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 Concept Videos

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

12.6K
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...
12.6K
Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

121
Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
121
Genetic Screens02:46

Genetic Screens

4.6K
Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which...
4.6K
Epistasis Analysis01:09

Epistasis Analysis

4.9K
Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
4.9K
Pharmacogenetics and Pharmacogenomics: Overview01:29

Pharmacogenetics and Pharmacogenomics: Overview

253
Pharmacogenetics and pharmacogenomics examine how genetic factors influence an individual's response to drugs. While pharmacogenetics focuses on the impact of specific genetic variants on drug effects, pharmacogenomics takes a broader approach, studying how genetic variation across populations contributes to differences in drug responses. These fields aim to explain why individuals may experience varying levels of efficacy or adverse reactions to the same medication.Variability in drug...
253
Protein Networks02:26

Protein Networks

3.7K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
3.7K

You might also read

Related Articles

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

Sort by
Same author

Longitudinal Blood DNA Methylation Changes During Weight-Loss Intervention and Dementia Progression Risk.

Research square·2026
Same author

Genome wide association study meta-analysis of neuropathologic lesions of Alzheimer's disease and related dementias in a multi-site autopsy cohort.

PLoS genetics·2026
Same author

Heritability of Alzheimer's disease-related plasma biomarkers in the Amish population.

Alzheimer's & dementia (Amsterdam, Netherlands)·2026
Same author

From aging to Alzheimer's disease: concordant brain DNA methylation changes in late life.

Genome medicine·2026
Same author

Blood DNA methylation signature of cognitive reserve moderates the association between CSF tau pathology and memory in prodromal Alzheimer's disease.

Alzheimer's & dementia (New York, N. Y.)·2026
Same author

Genetic correlation analysis of Alzheimer's disease and stroke implicates PHLPP1 as a shared locus in individuals of African ancestry.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2026

Related Experiment Video

Updated: May 1, 2026

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
05:01

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

Published on: July 1, 2020

4.7K

Detecting genetic interactions in pathway-based genome-wide association studies.

Anhui Huang1, Eden R Martin, Jeffery M Vance

  • 1Department of Electrical and Computer Engineering, University of Miami, Coral Gables, Florida, United States of America.

Genetic Epidemiology
|April 11, 2014
PubMed
Summary
This summary is machine-generated.

This study introduces a new Bayesian method to analyze genetic pathways, detecting both individual and interacting gene effects. The approach successfully identified key pathways in Parkinson's disease, highlighting epistatic interactions.

Keywords:
GWASParkinson diseaseepistasisgroup EBlassopathway

More Related Videos

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
14:06

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

46.1K
A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions
13:56

A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions

Published on: July 18, 2013

10.6K

Related Experiment Videos

Last Updated: May 1, 2026

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
05:01

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

Published on: July 1, 2020

4.7K
Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
14:06

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Published on: November 12, 2012

46.1K
A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions
13:56

A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions

Published on: July 18, 2013

10.6K

Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Pathway-based genome-wide association studies (GWAS) enhance detection power by analyzing collective effects of causal variants.
  • Existing pathway-based GWAS methods often overlook epistatic effects (interactions between genetic variants), which are crucial for complex traits.

Purpose of the Study:

  • To develop a novel pathway-based GWAS method incorporating both main and pairwise epistatic effects of genetic variants.
  • To improve the detection of genetic associations in complex diseases by accounting for gene-gene interactions.

Main Methods:

  • Employed a Bayesian Lasso logistic regression model for pathway-based GWAS.
  • Utilized an efficient group empirical Bayesian Lasso (EBLasso) method for model inference.
  • Applied Wald statistics for pathway significance testing and stability selection for effect identification.

Main Results:

  • The group EBLasso method demonstrated superior performance compared to two competitive methods in extensive computer simulations.
  • Application to a Parkinson disease GWAS dataset identified three significant pathways: primary bile acid biosynthesis, neuroactive ligand-receptor interaction, and MAPK signaling.
  • A significant portion of the identified effects, particularly in the primary bile acid biosynthesis pathway, were epistatic.

Conclusions:

  • The group EBLasso method is a valuable tool for pathway-based GWAS, capable of identifying both main and epistatic genetic effects.
  • The findings underscore the importance of considering gene-gene interactions in understanding complex traits and diseases like Parkinson's.