↓ Skip to main content

Comprehensive molecular diagnosis of Epstein–Barr virus-associated lymphoproliferative diseases using next-generation sequencing

Overview of attention for article published in International Journal of Hematology, May 2018
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

Mentioned by

twitter
2 X users

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
39 Mendeley
Title
Comprehensive molecular diagnosis of Epstein–Barr virus-associated lymphoproliferative diseases using next-generation sequencing
Published in
International Journal of Hematology, May 2018
DOI 10.1007/s12185-018-2475-6
Pubmed ID
Authors

Shintaro Ono, Manabu Nakayama, Hirokazu Kanegane, Akihiro Hoshino, Saeko Shimodera, Hirofumi Shibata, Hisanori Fujino, Takahiro Fujino, Yuta Yunomae, Tsubasa Okano, Motoi Yamashita, Takahiro Yasumi, Kazushi Izawa, Masatoshi Takagi, Kohsuke Imai, Kejian Zhang, Rebecca Marsh, Capucine Picard, Sylvain Latour, Osamu Ohara, Tomohiro Morio

Abstract

Epstein-Barr virus (EBV) is associated with several life-threatening diseases, such as lymphoproliferative disease (LPD), particularly in immunocompromised hosts. Some categories of primary immunodeficiency diseases (PIDs) including X-linked lymphoproliferative syndrome (XLP), are characterized by susceptibility and vulnerability to EBV infection. The number of genetically defined PIDs is rapidly increasing, and clinical genetic testing plays an important role in establishing a definitive diagnosis. Whole-exome sequencing is performed for diagnosing rare genetic diseases, but is both expensive and time-consuming. Low-cost, high-throughput gene analysis systems are thus necessary. We developed a comprehensive molecular diagnostic method using a two-step tailed polymerase chain reaction (PCR) and a next-generation sequencing (NGS) platform to detect mutations in 23 candidate genes responsible for XLP or XLP-like diseases. Samples from 19 patients suspected of having EBV-associated LPD were used in this comprehensive molecular diagnosis. Causative gene mutations (involving PRF1 and SH2D1A) were detected in two of the 19 patients studied. This comprehensive diagnosis method effectively detected mutations in all coding exons of 23 genes with sufficient read numbers for each amplicon. This comprehensive molecular diagnostic method using PCR and NGS provides a rapid, accurate, low-cost diagnosis for patients with XLP or XLP-like diseases.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 39 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 15%
Student > Ph. D. Student 4 10%
Other 3 8%
Professor > Associate Professor 3 8%
Student > Master 3 8%
Other 9 23%
Unknown 11 28%
Readers by discipline Count As %
Medicine and Dentistry 9 23%
Biochemistry, Genetics and Molecular Biology 4 10%
Immunology and Microbiology 3 8%
Agricultural and Biological Sciences 2 5%
Social Sciences 2 5%
Other 4 10%
Unknown 15 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 21 May 2018.
All research outputs
#17,958,638
of 23,061,402 outputs
Outputs from International Journal of Hematology
#889
of 1,415 outputs
Outputs of similar age
#238,017
of 329,133 outputs
Outputs of similar age from International Journal of Hematology
#8
of 24 outputs
Altmetric has tracked 23,061,402 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,415 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 34th percentile – i.e., 34% of its peers scored the same or lower than it.
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 329,133 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24 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.