Complex gene-gene interactions in multiple sclerosis: a multifactorial approach reveals associations with inflammatory genes.
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 approximately 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.
Motsinger
Alison A
AA
Center for Human Genetics Research, Department of Molecular Physiology and Biophysics, 519 Light Hall, Vanderbilt University Medical School, Nashville, TN 37232-0700, USA. motsinger@chgr.mc.vanderbilt.edu
Brassat
David
D
Caillier
Stacy J
SJ
Erlich
Henry A
HA
Walker
Karen
K
Steiner
Lori L
LL
Barcellos
Lisa F
LF
Pericak-Vance
Margaret A
MA
Schmidt
Silke
S
Gregory
Simon
S
Hauser
Stephen L
SL
Haines
Jonathan L
JL
Oksenberg
Jorge R
JR
Ritchie
Marylyn D
MD
D016022:Case-Control Studies; D005838:Genotype; D006801:Humans; D007249:Inflammation / Q000235:genetics*; D008957:Models, Genetic; D009103:Multiple Sclerosis / Q000235:genetics* / Q000473:pathology; D011506:Proteins / Q000235:genetics
D011506:Proteins