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T cell dynamics and response of the microbiota after gene therapy to treat X-linked severe combined immunodeficiency

Overview of attention for article published in Genome Medicine, September 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)

Mentioned by

1 news outlet
17 tweeters
1 Facebook page


23 Dimensions

Readers on

56 Mendeley
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T cell dynamics and response of the microbiota after gene therapy to treat X-linked severe combined immunodeficiency
Published in
Genome Medicine, September 2018
DOI 10.1186/s13073-018-0580-z
Pubmed ID

Erik L. Clarke, A. Jesse Connell, Emmanuelle Six, Nadia A. Kadry, Arwa A. Abbas, Young Hwang, John K. Everett, Casey E. Hofstaedter, Rebecca Marsh, Myriam Armant, Judith Kelsen, Luigi D. Notarangelo, Ronald G. Collman, Salima Hacein-Bey-Abina, Donald B. Kohn, Marina Cavazzana, Alain Fischer, David A. Williams, Sung-Yun Pai, Frederic D. Bushman


Mutation of the IL2RG gene results in a form of severe combined immune deficiency (SCID-X1), which has been treated successfully with hematopoietic stem cell gene therapy. SCID-X1 gene therapy results in reconstitution of the previously lacking T cell compartment, allowing analysis of the roles of T cell immunity in humans by comparing before and after gene correction. Here we interrogate T cell reconstitution using four forms of high throughput analysis. (1) Estimation of the numbers of transduced progenitor cells by monitoring unique positions of integration of the therapeutic gene transfer vector. (2) Estimation of T cell population structure by sequencing of the recombined T cell receptor (TCR) beta locus. (3) Metagenomic analysis of microbial populations in oropharyngeal, nasopharyngeal, and gut samples. (4) Metagenomic analysis of viral populations in gut samples. Comparison of progenitor and mature T cell populations allowed estimation of a minimum number of cell divisions needed to generate the observed populations. Analysis of microbial populations showed the effects of immune reconstitution, including normalization of gut microbiota and clearance of viral infections. Metagenomic analysis revealed enrichment of genes for antibiotic resistance in gene-corrected subjects relative to healthy controls, likely a result of higher healthcare exposure. This multi-omic approach enables the characterization of multiple effects of SCID-X1 gene therapy, including T cell repertoire reconstitution, estimation of numbers of cell divisions between progenitors and daughter T cells, normalization of the microbiome, clearance of microbial pathogens, and modulations in antibiotic resistance gene levels. Together, these results quantify several aspects of the long-term efficacy of gene therapy for SCID-X1. This study includes data from ClinicalTrials.gov numbers NCT01410019, NCT01175239, and NCT01129544.

Twitter Demographics

The data shown below were collected from the profiles of 17 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 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 56 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 21%
Student > Bachelor 7 13%
Student > Ph. D. Student 7 13%
Student > Master 6 11%
Librarian 3 5%
Other 6 11%
Unknown 15 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 20%
Medicine and Dentistry 7 13%
Agricultural and Biological Sciences 6 11%
Immunology and Microbiology 3 5%
Nursing and Health Professions 2 4%
Other 7 13%
Unknown 20 36%

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 07 November 2018.
All research outputs
of 15,939,385 outputs
Outputs from Genome Medicine
of 1,074 outputs
Outputs of similar age
of 278,391 outputs
Outputs of similar age from Genome Medicine
of 1 outputs
Altmetric has tracked 15,939,385 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,074 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.6. This one has gotten more attention than average, scoring higher than 72% 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 278,391 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 86% of its contemporaries.
We're also able to compare this research output to 1 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