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Updated: Jun 23, 2026
11:35
Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)
Published on: August 21, 2016
Genetic variants associated with complex human diseases show wide variation across multiple populations
1Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892-5635, USA. adeyemoa@mail.nih.gov
Public Health Genomics
|May 15, 2009
Summary
Genetic risk variants for complex diseases show significant frequency differences across global populations. Understanding this variation is crucial for equitable genomic research and public health initiatives.
Area of Science:
- Genetics
- Population Genetics
- Genomics
Background:
- Genome-Wide Association Studies (GWAS) identify genetic variants linked to complex diseases.
- Limited data exists on genetic variation in non-European populations.
- Investigating population variation in disease susceptibility loci is essential.
Purpose of the Study:
- To analyze population variation in genetic susceptibility loci identified by GWAS.
- To assess allele frequencies and population differentiation across diverse ethnic groups.
Main Methods:
- Utilized data from the International HapMap Project Phase 3 (11 population groups).
- Estimated allele frequencies at loci associated with 26 complex diseases and traits.
- Calculated F(ST) statistics to measure population differentiation.
Main Results:
- Observed substantial variation in allele frequencies (20- to 40-fold differences) across populations.
- Demonstrated wide-ranging F(ST) values, indicating significant population differentiation for disease loci.
- Specific examples include type 2 diabetes, prostate cancer, and serum lipid levels.
Conclusions:
- Allele frequencies significantly influence public health risks across populations.
- Gene-gene and gene-environment interactions may amplify these risk differences.
- Inclusion of diverse global populations is vital for genomic research and understanding disease distribution.
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