HLA analysis and disease for multiple sclerosis

Hsin Wen Tsao, Hung Wen Chiu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Alleles for HLA-A, HLA-B, HLA-C, HLADQB1, HLA-DRB1, and HLA-DRB were typed across 820 age, gender, and race matched participants; 677 for whom have Multiple Sclerosis (MS) vs. 143 that do not. Observed alleles were coded and subject to significance testing with the goal to identify those alleles significantly associated with MS. Of the 368 unique alleles observed, eight were identified to be significantly associated with MS 100% of the time over 50 rounds of cross-validation testing; specifically HLA-DQB1*003, HLADQB1*00301, HLA-DQB1*00602, HLA-DRB1*0404, HLADRB1*1501, HLA-DRB1*1516/18, HLA-DRB3*02, and HLADRB4*01 were identified. Allele based classification modeling performed with each round of cross-validation testing provided for an overall classification success rate of 70%. Inspection of the alleles identified to be significantly associated with MS reveal nearly all to have been previously reported to be associated with MS; including four alleles reported to have association with disease severity.

Original languageEnglish
Title of host publicationIFMBE Proceedings
Pages1385-1388
Number of pages4
Volume37
DOIs
Publication statusPublished - 2011

Keywords

  • Alleles
  • Cross- Validation Condition
  • HLA
  • Multiple Sclerosis
  • R software

ASJC Scopus subject areas

  • Biomedical Engineering
  • Bioengineering

Fingerprint Dive into the research topics of 'HLA analysis and disease for multiple sclerosis'. Together they form a unique fingerprint.

  • Cite this