Common Variants in 6 Lipid-Related Genes Discovered by High-Resolution DNA Melting Analysis and Their Association with Plasma Lipids.
Common Variants in 6 Lipid-Related Genes Discovered by High-Resolution DNA Melting Analysis and Their Association with Plasma Lipids.
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DOI：
10.4172/2155-9880.1000138
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发表时间：
2011-07
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通讯作者：
J. Carlquist;J. Mckinney;B. Horne;N. Camp;L. Cannon-Albright;J. Muhlestein;P. Hopkins;Jessica L. Clarke;Chrissa P. Mower;James J. Park;Zachary P. Nicholas;John A. Huntinghouse;Jeffrey L. Anderson
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文献类型：
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作者：
J. Carlquist;J. Mckinney;B. Horne;N. Camp;L. Cannon-Albright;J. Muhlestein;P. Hopkins;Jessica L. Clarke;Chrissa P. Mower;James J. Park;Zachary P. Nicholas;John A. Huntinghouse;Jeffrey L. Anderson
背景：总胆固醇是最早确定的冠心病危险因素之一。我们试图确定与脂质代谢相关的六个基因的遗传变异，并估计其各自对冠心病风险的贡献。方法：对于6个脂质相关基因（LCAT、CETP、LIPC、LPL、SCARB 1和ApoF），我们使用Hi-Res Melting®曲线分析（HRMCA）扫描外显子、5'和3'非翻译区以及供体和受体剪接位点的变体，并通过循环测序进行确认。健康受试者用于SNP发现（n=64）、单倍型确定/标记SNP发现（n=339）和脂质关联测试（n=786）。结果：在17，840个碱基的查询序列中，鉴定出90个变异SNP; 19个（21.1%）以前未报道。外显子变异34个（37.8%）（16个非同义），28个（31.1%）位于内含子-外显子边界，28个（31.1%）位于5'和3'非翻译区。与循环测序相比，HRMCA的敏感性为99.4%，特异性为97.7%。标记SNPs（n=38）解释了6个基因中>90%的变异，并确定了连锁不平衡（LD）组。在CETP LD组2、LIPC LD组1和7以及SCARB 1 LD组1、3和4中观察到显著有益的脂质谱。CETP LD组3和LPL LD组4的风险特征恶化。结论：这些发现证明了HRMCA用于SNP发现的可行性、敏感性和特异性。在这些基因中发现的变异可用于预测脂质相关风险和临床CHD风险的重新分类。
BACKGROUND: Total cholesterol was among the earliest identified risk factors for coronary heart disease (CHD). We sought to identify genetic variants in six genes associated with lipid metabolism and estimate their respective contribution to risk for CHD. METHODS: For 6 lipid-associated genes (LCAT, CETP, LIPC, LPL, SCARB1, and ApoF) we scanned exons, 5' and 3' untranslated regions, and donor and acceptor splice sites for variants using Hi-Res Melting® curve analysis (HRMCA) with confirmation by cycle sequencing. Healthy subjects were used for SNP discovery (n=64), haplotype determination/tagging SNP discovery (n=339), and lipid association testing (n=786). RESULTS: In 17,840 bases of interrogated sequence, 90 variant SNPs were identified; 19 (21.1%) previously unreported. Thirty-four variants (37.8%) were exonic(16 non-synonymous), 28 (31.1%) in intron-exon boundaries, and 28 (31.1%) in the 5' and 3' untranslated regions. Compared to cycle sequencing, HRMCA had sensitivity of 99.4% and specificity of 97.7%. Tagging SNPs (n=38) explained >90% of the variation in the 6 genes and identified linkage disequilibrium (LD) groups. Significant beneficial lipid profiles were observed for CETP LD group 2, LIPC LD groups 1 and 7, and SCARB1 LD groups 1, 3 and 4. Risk profiles worsened for CETP LD group 3, LPL LD group 4. CONCLUSIONS: These findings demonstrate the feasibility, sensitivity, and specificity of HRMCA for SNP discovery. Variants identified in these genes may be used to predict lipid-associated risk and reclassification of clinical CHD risk.