Title |
Comprehensive molecular diagnosis of Epstein–Barr virus-associated lymphoproliferative diseases using next-generation sequencing
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Published in |
International Journal of Hematology, May 2018
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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
Geographical breakdown
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Thailand | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 39 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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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 % |
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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% |