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Assessment of gene-covariate interactions by incorporating covariates into association mapping

Yen-Feng Chiu1, Hui-Yi Kao, Yi-Shin Chen

  • 1Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, 35 Keyan Road, Zhunan, Miaoli County 350, Taiwan, Republic of China. yfchiu@nhri.org.tw.

BMC Proceedings
|December 19, 2009
PubMed

Insights

The human leukocyte antigen (HLA) region is a key genetic risk factor for rheumatoid arthritis. This study links shared epitope alleles and antibodies to cyclic citrullinated peptides (anti-CCP) to better understand rheumatoid arthritis genetic pathways.

Area of Science:

  • Immunogenetics
  • Rheumatology
  • Genetic Epidemiology

Background:

  • The human leukocyte antigen (HLA) region is the primary genetic risk factor for rheumatoid arthritis (RA).
  • Specific HLA-DRB1 alleles encoding the shared epitope (SE) are associated with RA characterized by antibodies to cyclic citrullinated peptides (anti-CCP).

Purpose of the Study:

  • To assess the association between the SE or anti-CCP antibodies and identified RA susceptibility genes.
  • To evaluate gene-gene and gene-environment interactions in RA pathogenesis.
  • To dissect the pathways underlying RA induction and progression using quantitative antibody measurements.

Main Methods:

  • Linkage disequilibrium mapping incorporating SE and anti-CCP antibodies or rheumatoid factor as covariates.
  • Statistical analysis to assess associations and interactions.

Main Results:

  • The study successfully incorporated SE and antibody data into linkage disequilibrium mapping.
  • This approach allows for the evaluation of gene-gene and gene-environment interactions in RA.

Conclusions:

  • The methodology enables a deeper understanding of the genetic architecture of RA.
  • This approach can dissect the complex pathways involved in RA development and progression, particularly concerning antibody production.

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