Article

The ubiquitous nature of epistasis in determining susceptibility to common human diseases.

Program in Human Genetics, Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, TN 37232-0700, USA.
Human Heredity (Impact Factor: 1.64). 02/2003; 56(1-3):73-82. DOI: 10.1159/000073735
Source: PubMed

ABSTRACT 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.

0 Bookmarks
 · 
94 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The science of nutrition aims to improve human health by a preventive approach, to slow down illnesses or even decrease their occurrence. The focus is on chronic diseases such as cardiovascular diseases, diabetes, obesity and some types of cancer. Human health is affected by a variety of environmental factors as well as the individual's hereditary background. Due to its progression in the last decades, molecular biology studies have become abundant in many health branches including nutrition science. Nutrigenomics is a field that studies the interaction of nutrients with genome and gene expression. Nutrigenetics is another field that examines the effects of genetic differences on diet-disease relation. The human genome project has brought in the concept of personalized nutrition, pointing out the individual differences between humans. Personalized nutrition tries to achieve health through genotype-based dietary interventions to prevent diet-related diseases and improve life quality. The reasons of genetic differences leading to the necessity of personalized nutrition are as genetic polymorphisms, epigenetic and epistatic interactions. Current techniques used in nutritional genomics; proteomics, metabolics and transcriptomics help to reveal genetic differences. In this review, we provide an overview of personalized nutrition from our point of view by describing the causes leading to this concept and the current techniques used in this field.
  • [Show abstract] [Hide abstract]
    ABSTRACT: Breast cancer is the most common cancer and the second leading cause of death in women worldwide. The disease is caused by a combination of genetic, environmental, lifestyle, and reproductive risk factors. Linkage and family-based studies have identified many pathological germline mutations, which account for around 20% of the genetic risk of familial breast cancer. In recent years, single nucleotide polymorphism-based genetic association studies, especially genome-wide association studies (GWASs), have been very successful in uncovering low-penetrance common variants associated with breast cancer risk. These common variants alone may explain up to an additional 30% of the familial risk of breast cancer. With the advent of available genetic resources and growing collaborations among researchers across the globe, the much needed large sample size to capture variants with small effect sizes and low population frequencies is being addressed, and hence many more common variants are expected to be discovered in the coming days. Here, major GWASs conducted for breast cancer predisposition and prognosis until 2013 are summarized. Few studies investigating other forms of genetic variations contributing to breast cancer predisposition and disease outcomes are also discussed. Finally, the potential utility of the GWAS-identified variants in disease risk models and some future perspectives are presented. © 2014 S. Karger AG, Basel.
    Cytogenetic and Genome Research 11/2014; 144(2):77-91. DOI:10.1159/000369045 · 1.91 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Best practice for statistical methodology in cell-based dose-response studies has yet to be established. We examine the ability of MANOVA to detect trait-associated genetic loci in the presence of gene-gene interactions. We present a novel Bayesian nonparametric method designed to detect such interactions. MANOVA and the Bayesian nonparametric approach show good ability to detect trait-associated genetic variants under various possible genetic models. It is shown through several sets of analyses that this may be due to marginal effects being present, even if the underlying genetic model does not explicitly contain them. Understanding how genetic interactions affect drug response continues to be a critical goal. MANOVA and the novel Bayesian framework present a trade-off between computational complexity and model flexibility.
    BioData Mining 01/2015; 8:6. DOI:10.1186/s13040-015-0039-3 · 1.54 Impact Factor

Preview

Download
0 Downloads
Available from