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.
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.
Authors: B D Horne; J B Muhlestein; J F Carlquist; T L Bair; T E Madsen; N I Hart; J L Anderson Journal: J Am Coll Cardiol Date: 2000-11-15 Impact factor: 24.094
Authors: Hua Tang; Tom Quertermous; Beatriz Rodriguez; Sharon L R Kardia; Xiaofeng Zhu; Andrew Brown; James S Pankow; Michael A Province; Steven C Hunt; Eric Boerwinkle; Nicholas J Schork; Neil J Risch Journal: Am J Hum Genet Date: 2004-12-29 Impact factor: 11.025
Authors: Lillian L C Khor; Joseph B Muhlestein; John F Carlquist; Benjamin D Horne; Tami L Bair; Chloe A Maycock; Jeffrey L Anderson Journal: Am J Med Date: 2004-11-01 Impact factor: 4.965
Authors: Alexander Thompson; Emanuele Di Angelantonio; Nadeem Sarwar; Sebhat Erqou; Danish Saleheen; Robin P F Dullaart; Bernard Keavney; Zheng Ye; John Danesh Journal: JAMA Date: 2008-06-18 Impact factor: 56.272
Authors: D A Nickerson; S L Taylor; K M Weiss; A G Clark; R G Hutchinson; J Stengård; V Salomaa; E Vartiainen; E Boerwinkle; C F Sing Journal: Nat Genet Date: 1998-07 Impact factor: 38.330
Authors: Cristen J Willer; Serena Sanna; Anne U Jackson; Angelo Scuteri; Lori L Bonnycastle; Robert Clarke; Simon C Heath; Nicholas J Timpson; Samer S Najjar; Heather M Stringham; James Strait; William L Duren; Andrea Maschio; Fabio Busonero; Antonella Mulas; Giuseppe Albai; Amy J Swift; Mario A Morken; Narisu Narisu; Derrick Bennett; Sarah Parish; Haiqing Shen; Pilar Galan; Pierre Meneton; Serge Hercberg; Diana Zelenika; Wei-Min Chen; Yun Li; Laura J Scott; Paul A Scheet; Jouko Sundvall; Richard M Watanabe; Ramaiah Nagaraja; Shah Ebrahim; Debbie A Lawlor; Yoav Ben-Shlomo; George Davey-Smith; Alan R Shuldiner; Rory Collins; Richard N Bergman; Manuela Uda; Jaakko Tuomilehto; Antonio Cao; Francis S Collins; Edward Lakatta; G Mark Lathrop; Michael Boehnke; David Schlessinger; Karen L Mohlke; Gonçalo R Abecasis Journal: Nat Genet Date: 2008-01-13 Impact factor: 38.330