title: Kernel canonical correlation analysis for assessing gene-gene interactions and application to ovarian cancer.
abstract: Although single-locus approaches have been widely applied to identify disease-associated single-nucleotide polymorphisms (SNPs), complex diseases are thought to be the product of multiple interactions between loci. This has led to the recent development of statistical methods for detecting statistical interactions between two loci. Canonical correlation analysis (CCA) has previously been proposed to detect gene-gene coassociation. However, this approach is limited to detecting linear relations and can only be applied when the number of observations exceeds the number of SNPs in a gene. This limitation is particularly important for next-generation sequencing, which could yield a large number of novel variants on a limited number of subjects. To overcome these limitations, we propose an approach to detect gene-gene interactions on the basis of a kernelized version of CCA (KCCA). Our simulation studies showed that KCCA controls the Type-I error, and is more powerful than leading gene-based approaches under a disease model with negligible marginal effects. To demonstrate the utility of our approach, we also applied KCCA to assess interactions between 200 genes in the NF-κB pathway in relation to ovarian cancer risk in 3869 cases and 3276 controls. We identified 13 significant gene pairs relevant to ovarian cancer risk (local false discovery rate <0.05). Finally, we discuss the advantages of KCCA in gene-gene interaction analysis and its future role in genetic association studies.
authors.affiliation: Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
authors.forename: Nicholas B
authors.initials: NB
authors.lastname: Larson
authors.affiliation: Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
authors.forename: Gregory D
authors.initials: GD
authors.lastname: Jenkins
authors.affiliation: Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
authors.forename: Melissa C
authors.initials: MC
authors.lastname: Larson
authors.affiliation: Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
authors.forename: Robert A
authors.initials: RA
authors.lastname: Vierkant
authors.affiliation: Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA.
authors.forename: Thomas A
authors.initials: TA
authors.lastname: Sellers
authors.affiliation: Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA.
authors.forename: Catherine M
authors.initials: CM
authors.lastname: Phelan
authors.affiliation: Duke Comprehensive Cancer Center, Duke University, Durham, NC, USA.
authors.forename: Joellen M
authors.initials: JM
authors.lastname: Schildkraut
authors.affiliation: Department of Pediatrics, Universty of South Florida College of Medicine, Tampa, FL, USA.
authors.forename: Rebecca
authors.initials: R
authors.lastname: Sutphen
authors.affiliation: Department of Oncology, University of Cambridge, Cambridge, UK.
authors.forename: Paul P D
authors.initials: PP
authors.lastname: Pharoah
authors.affiliation: Department of Preventative Medicine, University of Southern California, Los Angeles, CA, USA.
authors.forename: Simon A
authors.initials: SA
authors.lastname: Gayther
authors.affiliation: Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
authors.forename: Nicolas
authors.initials: N
authors.lastname: Wentzensen
authors.affiliation: Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
authors.forename: Ellen L
authors.initials: EL
authors.lastname: Goode
authors.affiliation: 1] Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA [2] Department of Biostatistics, University of Kansas Medical Center, Kansas City, KS, USA.
authors.forename: Brooke L
authors.initials: BL
authors.lastname: Fridley
mesh_terms: D019295:Computational Biology / Q000379:methods; D004843:Epistasis, Genetic; D005260:Female; D020022:Genetic Predisposition to Disease; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D016328:NF-kappa B; D010051:Ovarian Neoplasms / Q000235:genetics* / Q000473:pathology; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D012307:Risk Factors; D012984:Software
chemical_list: D016328:NF-kappa B