Related Experiment Video
Updated: May 21, 2026
05:53
Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
Published on: June 21, 2018
Highly interconnected genes in disease-specific networks are enriched for disease-associated polymorphisms
Fredrik Barrenäs1, Sreenivas Chavali, Alexessander Couto Alves
1The Centre for Individualized Medication, Linköping University Hospital, Linköping University, Linköping, Sweden.
Genome Biology
|June 19, 2012
Summary
This study introduces a new method to find key genes in complex diseases. The approach identifies gene modules linked to disease-associated genetic variations, aiding in the discovery of novel disease genes.
Area of Science:
- Genetics
- Systems Biology
- Bioinformatics
Background:
- Complex diseases involve intricate interactions among numerous genes.
- Identifying critical disease-associated genes remains a significant challenge in human genetics.
Purpose of the Study:
- To develop and validate a novel computational method for identifying and prioritizing genes implicated in complex diseases.
- To assess the utility of identified gene modules for discovering novel disease-associated genes.
Main Methods:
- Integrated gene expression and protein-protein interaction data to construct disease-specific gene networks.
- Identified highly interconnected gene modules within these networks.
- Analyzed enrichment of disease-associated single nucleotide polymorphisms (SNPs) within identified modules.
- Validated findings using gene expression microarray and genome-wide association study (GWAS) data for seasonal allergic rhinitis.
Main Results:
- Modules of highly interconnected genes were identified in 13 diverse complex diseases.
- These modules were significantly enriched for genes harboring disease-associated SNPs.
- A novel gene, FGF2, was identified for seasonal allergic rhinitis and validated through functional studies.
- Overlapping modules across diseases suggested a general susceptibility to complex diseases, confirmed by enrichment with GWAS genes for 145 other conditions.
Conclusions:
- The developed method effectively identifies modules of interconnected genes associated with complex diseases.
- These gene modules serve as a valuable resource for prioritizing disease genes and discovering novel candidates for functional studies.
Related Concept Videos
01:11Genome-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...
GWAS does not require the identification of the target gene involved in...
02:26Protein Networks
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,...
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,...
01:05Single Nucleotide Polymorphisms-SNPs
A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
01:29Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu
Genetic variations significantly influence drug response through pharmacokinetics, receptor interactions, and biologic milieu modifications. Pharmacokinetic alterations impact drug metabolism and clearance, affecting efficacy and toxicity. Variants in drug-metabolizing enzymes, such as CYP2C9 and CYP2C19, alter drug activation and elimination. For example, CYP2C9 loss-of-function variants require lower warfarin doses to prevent excessive bleeding, while CYP2C19 variants reduce clopidogrel...
01:29Pharmacogenomics: Identification of New Drug Targets
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...
01:27Principles of Pharmacogenetics: Types of Genetic Variants
The human genome is over 99.9% identical between individuals, yet genetic differences exist at millions of bases. The human genome contains approximately 3 million variant positions per individual, many of which are heterozygous, contributing to genetic diversity and individual traits. Genetic variations include single-nucleotide polymorphisms (SNPs), insertions, deletions, and copy number variations (CNVs).SNPs, the most common variation, involve single-base changes in DNA. These can be...