Anti-centromere antibody exhibits specific distribution levels among anti-nuclear antibodies and may characterize a distinct subset in rheumatoid arthritis

• Kuramoto, Nobuo

• Ohmura, Koichiro

• Ikari, Katsunori

• Yano, Koichiro

• Furu, Moritoshi

• Yamakawa, Noriyuki

• Hashimoto, Motomu

• Ito, Hiromu

• Fujii, Takao

• Murakami, Kosaku

• Nakashima, Ran

• Imura, Yoshitaka

• Yukawa, Naoichiro

• Yoshifuji, Hajime

• Taniguchi, Atsuo

• Momohara, Shigeki

• Yamanaka, Hisashi

• Matsuda, Fumihiko

• Mimori, Tsuneyo

• Terao, Chikashi

Abstract

Anti-centromere antibody (ACA) is one of the classical anti-nuclear antibody (ANA) staining patterns. However, characteristics of ACA in comparison with the other ANA patterns and clinical features of ACA-positive subjects have not been elucidated. Here, we examined all ANA patterns by indirect immunofluorescence for 859 rheumatoid arthritis (RA) patients. Together with the ANA data of 9, 575 healthy volunteers, we compared distributions of the ANA levels. ACA was the only ANA that demonstrated a definite bimodal distribution of levels. ACA showed significantly higher levels than the other ANA staining patterns in both RA and healthy population (p < 0.0001). ACA-positivity was associated with old age and was observed more in females. We further recruited another cohort of 3, 353 RA patients and confirmed the findings. ACA was also associated with Raynaud’s phenomenon (p = 6.8 × 10−11) in RA. As a conclusion, ACA displays a specific ANA staining pattern with a bimodal distribution, and ACA-positive RA may constitute a distinct subset with specific clinical features.

Journal

• Scientific Reports

  Scientific Reports 7 6911-, 2017-07-31

  Springer Nature

Keywords

• Autoimmunity
• Rheumatoid arthritis

Details

• CRID: 1050282810828683648
• NII Article ID: 120006368159
• ISSN: 20452322
• DOI: 10.1038/s41598-017-07137-4
• HANDLE: 2433/228140
• Web Site: https://www.nature.com/articles/s41598-017-07137-4
• Web Site: https://www.nature.com/articles/s41598-017-07137-4.pdf
• Text Lang: en
• Article Type: journal article
• Data Source:
  • IRDB
  • Crossref
  • CiNii Articles
  • KAKEN