lytle-Gabbin, Dawn H. Marchadier, Peter Rogov, Jianting Shi, Katherine J. Slovik, Ioannis M. Stylianou, Li Wang, Ruilan Yan, Xiaolan Zhang, Sekar Kathiresan, Stephen A. Duncan, Tarjei S. Mikkelsen, Edward E. Morrisey, Daniel J. Rader, Christopher D. Brown, Kiran Musunuru

Abstract

Genome-wide association studies have struggled to identify functional genes and variants underlying complex phenotypes. We recruited a multi-ethnic cohort of healthy volunteers (n = 91) and used their tissue to generate induced pluripotent stem cells (iPSCs) and hepatocyte-like cells (HLCs) for genome-wide mapping of expression quantitative trait loci (eQTLs) and allele-specific expression (ASE). We identified many eQTL genes (eGenes) not observed in the comparably sized Genotype-Tissue Expression project's human liver cohort (n = 96). Focusing on blood lipid-associated loci, we performed massively parallel reporter assays to screen candidate functional variants and used genome-edited stem cells, CRISPR interference, and mouse modeling to establish rs2277862-CPNE1, rs10889356-DOCK7, rs10889356-ANGPTL3, and rs10872142-FRK as functional SNP-gene sets. We demonstrated HLC eGenes CPNE1, VKORC1, UBE2L3, and ANGPTL3 and HLC ASE gene ACAA2 to be lipid-functional genes in mouse models. These findings endorse an iPSC-based experimental framework to discover functional variants and genes contributing to complex human traits.

X Demographics

X Demographics

The data shown below were collected from the profiles of 45 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 160 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 160 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 39 24%
Researcher 30 19%
Student > Master 13 8%
Other 9 6%
Student > Bachelor 9 6%
Other 30 19%
Unknown 30 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 59 37%
Agricultural and Biological Sciences 37 23%
Medicine and Dentistry 13 8%
Computer Science 4 3%
Pharmacology, Toxicology and Pharmaceutical Science 4 3%
Other 10 6%
Unknown 33 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 78. 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 15 December 2022.
All research outputs
#543,275
of 25,382,440 outputs
Outputs from Cell Stem Cell
#372
of 2,823 outputs
Outputs of similar age
#11,369
of 323,961 outputs
Outputs of similar age from Cell Stem Cell
#7
of 46 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,823 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 48.5. This one has done well, scoring higher than 86% 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 323,961 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 46 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.