Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Gene-environment interaction and affected sib pair linkage analysis.

W J Gauderman1, K D Siegmund

  • 1Department of Preventive Medicine, University of Southern California, 1540 Alcazar Street, Los Angeles, CA 90089, USA. jimg@usc.edu

Human Heredity
|May 19, 2001
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Comprehensive epigenomic profiling of human alveolar epithelial differentiation identifies key epigenetic states and transcription factor co-regulatory networks for maintenance of distal lung identity.

BMC genomics·2021
Same author

The Effects of Policy-Driven Air Quality Improvements on Children's Respiratory Health.

Research report (Health Effects Institute)·2020
Same author

Air pollution, weight loss and metabolic benefits of bariatric surgery: a potential model for study of metabolic effects of environmental exposures.

Pediatric obesity·2017
Same author

Genetic variations in nitric oxide synthase and arginase influence exhaled nitric oxide levels in children.

Allergy·2010
Same author

Glutathione-S-transferase (GST) P1, GSTM1, exercise, ozone and asthma incidence in school children.

Thorax·2008
Same author

DNA methylation profiles in diffuse large B-cell lymphoma and their relationship to gene expression status.

Leukemia·2008

Incorporating gene-environment (GxE) interaction into linkage analysis significantly boosts power for detecting disease genes. A new mean-interaction test improves detection compared to traditional methods ignoring environmental factors.

Area of Science:

  • Genetics
  • Biostatistics
  • Epidemiology

Background:

  • Complex diseases often result from gene-environment (GxE) interactions.
  • Genome-wide screens typically do not account for GxE interactions.
  • Affected sib pair linkage analysis is a common method for gene discovery.

Purpose of the Study:

  • To propose and evaluate a novel statistical test for linkage analysis that incorporates GxE interactions.
  • To assess the power of the proposed test compared to standard methods.

Main Methods:

  • Developed a "mean-interaction" test extending the standard mean test.
  • Calculated expected identity-by-descent (IBD) sharing based on sibling exposure status (EE, UU, EU).
  • Evaluated test power for various GxE interaction scenarios.

Related Experiment Videos

Main Results:

  • The mean-interaction test demonstrated superior power over the mean test for detecting linkage with moderate to strong GxE.
  • Increased power was observed when the interaction relative risk (R(ge)) exceeded 3 or was less than 1/3.
  • For strong interaction (R(ge)=10), the mean-interaction test required ~30% fewer affected sib pairs for 80% power compared to the mean test.

Conclusions:

  • Linkage methods that integrate environmental data and GxE interactions enhance the ability to localize disease genes.
  • This approach is particularly beneficial for complex diseases influenced by GxE.
  • The mean-interaction test offers a more powerful tool for genetic association studies.