期刊
HUMAN HEREDITY
卷 56, 期 1-3, 页码 73-82出版社
KARGER
DOI: 10.1159/000073735
关键词
gene-gene interactions; multifactor dimensionality reduction; biological systems moduling
资金
- NATIONAL HEART, LUNG, AND BLOOD INSTITUTE [U19HL065962, R01HL065234, U01HL065962] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [P01GM031304] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE ON AGING [R01AG019085, R01AG020135] Funding Source: NIH RePORTER
- NHLBI NIH HHS [HL65962, HL65234] Funding Source: Medline
- NIA NIH HHS [AG20135, AG19085] Funding Source: Medline
- NIGMS NIH HHS [GM31304] Funding Source: Medline
There is increasing awareness that epistasis or gene-gene interaction plays a role in susceptibility to common human diseases. In this paper, we formulate a working hypothesis that epistasis is a ubiquitous component of the genetic architecture of common human diseases and that complex interactions are more important than the independent main effects of any one susceptibility gene. This working hypothesis is based on several bodies of evidence. First, the idea that epistasis is important is not new. In fact, the recognition that deviations from Mendelian ratios are due to interactions between genes has been around for nearly 100 years. Second, the ubiquity of biomolecular interactions in gene regulation and biochemical and metabolic systems suggest that relationship between DNA sequence variations and clinical endpoints is likely to involve gene-gene interactions. Third, positive results from studies of single polymorphisms typically do not replicate across independent samples. This is true for both linkage and association studies. Fourth, gene-gene interactions are commonly found when properly investigated. We review each of these points and then review an analytical strategy called multifactor dimensionality reduction for detecting epistasis. We end with ideas of how hypotheses about biological epistasis can be generated from statistical evidence using biochemical systems models. If this working hypothesis is true, it suggests that we need a research strategy for identifying common disease susceptibility genes that embraces, rather than ignores, the complexity of the genotype to phenotype relationship. Copyright (C) 2003 S. Karger AG, Basel.
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