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Related Concept Videos

Genome-wide Association Studies-GWAS01:11

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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.
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When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
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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,...
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Pharmacogenomics: Identification of New Drug Targets01:29

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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...
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Principles of Pharmacogenetics: Types of Genetic Variants01:27

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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...
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The odds ratio (OR) is a statistical measure used extensively in epidemiology and research to quantify the strength of association between exposure and outcome across different groups. Unlike relative risk, which compares the probabilities of an event occurring, the odds ratio compares the odds of an event occurring in the exposed group to the odds of it occurring in the unexposed group. The odds, in this context, are calculated as the probability of the event happening divided by the...
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Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
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How Can We Explain Very Low Odds Ratios in GWAS? I. Polygenic Models.

Susan E Hodge1, David A Greenberg

  • 1Battelle Center for Mathematical Medicine, The Research Institute, Nationwide Children's Hospital, and Department of Pediatrics, The Ohio State University, Columbus, OH, USA.

Human Heredity
|February 8, 2017
PubMed
Summary
This summary is machine-generated.

Common diseases often show statistically significant single nucleotide polymorphisms (SNPs) with low odds ratios (ORs). A polygenic inheritance model is incompatible with these low ORs unless hundreds of genes are involved.

Keywords:
Case-control association analysisComplex disorderGWASGenetic heterogeneityGenome-wide scanLinkage disequilibriumOdds ratiosPolygenic inheritanceStatistical genetics

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Area of Science:

  • Genetics
  • Population Genetics
  • Disease Inheritance

Background:

  • Genome-wide association studies (GWAS) frequently detect significant single nucleotide polymorphisms (SNPs) for common diseases.
  • These significant SNPs often exhibit very low odds ratios (ORs), typically below 1.5, explaining minimal disease risk.
  • The low ORs limit understanding of genetic contributions and inheritance patterns for complex diseases.

Purpose of the Study:

  • To investigate the compatibility of polygenic inheritance models with low odds ratios (ORs) observed in GWAS.
  • To determine the number of genetic loci required under a polygenic model to explain low ORs in common diseases.

Main Methods:

  • Statistical modeling of genetic association data.
  • Analysis of the relationship between odds ratios, disease prevalence, and the number of contributing genetic loci.
  • Evaluation of polygenic inheritance models under varying population prevalences (≤10%).

Main Results:

  • A pure polygenic inheritance model is generally incompatible with very low odds ratios (ORs) for common diseases.
  • Compatibility requires a large number of contributing genetic loci, potentially hundreds or thousands.
  • This finding challenges the common explanation for low ORs in GWAS findings.

Conclusions:

  • The prevalence of very low ORs in GWAS may indicate limitations in the pure polygenic model for common diseases.
  • A substantial number of interacting genes may be necessary to explain the genetic architecture of diseases with low SNP effect sizes.
  • Further research is needed to refine models of complex disease genetics and inheritance.