A General Model for Multilocus Epistatic Interactions in Case-Control Studies

Background Epistasis, i.e., the interaction of alleles at different loci, is thought to play a central role in the formation and progression of complex diseases. The complexity of disease expression should arise from a complex network of epistatic interactions involving multiple genes. Methodology We develop a general model for testing high-order epistatic interactions for a complex disease in a case-control study. We incorporate the quantitative genetic theory of high-order epistasis into the setting of cases and controls sampled from a natural population. The new model allows the identification and testing of epistasis and its various genetic components. Conclusions Simulation studies were used to examine the power and false positive rates of the model under different sampling strategies. The model was used to detect epistasis in a case-control study of inflammatory bowel disease, in which five SNPs at a candidate gene were typed, leading to the identification of a significant three-locus epistasis.

[1]  W. Bateson Mendel's Principles of Heredity , 1910, Nature.

[2]  K. Mather,et al.  Biometrical Genetics , 1971, Springer US.

[3]  O. Kempthorne The correlation between relatives on the supposition of mendelian inheritance , 1968 .

[4]  P W Sternberg,et al.  Genetic dissection of developmental pathways. , 1995, Methods in cell biology.

[5]  B. R. Wiseman,et al.  Quantitative trait loci and metabolic pathways. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[6]  U. Bhalla,et al.  Complexity in biological signaling systems. , 1999, Science.

[7]  R Judson,et al.  The predictive power of haplotypes in clinical response. , 2000, Pharmacogenomics.

[8]  G. Wagner,et al.  Epistasis and the mutation load: a measurement-theoretical approach. , 2001, Genetics.

[9]  J. Bader The relative power of SNPs and haplotype as genetic markers for association tests. , 2001, Pharmacogenomics.

[10]  J. H. Moore,et al.  Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer. , 2001, American journal of human genetics.

[11]  L. Andersson,et al.  Use of randomization testing to detect multiple epistatic QTLs. , 2002, Genetical research.

[12]  Keith Hoots,et al.  Epistatic interaction between KIR3DS1 and HLA-B delays the progression to AIDS , 2002, Nature Genetics.

[13]  G. Casella,et al.  Sequencing Complex Diseases With HapMap , 2004, Genetics.

[14]  Thomas Lengauer,et al.  Genetic variation in DLG5 is associated with inflammatory bowel disease , 2004, Nature Genetics.

[15]  R. L. Wu,et al.  Detecting epistatic genetic variance with a clonally replicated design: models for lowvs high-order nonallelic interaction , 1996, Theoretical and Applied Genetics.

[16]  A. Lacasa,et al.  Epistasis in the resistance of pepper to phytophthora stem blight (Phytophthora capsici L.) and its significance in the prediction of double cross performances , 1994, Euphytica.

[17]  P. Donnelly,et al.  Genome-wide strategies for detecting multiple loci that influence complex diseases , 2005, Nature Genetics.

[18]  M. Daly,et al.  Genome-wide association studies for common diseases and complex traits , 2005, Nature Reviews Genetics.

[19]  W. Bateson Mendels principles of heredity , 2005, Zeitschrift für Induktive Abstammungs- und Vererbungslehre.

[20]  D. Clayton,et al.  Genome-wide association studies: theoretical and practical concerns , 2005, Nature Reviews Genetics.

[21]  Paul W Sternberg,et al.  Genetic dissection of developmental pathways. , 2006, WormBook : the online review of C. elegans biology.

[22]  Lior Pachter,et al.  Analysis of epistatic interactions and fitness landscapes using a new geometric approach , 2007, BMC Evolutionary Biology.

[23]  J. Roh,et al.  An association between RRM1 haplotype and gemcitabine-induced neutropenia in breast cancer patients. , 2007, The oncologist.

[24]  Jun S. Liu,et al.  Bayesian inference of epistatic interactions in case-control studies , 2007, Nature Genetics.

[25]  Hans-Peter Piepho,et al.  Power to Detect Higher-Order Epistatic Interactions in a Metabolic Pathway Using a New Mapping Strategy , 2007, Genetics.

[26]  Calin Belta,et al.  Exploiting the pathway structure of metabolism to reveal high-order epistasis , 2008, BMC Systems Biology.

[27]  Ingo Wegener,et al.  Detecting high-order interactions of single nucleotide polymorphisms using genetic programming , 2007, Bioinform..

[28]  Manuel A. R. Ferreira,et al.  PLINK: a tool set for whole-genome association and population-based linkage analyses. , 2007, American journal of human genetics.

[29]  C. Moore,et al.  Interaction between allelic variation in IL12B and CCR5 affects the development of AIDS: IL12B/CCR5 interaction and HIV/AIDS , 2007, AIDS.

[30]  Arpad Kelemen,et al.  Statistical advances and challenges for analyzing correlated high dimensional SNP data in genomic study for complex diseases , 2008, 0803.4065.

[31]  Alison A Motsinger-Reif The effect of alternative permutation testing strategies on the performance of multifactor dimensionality reduction , 2008, BMC Research Notes.

[32]  F. Morón,et al.  A method for detecting epistasis in genome-wide studies using case-control multi-locus association analysis , 2008, BMC Genomics.

[33]  P. Phillips Epistasis — the essential role of gene interactions in the structure and evolution of genetic systems , 2008, Nature Reviews Genetics.

[34]  Rui Jiang,et al.  A random forest approach to the detection of epistatic interactions in case-control studies , 2009, BMC Bioinformatics.

[35]  Scott M. Williams,et al.  Epistasis and its implications for personal genetics. , 2009, American journal of human genetics.

[36]  James R Faeder,et al.  The Complexity of Cell Signaling and the Need for a New Mechanics , 2009, Science Signaling.

[37]  R. Wu,et al.  Genetic Association of DLG5 R30Q with Familial and Sporadic Inflammatory Bowel Disease in Men , 2009, Disease markers.

[38]  Koji Tsuda,et al.  Efficiently finding genome-wide three-way gene interactions from transcript- and genotype-data , 2009, Bioinform..

[39]  Marylyn D. Ritchie,et al.  A General Framework for Formal Tests of Interaction after Exhaustive Search Methods with Applications to MDR and MDR-PDT , 2010, PloS one.

[40]  Qiang Yang,et al.  Predictive rule inference for epistatic interaction detection in genome-wide association studies , 2010, Bioinform..