• Search Research Projects
  • Search Researchers
  • How to Use
  1. Back to project page

2020 Fiscal Year Final Research Report

Comprehensive search of autoantibies in neuroimmunological disorders using a novel hybrid SEREX-FACS method

Research Project

  • PDF
Project/Area Number 18K07387
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Review Section Basic Section 51030:Pathophysiologic neuroscience-related
Research InstitutionChiba University

Principal Investigator

Masahiro Mori  千葉大学, 大学院医学研究院, 准教授 (70345023)

Co-Investigator(Kenkyū-buntansha) 鵜沢 顕之  千葉大学, 医学部附属病院, 助教 (10533317)
八木 良二  千葉大学, 大学院医学研究院, 特任准教授 (20392152)
日和佐 隆樹  千葉大学, 大学院医学研究院, 特任准教授 (30260251)
星野 忠次  千葉大学, 大学院薬学研究院, 准教授 (90257220)
Project Period (FY) 2018-04-01 – 2021-03-31
Keywords視神経脊髄炎 / 神経免疫疾患 / 自己抗体 / フローサイトメトリー / SEREX
Outline of Final Research Achievements

We have obtained sera from double seronegative (dSN) neuromyelitis optica patients without anti-aquaporin-4 antibody or anti-myelin oligodendrocyte glycoprotein antibody, and a cDNA library (plasmid DNA) constructed from human brain, which were transferred into HEK293 cells. Then, the transformed cells were reacted with sera from the dSN NMO patients. The reacted cells were collected by a Cell Sorter. Plasmid DNA was extracted from the collected cells, and amplified by PCR. Nucleotide sequences were determined with PCR-amplified DNA using an automated sequencer. After the homology screening of the identified genes within the public sequence database, and we succeded in identification of two possible antigen genes.

Free Research Field

神経免疫学

Academic Significance and Societal Importance of the Research Achievements

今回、我々はSEREX法とFACS法を融合させた、世界で初めての新手法を編みだし、自己免疫が関与する神経難病であり、既存の抗体が陰性で原因が未解明である視神経脊髄炎患者血清を用いた検討を行った。結果、新規自己抗原候補のタンパクをコードする遺伝子の同定に成功した。それらが真の自己抗原か、さらなる検討が必要であるが、この方法が実際に施行でき、新規自己抗原が検出できる可能性を明確に示した点で学術的な意義は大きく、さらにこの方法が他の原因不明の多くの自己免疫疾患に応用できる可能性を秘めており、それらの疾患の治療に結びつきうる点でも意義は大きいと考える。

URL: 

Published: 2022-01-27  

Information User Guide FAQ News Terms of Use Attribution of KAKENHI

Powered by NII kakenhi