Comparative analysis of genome-wide association studies signals for lipids, diabetes, and coronary heart disease: Cardiovascular Biomarker Genetics Collaboration

Angelakopoulou, Aspasia, Shah, Tina, Sofat, Reecha, Shah, Sonia, Berry, Diane J., Cooper, Jackie, Palmen, Jutta, Tzoulaki, Ioanna, Wong, Andrew, Jefferis, Barbara J., Maniatis, Nikolas, Drenos, Fotios, Gigante, Bruna, Hardy, Rebecca, Laxton, Ross C., Leander, Karin, Motterle, Anna, Simpson, Iain A., Smeeth, Liam, Thomson, Andy, Verzilli, Claudio, Kuh, Diana, Ireland, Helen, Deanfield, John, Caulfield, Mark, Wallace, Chris, Samani, Nilesh, Munroe, Patricia B., Lathrop, Mark, Fowkes, F. Gerry R., Marmot, Michael, Whincup, Peter H., Whittaker, John C., de Faire, Ulf, Kivimaki, Mika, Kumari, Meena, Hypponen, Elina, Power, Chris, Humphries, Steve E., Talmud, Philippa J., Price, Jackie, Morris, Richard W., Ye, Shu, Casas, Juan P. and Hingorani, Aroon D. (2012) Comparative analysis of genome-wide association studies signals for lipids, diabetes, and coronary heart disease: Cardiovascular Biomarker Genetics Collaboration. European Heart Journal, 33 3: 393-407. doi:10.1093/eurheartj/ehr225


Author Angelakopoulou, Aspasia
Shah, Tina
Sofat, Reecha
Shah, Sonia
Berry, Diane J.
Cooper, Jackie
Palmen, Jutta
Tzoulaki, Ioanna
Wong, Andrew
Jefferis, Barbara J.
Maniatis, Nikolas
Drenos, Fotios
Gigante, Bruna
Hardy, Rebecca
Laxton, Ross C.
Leander, Karin
Motterle, Anna
Simpson, Iain A.
Smeeth, Liam
Thomson, Andy
Verzilli, Claudio
Kuh, Diana
Ireland, Helen
Deanfield, John
Caulfield, Mark
Wallace, Chris
Samani, Nilesh
Munroe, Patricia B.
Lathrop, Mark
Fowkes, F. Gerry R.
Marmot, Michael
Whincup, Peter H.
Whittaker, John C.
de Faire, Ulf
Kivimaki, Mika
Kumari, Meena
Hypponen, Elina
Power, Chris
Humphries, Steve E.
Talmud, Philippa J.
Price, Jackie
Morris, Richard W.
Ye, Shu
Casas, Juan P.
Hingorani, Aroon D.
Title Comparative analysis of genome-wide association studies signals for lipids, diabetes, and coronary heart disease: Cardiovascular Biomarker Genetics Collaboration
Journal name European Heart Journal   Check publisher's open access policy
ISSN 0195-668X
1522-9645
Publication date 2012
Sub-type Article (original research)
DOI 10.1093/eurheartj/ehr225
Open Access Status
Volume 33
Issue 3
Start page 393
End page 407
Total pages 15
Place of publication Oxford, United Kingdom
Publisher Oxford University Press
Language eng
Formatted abstract
Aims: To evaluate the associations of emergent genome-wide-association study-derived coronary heart disease (CHD)-associated single nucleotide polymorphisms (SNPs) with established and emerging risk factors, and the association of genome-wide-association study-derived lipid-associated SNPs with other risk factors and CHD events.

Methods and results: Using two casecontrol studies, three cross-sectional, and seven prospective studies with up to 25 000 individuals and 5794 CHD events we evaluated associations of 34 genome-wide-association study-identified SNPs with CHD risk and 16 CHD-associated risk factors or biomarkers. The Ch9p21 SNPs rs1333049 (OR 1.17; 95 confidence limits 1.111.24) and rs10757274 (OR 1.17; 1.091.26), MIA3 rs17465637 (OR 1.10; 1.041.15), Ch2q36 rs2943634 (OR 1.08; 1.031.14), APC rs383830 (OR 1.10; 1.02, 1.18), MTHFD1L rs6922269 (OR 1.10; 1.03, 1.16), CXCL12 rs501120 (OR 1.12; 1.04, 1.20), and SMAD3 rs17228212 (OR 1.11; 1.05, 1.17) were all associated with CHD risk, but not with the CHD biomarkers and risk factors measured. Among the 20 blood lipid-related SNPs, LPL rs17411031 was associated with a lower risk of CHD (OR 0.91; 0.840.97), an increase in Apolipoprotein AI and HDL-cholesterol, and reduced triglycerides. SORT1 rs599839 was associated with CHD risk (OR 1.20; 1.151.26) as well as total-and LDL-cholesterol, and apolipoprotein B. ANGPTL3 rs12042319 was associated with CHD risk (OR 1.11; 1.03, 1.19), total-and LDL-cholesterol, triglycerides, and interleukin-6.

Conclusion: Several SNPs predicting CHD events appear to involve pathways not currently indexed by the established or emerging risk factors; others involved changes in blood lipids including triglycerides or HDL-cholesterol as well as LDL-cholesterol. The overlapping association of SNPs with multiple risk factors and biomarkers supports the existence of shared points of regulation for these phenotypes.
Keyword Coronary disease
Genes
Lipids
Risk factors
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: Queensland Brain Institute Publications
 
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