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Related Concept Videos

Gene-Environment Interactions01:20

Gene-Environment Interactions

Gene expression is a dynamic process that is significantly influenced by environmental factors. This interaction underlies the complex nature of biological development and the phenotypic differences observed among individuals, even among those with identical genetic makeups. Factors such as radiation, temperature, behavior, nutrition, and stress play pivotal roles in determining how genes are expressed. The concept of the reaction range is central to understanding this interaction. It posits...
Background and Environment Affect Phenotype02:27

Background and Environment Affect Phenotype

Although the genetic makeup of an organism plays a major role in determining the phenotype, there are also several environmental factors, such as temperature, oxygen availability, presence of mutagens, that can alter an organism’s phenotype.
An example of how genetic background affects phenotype can be seen in horses. The Extension gene in horses is responsible for their coat color. A wild-type gene (EE) produces black pigment in the coat, while a mutant gene (ee) produces red pigment. A...
Behavioral Genetics and Its Designs01:23

Behavioral Genetics and Its Designs

Behavior genetics explores how genetic inheritance influences human behavior. It focuses on how genes, passed from parents to offspring, contribute to the development of behavioral traits and tendencies. This branch of genetics seeks to understand the complex interplay between inherited genetic factors and environmental influences in shaping our behaviors.
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Genetic Screens02:46

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Forward genetic screens
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Human Genetics01:28

Human Genetics

Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
The complex relationship between genetics and psychology is observable through common biological components such...
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

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Gene-environment Interaction Models to Unmask Susceptibility Mechanisms in Parkinson's Disease
08:09

Gene-environment Interaction Models to Unmask Susceptibility Mechanisms in Parkinson's Disease

Published on: January 7, 2014

Boosting for detection of gene-environment interactions.

H Pashova1, M LeBlanc, C Kooperberg

  • 1Department of Biostatistics, University of Washington, F-600 Health Sciences Building, Campus Mail Stop 357232, Seattle, Washington 98195, USA. hpashova@u.washington.edu

Statistics in Medicine
|July 6, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a new boosting method to find gene-environment interactions, identifying multiple environmental factors that jointly influence a phenotype. The method shows improved performance in simulations and real-world genetic association studies.

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Area of Science:

  • Genetics
  • Biostatistics
  • Computational Biology

Background:

  • Traditional gene-environment interaction studies often examine one environmental variable at a time.
  • Multiple environmental factors may collectively influence genetic effects on phenotypes.
  • Existing methods may not effectively capture complex gene-environment interplay.

Purpose of the Study:

  • To develop a novel L(2) boosting method for identifying combinations of environmental variables that jointly modify gene effects.
  • To enhance the detection of gene-environment interactions in genetic association studies.
  • To improve the understanding of how multiple environmental factors interact with genes to influence phenotypes.

Main Methods:

  • Developed a variant of L(2) boosting tailored for gene-environment interaction analysis.
  • Focused on an orthogonal space to isolate interaction effects from main genetic effects.
  • Utilized simulation studies and real-world data (Women's Health Initiative-Population Architecture using Genomics and Epidemiology) for validation.

Main Results:

  • The proposed boosting method demonstrated superior performance in simulation studies compared to traditional model selection procedures.
  • Identified two single-nucleotide polymorphisms exhibiting effect modification in the Women's Health Initiative-Population Architecture using Genomics and Epidemiology dataset.
  • Performance evaluation on an independent test set indicated promising results for the developed method.

Conclusions:

  • The novel boosting approach effectively identifies combinations of environmental variables interacting with genes.
  • This method offers a powerful tool for dissecting complex gene-environment relationships in genetic studies.
  • The findings suggest a more nuanced understanding of genetic inheritance influenced by multiple environmental exposures is achievable.