TY - JOUR
T1 - Immunochip analyses of epistasis in rheumatoid arthritis confirm multiple interactions within MHC and suggest novel non-MHC epistatic signals.
AU - Wei, Wen-Hua
AU - Loh, Chia-Yin
AU - Worthington, Jane
AU - Eyre, Stephen
PY - 2016
Y1 - 2016
N2 - OBJECTIVE: Studying statistical gene-gene interactions (epistasis) has been limited by the difficulties in performance, both statistically and computationally, in large enough sample numbers to gain sufficient power. Three large Immunochip datasets from cohort samples recruited in the United Kingdom, United States, and Sweden with European ancestry were used to examine epistasis in rheumatoid arthritis (RA). METHODS: A full pairwise search was conducted in the UK cohort using a high-throughput tool and the resultant significant epistatic signals were tested for replication in the United States and Swedish cohorts. A forward selection approach was applied to remove redundant signals, while conditioning on the preidentified additive effects. RESULTS: We detected abundant genome-wide significant (p <1.0e-13) epistatic signals, all within the MHC region. These signals were reduced substantially, but a proportion remained significant (p <1.0e-03) in conditional tests. We identified 11 independent epistatic interactions across the entire MHC, each explaining on average 0.12% of the phenotypic variance, nearly all replicated in both replication cohorts. We also identified non-MHC epistatic interactions between RA susceptible loci LOC100506023 and IRF5 with Immunochip-wide significance (p <1.1e-08) and between 2 neighboring single-nucleotide polymorphism near PTPN22 that were in low linkage disequilibrium with independent interaction (p <1.0e-05). Both non-MHC epistatic interactions were statistically replicated with a similar interaction pattern in the US cohort only. CONCLUSION: There are multiple but relatively weak interactions independent of the additive effects in RA and a larger sample number is required to confidently assign additional non-MHC epistasis.
AB - OBJECTIVE: Studying statistical gene-gene interactions (epistasis) has been limited by the difficulties in performance, both statistically and computationally, in large enough sample numbers to gain sufficient power. Three large Immunochip datasets from cohort samples recruited in the United Kingdom, United States, and Sweden with European ancestry were used to examine epistasis in rheumatoid arthritis (RA). METHODS: A full pairwise search was conducted in the UK cohort using a high-throughput tool and the resultant significant epistatic signals were tested for replication in the United States and Swedish cohorts. A forward selection approach was applied to remove redundant signals, while conditioning on the preidentified additive effects. RESULTS: We detected abundant genome-wide significant (p <1.0e-13) epistatic signals, all within the MHC region. These signals were reduced substantially, but a proportion remained significant (p <1.0e-03) in conditional tests. We identified 11 independent epistatic interactions across the entire MHC, each explaining on average 0.12% of the phenotypic variance, nearly all replicated in both replication cohorts. We also identified non-MHC epistatic interactions between RA susceptible loci LOC100506023 and IRF5 with Immunochip-wide significance (p <1.1e-08) and between 2 neighboring single-nucleotide polymorphism near PTPN22 that were in low linkage disequilibrium with independent interaction (p <1.0e-05). Both non-MHC epistatic interactions were statistically replicated with a similar interaction pattern in the US cohort only. CONCLUSION: There are multiple but relatively weak interactions independent of the additive effects in RA and a larger sample number is required to confidently assign additional non-MHC epistasis.
U2 - 10.3899/jrheum.150836
DO - 10.3899/jrheum.150836
M3 - Article
C2 - 26879349
SN - 1499-2752
VL - 43
SP - 839
EP - 845
JO - The Journal of rheumatology
JF - The Journal of rheumatology
IS - 5
ER -