Complex gene-gene interactions in multiple sclerosis: A multifactorial approach reveals associations with inflammatory genes

Alison A. Motsinger, David Brassat, Stacy J. Caillier, Henry A. Erlich, Karen Walker, Lori L. Steiner, Lisa F. Barcellos, Margaret A. Pericak-Vance, Silke Schmidt, Simon Gregory, Stephen L. Hauser, Jonathan L. Haines, Jorge R. Oksenberg, Marylyn Deriggi Ritchie

Research output: Contribution to journalArticle

29 Citations (Scopus)

Abstract

The complex inheritance involved in multiple sclerosis (MS) risk has been extensively investigated, but our understanding of MS genetics remains rudimentary. In this study, we explore 51 single nucleotide polymorphisms (SNPs) in 36 candidate genes from the inflammatory pathway and test for gene-gene interactions using complementary case-control, discordant sibling pair, and trio family study designs. We used a sample of 421 carefully diagnosed MS cases and 96 unrelated, healthy controls; discordant sibling pairs from 146 multiplex families; and 275 trio families. We used multifactor dimensionality reduction to explore gene-gene interactions. Based on our analyses, we have identified several statistically significant models including both main effect models and two-locus, three-locus, and four-locus epistasis models that predict MS disease risk with between ∼61% and 85% accuracy. These results suggest that significant epistasis, or gene-gene interactions, may exist even in the absence of statistically significant individual main effects.

Original languageEnglish (US)
Pages (from-to)11-20
Number of pages10
JournalNeurogenetics
Volume8
Issue number1
DOIs
StatePublished - Jan 1 2007

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Multiple Sclerosis
Genes
Multifactor Dimensionality Reduction
Single Nucleotide Polymorphism

All Science Journal Classification (ASJC) codes

  • Genetics
  • Genetics(clinical)
  • Cellular and Molecular Neuroscience

Cite this

Motsinger, A. A., Brassat, D., Caillier, S. J., Erlich, H. A., Walker, K., Steiner, L. L., ... Ritchie, M. D. (2007). Complex gene-gene interactions in multiple sclerosis: A multifactorial approach reveals associations with inflammatory genes. Neurogenetics, 8(1), 11-20. https://doi.org/10.1007/s10048-006-0058-9
Motsinger, Alison A. ; Brassat, David ; Caillier, Stacy J. ; Erlich, Henry A. ; Walker, Karen ; Steiner, Lori L. ; Barcellos, Lisa F. ; Pericak-Vance, Margaret A. ; Schmidt, Silke ; Gregory, Simon ; Hauser, Stephen L. ; Haines, Jonathan L. ; Oksenberg, Jorge R. ; Ritchie, Marylyn Deriggi. / Complex gene-gene interactions in multiple sclerosis : A multifactorial approach reveals associations with inflammatory genes. In: Neurogenetics. 2007 ; Vol. 8, No. 1. pp. 11-20.
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Motsinger, AA, Brassat, D, Caillier, SJ, Erlich, HA, Walker, K, Steiner, LL, Barcellos, LF, Pericak-Vance, MA, Schmidt, S, Gregory, S, Hauser, SL, Haines, JL, Oksenberg, JR & Ritchie, MD 2007, 'Complex gene-gene interactions in multiple sclerosis: A multifactorial approach reveals associations with inflammatory genes', Neurogenetics, vol. 8, no. 1, pp. 11-20. https://doi.org/10.1007/s10048-006-0058-9

Complex gene-gene interactions in multiple sclerosis : A multifactorial approach reveals associations with inflammatory genes. / Motsinger, Alison A.; Brassat, David; Caillier, Stacy J.; Erlich, Henry A.; Walker, Karen; Steiner, Lori L.; Barcellos, Lisa F.; Pericak-Vance, Margaret A.; Schmidt, Silke; Gregory, Simon; Hauser, Stephen L.; Haines, Jonathan L.; Oksenberg, Jorge R.; Ritchie, Marylyn Deriggi.

In: Neurogenetics, Vol. 8, No. 1, 01.01.2007, p. 11-20.

Research output: Contribution to journalArticle

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T2 - A multifactorial approach reveals associations with inflammatory genes

AU - Motsinger, Alison A.

AU - Brassat, David

AU - Caillier, Stacy J.

AU - Erlich, Henry A.

AU - Walker, Karen

AU - Steiner, Lori L.

AU - Barcellos, Lisa F.

AU - Pericak-Vance, Margaret A.

AU - Schmidt, Silke

AU - Gregory, Simon

AU - Hauser, Stephen L.

AU - Haines, Jonathan L.

AU - Oksenberg, Jorge R.

AU - Ritchie, Marylyn Deriggi

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N2 - The complex inheritance involved in multiple sclerosis (MS) risk has been extensively investigated, but our understanding of MS genetics remains rudimentary. In this study, we explore 51 single nucleotide polymorphisms (SNPs) in 36 candidate genes from the inflammatory pathway and test for gene-gene interactions using complementary case-control, discordant sibling pair, and trio family study designs. We used a sample of 421 carefully diagnosed MS cases and 96 unrelated, healthy controls; discordant sibling pairs from 146 multiplex families; and 275 trio families. We used multifactor dimensionality reduction to explore gene-gene interactions. Based on our analyses, we have identified several statistically significant models including both main effect models and two-locus, three-locus, and four-locus epistasis models that predict MS disease risk with between ∼61% and 85% accuracy. These results suggest that significant epistasis, or gene-gene interactions, may exist even in the absence of statistically significant individual main effects.

AB - The complex inheritance involved in multiple sclerosis (MS) risk has been extensively investigated, but our understanding of MS genetics remains rudimentary. In this study, we explore 51 single nucleotide polymorphisms (SNPs) in 36 candidate genes from the inflammatory pathway and test for gene-gene interactions using complementary case-control, discordant sibling pair, and trio family study designs. We used a sample of 421 carefully diagnosed MS cases and 96 unrelated, healthy controls; discordant sibling pairs from 146 multiplex families; and 275 trio families. We used multifactor dimensionality reduction to explore gene-gene interactions. Based on our analyses, we have identified several statistically significant models including both main effect models and two-locus, three-locus, and four-locus epistasis models that predict MS disease risk with between ∼61% and 85% accuracy. These results suggest that significant epistasis, or gene-gene interactions, may exist even in the absence of statistically significant individual main effects.

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