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Related Concept Videos

Principles of Pharmacogenetics: Types of Genetic Variants01:27

Principles 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...
Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: 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...
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...
Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu01:29

Pharmacogenetic 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...
Incomplete Dominance01:43

Incomplete Dominance

Gregor Mendel's work (1822 - 1884) was primarily focused on pea plants. Through his initial experiments, he determined that every gene in a diploid cell has two variants called alleles inherited from each parent. He suggested that amongst these two alleles, one allele is dominant in character and the other recessive. The combination of alleles determines the phenotype of a gene in an organism.
Pedigree Analysis01:35

Pedigree Analysis

Overview

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Related Experiment Video

Updated: May 8, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Considerations for subgroups and phenocopies in complex disease genetics.

Ryan Ramanujam1, S Ramanujam, Jan Hillert

  • 1Department of Clinical Neuroscience, Karolinska Institutet at Karolinska University Hospital Solna, Stockholm, Sweden.

Plos One
|August 27, 2013
PubMed
Summary

Complex diseases like multiple sclerosis (MS) may have hidden genetic associations within subgroups. This study provides methods to calculate true genetic effects, potentially explaining heritability gaps and uncovering significant findings in heterogeneous diseases.

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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
09:34

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

Area of Science:

  • Genetics
  • Biostatistics
  • Complex Disease Research

Background:

  • Identified genetic variants often fail to fully explain the heritability of complex diseases.
  • Complex diseases like multiple sclerosis (MS) may involve multiple underlying disease mechanisms and subgroups.
  • Existing association measurements may obscure true genetic effects due to disease heterogeneity.

Purpose of the Study:

  • To develop a methodology for calculating true genetic associations within disease subgroups.
  • To extend these calculations to the chi-squared (χ(2)) statistic for scenarios involving phenocopies and heterogeneity.
  • To provide a framework for re-evaluating genetic associations in complex diseases with suspected subgroup effects.

Main Methods:

  • The study proposes manipulating the odds ratio to calculate subgroup-specific genetic associations, considering minor allele frequencies.
  • The methodology is extended to the χ(2) statistic, offering formulas for scenarios with phenocopy misclassification and subgroup heterogeneity.
  • A Python script is provided for calculating and visualizing the required sample size increase due to subgroup effects.

Main Results:

  • The proposed method can reveal significant genetic associations within subgroups that are masked in the overall population.
  • In a simulated study, a non-significant single nucleotide polymorphism (SNP) reached genome-wide significance when analyzed within a 20% subgroup of cases.
  • The calculations are sensitive to initial minor allele frequencies and the proportion of cases within subgroups.

Conclusions:

  • This methodology offers a way to address the heritability gap by uncovering complex genetic patterns.
  • It provides a potential explanation for modest genetic associations observed in heterogeneous diseases like MS.
  • The findings emphasize the importance of considering subgroup analysis in genetic association studies for complex diseases.