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Updated: May 26, 2026
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Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)
Published on: August 21, 2016
Common Variants in 6 Lipid-Related Genes Discovered by High-Resolution DNA Melting Analysis and Their Association
John F Carlquist1, Jason T McKinney, Benjamin D Horne
1Cardiovascular Department, Intermountain Healthcare, USA.
Journal of Clinical & Experimental Cardiology
|January 10, 2012
Summary
Researchers identified genetic variants in lipid metabolism genes to assess coronary heart disease (CHD) risk. Hi-Res Melting analysis proved effective for SNP discovery, aiding in predicting CHD risk based on lipid profiles.
Area of Science:
- Genetics
- Cardiovascular Disease Research
- Biochemistry
Background:
- Total cholesterol is a known risk factor for coronary heart disease (CHD).
- Genetic contributions to lipid metabolism and CHD risk require further elucidation.
- Identifying specific genetic variants can refine risk assessment.
Purpose of the Study:
- To identify genetic variants in six key lipid metabolism genes.
- To evaluate the contribution of these variants to coronary heart disease risk.
- To assess the utility of Hi-Res Melting analysis for variant discovery.
Main Methods:
- Scanned six lipid-associated genes (LCAT, CETP, LIPC, LPL, SCARB1, ApoF) for variants using Hi-Res Melting analysis (HRMCA).
- Confirmed variants via cycle sequencing in healthy subjects for SNP discovery, haplotype determination, and lipid association testing.
- Utilized HRMCA for high-throughput SNP discovery with high sensitivity and specificity.
Main Results:
- Identified 90 single nucleotide polymorphisms (SNPs), including 19 novel variants, across 17,840 bases.
- HRMCA demonstrated high sensitivity (99.4%) and specificity (97.7%) compared to cycle sequencing.
- Specific linkage disequilibrium (LD) groups within CETP, LIPC, and SCARB1 genes were associated with beneficial lipid profiles, while others indicated increased risk.
Conclusions:
- HRMCA is a feasible, sensitive, and specific method for SNP discovery in lipid metabolism genes.
- Identified genetic variants can potentially predict lipid-associated risk and reclassify clinical CHD risk.
- This research provides a foundation for personalized risk assessment in cardiovascular disease.
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