Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

We introduce an innovative multilocus test for disease association. It is an extension of an existing score test that gains power over alternative methods by incorporating a parsimonious one-degree-of-freedom model for interaction. We use our method in applications designed to detect interactions that generate hypotheses about the functionality of prostate cancer (PRCA) susceptibility regions.Our proposed score test is designed to gain additional power through the use of a retrospective likelihood that exploits an assumption of independence between unlinked loci in the underlying population. Its performance is validated through simulation. The method is used in conditional scans with data from stage II of the Cancer Genetic Markers of Susceptibility PRCA genome-wide association study.Our proposed method increases power to detect susceptibility loci in diverse settings. It identified two high-ranking, biologically interesting interactions: (1) rs748120 of NR2C2 and subregions of 8q24 that contain independent susceptibility loci specific to PRCA and (2) rs4810671 of SULF2 and both JAZF1 and HNF1B that are associated with PRCA and type 2 diabetes.Our score test is a promising multilocus tool for genetic epidemiology. The results of our applications suggest functionality for poorly understood PRCA susceptibility regions. They motivate replication study.

Original publication

DOI

10.1159/000331222

Type

Journal article

Journal

Human heredity

Publication Date

01/2011

Volume

72

Pages

182 - 193

Addresses

Epidemiology and Biostatistics Program, Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, Bethesda, MD 20852, USA.

Keywords

Chromosomes, Human, Pair 8, Humans, Prostatic Neoplasms, Genetic Predisposition to Disease, Neoplasm Staging, Odds Ratio, Regression Analysis, Epistasis, Genetic, Linkage Disequilibrium, Polymorphism, Single Nucleotide, Genome, Human, Male, Genes, Neoplasm, Genome-Wide Association Study