論文

査読有り
2015年

Development of a simple genotyping method for the HLA-A*31:01-tagging SNP in Japanese

PHARMACOGENOMICS
  • Keiko Maekawa
  • Ryosuke Nakamura
  • Nahoko Kaniwa
  • Seiho Mizusawa
  • Aya Kitamoto
  • Takuya Kitamoto
  • Maho Ukaji
  • Yumiko Matsuzawa
  • Emiko Sugiyama
  • Yoshimi Uchida
  • Kouichi Kurose
  • Mayumi Ueta
  • Chie Sotozono
  • Hiroko Ikeda
  • Akiko Yagami
  • Setsuko Matsukura
  • Shigeru Kinoshita
  • Masaaki Muramatsu
  • Zenro Ikezawa
  • Akihiro Sekine
  • Hirokazu Furuya
  • Yukitoshi Takahashi
  • Kayoko Matsunaga
  • Michiko Aihara
  • Yoshiro Saito
  • 全て表示

16
15
開始ページ
1689
終了ページ
1699
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.2217/pgs.15.115
出版者・発行元
FUTURE MEDICINE LTD

Aim: To construct a simple, low-cost typing method for the surrogate marker of HLA-A*31:01, a risk factor for carbamazepine (CBZ) related Stevens-Johnson syndrome/toxic epidermal necrolysis (SJS/TEN). Materials & methods: DNAs from Japanese SJS/TEN patients were used for genotyping and developing the assay. Results:HLA-A*31:01 was confirmed to be significantly associated with definite/probable cases of CBZ-related SJS/TEN (p = 0.0040). Three single nucleotide polymorphisms, rs1150738, rs3869066 and rs259945, were in absolute linkage disequilibrium with HLA-A*31:01 in 210 Japanese SJS/TEN patients. Robust genotyping of rs3869066 in ZNRD1-AS1 was developed using polymerase chain reaction-restriction fragment length polymorphism assays. Conclusion: Single nucleotide polymorphism genotyping is less time consuming and cheaper than conventional HLA typing, and would be useful for identifying Japanese patients at risk of CBZ-related SJS/TEN.

リンク情報
DOI
https://doi.org/10.2217/pgs.15.115
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/26490229
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000363398100002&DestApp=WOS_CPL
ID情報
  • DOI : 10.2217/pgs.15.115
  • ISSN : 1462-2416
  • eISSN : 1744-8042
  • PubMed ID : 26490229
  • Web of Science ID : WOS:000363398100002

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