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Molecular Biology Reports

, Volume 38, Issue 4, pp 2281–2284 | Cite as

Analysis on the interaction between IL-1F7 gene and environmental factors on patients with ankylosing spondylitis: a case-only study

  • Rui Ge
  • Faming PanEmail author
  • Fangfang Liao
  • Guo Xia
  • Yang Mei
  • Beibei Shen
  • Tianchen Zhang
  • Jing Gao
  • Li Zhang
  • Zhenhua Duan
  • Shengqian Xu
  • Jianhua Xu
Article

Abstract

To examine the interaction between IL-1F7 gene and environmental factors in patients with ankylosing spondylities (AS). 150 AS Han Chinese patients (all human leukocyte antigen-B27 positive) were genotyped using a panel of single-nucleotide polymorphism markers within IL-1F7 gene (rs3811047) by ligase detection reactions. Polymerase chain reaction with sequence-specific primer was used to determine HLA-B27 subtypes. We analyzed the interaction between IF-1F7 gene and eight environmental factors in AS patients by using a case–only study. The genetic polymorphism and environmental factors were considered as dependent variables in logistic models, and P-values, ORi and 95% confidence intervals were used for estimating the effects of interaction. The different frequency of A/G between drinking group and non-drinking group was significant (ORi 3.163, 95% CI 1.368–7.317, P = 0.006). Within the cooking oil group, odds ratio for interaction of G × E between main plants fats and half plants -half animal fats subunits was 4.273 (95% CI 1.590–11.479, P = 0.004). Our data show that there was no interaction between IL-1F7 alleles and the other six environmental factors in AS patients (all P > 0.05). We observed that there was an interaction between IF-1F7 gene and drinking in AS patients. Thus, drinking may be a risk exposure factor to take combined action with predisposing genes in AS patients. This action may increase the incident risk of AS. Also, main plants fats may be protective factors to AS.

Keywords

IL-1F7 gene Environmental factors Case-only study Interaction 

Notes

Acknowledgments

This work was supported by grants from the National and Province Natural Science Foundation of China (30771849,30972530 090413133), Anhui Medical University Dr. Priming Fund (01XJ2006001) and Anhui Science and Technology Agency annual plan in 2008 (08020303070). We thank all the families with AS and health control individuals for their enthusiastic participation in the genetic epidemiology.

References

  1. 1.
    Brown MA (2008) Breakthroughs in genetic studies of ankylosing spondylitis. Rheumatology (Oxford) 47:132–137CrossRefGoogle Scholar
  2. 2.
    Sims AM, Wordsworth BP, Brown MA (2004) Genetic susceptibility to ankylosing spondylitis. Curr Mol Med 4:13–20PubMedCrossRefGoogle Scholar
  3. 3.
    Maksymowych WP, Rahman P, Reeve JP, Gladman DD, Peddle L, Inman RD (2006) Association of the IL1 gene cluster with susceptibility to ankylosing spondylitis: an analysis of three Canadian populations. Arthritis Rheum 54:974–985PubMedCrossRefGoogle Scholar
  4. 4.
    Laval SH, Timms A, Edwards S, Bradbury L, Brophy S, Milicic A, Rubin L, Siminovitch KA, Weeks DE, Calin A (2001) Whole-genome screening in ankylosing spondylitis: evidence of non-MHC genetic-susceptibility loci. Am J Hum Genet 68:918–926PubMedCrossRefGoogle Scholar
  5. 5.
    Zhang G, Luo J, Bruckel J, Weisman MA (2004) Genetic studies in familial ankylosing spondylitis susceptibility. Arthritis Rheum 50:2246–2254PubMedCrossRefGoogle Scholar
  6. 6.
    Pan F, Liao F, Xia G, Ge R, Mei Y, Tang X, Xu S, Xu J, Pan H, Ye D, Zou Y (2010) Association of IL-1F7 gene with susceptibility to human leukocyte antigen-B27 positive ankylosing spondylitis in Han Chinese population. Clin Chim Acta 411(1–2):124–126PubMedCrossRefGoogle Scholar
  7. 7.
    Oliver JE, Silman AJ (2009) What epidemiology has told us about risk factors and aetiopathogenesis in rheumatic diseases. Arthritis Res Ther 11(3):223PubMedCrossRefGoogle Scholar
  8. 8.
    Van der Linden S, Valkenburg HA, Cats A (1984) Evaluation of diagnostic criteria for ankylosing spondylitis. A proposal for modification of the New York criteria. Arthritis Rheum 27:361–368PubMedCrossRefGoogle Scholar
  9. 9.
    Faul F, Erdfelder E, Lang AG, Buchner A (2007) G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods 39:175–191PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Rui Ge
    • 1
  • Faming Pan
    • 1
    Email author
  • Fangfang Liao
    • 1
  • Guo Xia
    • 1
  • Yang Mei
    • 1
  • Beibei Shen
    • 1
  • Tianchen Zhang
    • 1
  • Jing Gao
    • 1
  • Li Zhang
    • 3
  • Zhenhua Duan
    • 1
  • Shengqian Xu
    • 2
  • Jianhua Xu
    • 2
  1. 1.Department of Epidemiology and Biostatistics, School of Public HealthAnhui Medical UniversityHefei, AnhuiChina
  2. 2.Department of RheumatologyFirst Affiliated Hospital, Anhui Medical UniversityHefei, AnhuiChina
  3. 3.Anhui Medical Genetics Center in Anhui Medical CollegeHefeiChina

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