Plasma HDL cholesterol and risk of myocardial infarction: a mendelian randomisation study
Open accessAbstract
Background High plasma HDL cholesterol is associated with reduced risk of myocardial infarction, but whether this association is causal is unclear. Exploiting the fact that genotypes are randomly assigned at meiosis, are independent of non-genetic confounding, and are unmodified by disease processes, mendelian randomisation can be used to test the hypothesis that the association of a plasma biomarker with disease is causal.Methods We performed two mendelian randomisation analyses. First, we used as an instrument a single nucleotide polymorphism (SNP) in the endothelial lipase gene (LIPG Asn396Ser) and tested this SNP in 20 studies (20,913 myocardial infarction cases, 95,407 controls). Second, we used as an instrument a genetic score consisting of 14 common SNPs that exclusively associate with HDL cholesterol and tested this score in up to 12,482 cases of myocardial infarction and 41,331 controls. As a positive control, we also tested a genetic score of 13 common SNPs exclusively associated with LDL cholesterol.Findings Carriers of the LIPG 396Ser allele (2·6% frequency) had higher HDL cholesterol (0·14 mmol/L higher, p=8×10(-13)) but similar levels of other lipid and non-lipid risk factors for myocardial infarction compared with non-carriers. This difference in HDL cholesterol is expected to decrease risk of myocardial infarction by 13% (odds ratio [OR] 0·87, 95% CI 0·84-0·91). However, we noted that the 396Ser allele was not associated with risk of myocardial infarction (OR 0·99, 95% CI 0·88-1·11, p=0·85). From observational epidemiology, an increase of 1 SD in HDL cholesterol was associated with reduced risk of myocardial infarction (OR 0·62, 95% CI 0·58-0·66). However, a 1 SD increase in HDL cholesterol due to genetic score was not associated with risk of myocardial infarction (OR 0·93, 95% CI 0·68-1·26, p=0·63). For LDL cholesterol, the estimate from observational epidemiology (a 1 SD increase in LDL cholesterol associated with OR 1·54, 95% CI 1·45-1·63) was concordant with that from genetic score (OR 2·13, 95% CI 1·69-2·69, p=2×10(-10)).Interpretation Some genetic mechanisms that raise plasma HDL cholesterol do not seem to lower risk of myocardial infarction. These data challenge the concept that raising of plasma HDL cholesterol will uniformly translate into reductions in risk of myocardial infarction.Funding US National Institutes of Health, The Wellcome Trust, European Union, British Heart Foundation, and the German Federal Ministry of Education and Research.
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Mendelian randomization studies support the notion that HDL-C may not be causally related to coronary heart disease risk.
“Mendelian randomization studies further support the notion that HDL-C may not be causally related to CHD risk”
From The Forgotten Lipids: Triglycerides, Remnant Cholesterol, and Atherosclerotic Cardiovascular Disease Risk (2019) · cites this paper as [111]
The Discussion reports that HDL-C-raising genetic variants did not reduce myocardial infarction risk and suggests that plasma HDL-C’s association with myocardial infarction may be indirect. This supports the claim’s cautious causal interpretation, but the study tested myocardial infarction, not the broader category of coronary heart disease outcomes. (LLM, conf=0.85)
Experimental — accuracy not yet measuredMendelian randomization studies do not provide compelling evidence that HDL-C is causally associated with atherosclerotic cardiovascular disease risk.
“In contrast, Mendelian randomization studies do not provide compelling evidence that HDL-C is causally associated with the risk of ASCVD [49,61,62].”
From 2019 ESC/EAS guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk (2019) · cites this paper as [61]
The causative protective role of HDL-C against cardiovascular disease has been questioned by Mendelian randomization studies.
“The causative role of HDL-C for protection against CVD has been questioned in several studies utilizing Mendelian randomization. 87,89,91,92”
From 2016 ESC/EAS Guidelines for the Management of Dyslipidaemias (2016) · cites this paper as [92]
GWAS findings have increasing translational impact through identification of novel therapeutic targets, prioritization and deprioritization of existing targets, and development of polygenic scores that quantify individual genetic risk.
“As described below, findings from GWAS have increasing translational impact through identification of novel therapeutic targets67, prioritization (and deprioritization) of existing ones68 and development of polygenic scores that quantify individual genetic risk69.”
From A brief history of human disease genetics (2020) · cites this paper as [68]
The causative role of HDL-C for protection against CVD has been questioned in several Mendelian randomization studies.
“The causative role of HDL-C for protection against CVD has been questioned in several studies utilizing Mendelian randomization.87,89,91,92”
From 2016 ESC/EAS Guidelines for the Management of Dyslipidaemias (2016) · cites this paper as [92]
Dietary interventions which raise HDL-C may not necessarily translate into CVD risk reduction, as serum HDL-c has recently been called into question regarding its role in the causal pathway of CVD.
“Dietary interventions which raise HDL-C may not necessarily translate into CVD risk reduction, as serum HDL-c has recently been called into question regarding its role in the causal pathway of CVD (110).”
From Food Consumption and its Impact on Cardiovascular Disease: Importance of Solutions Focused on the Globalized Food System (2015) · cites this paper as [110]
MR is being widely applied to quantitative traits with the aim of discovering modifiable risk factors for disease that are causal and amenable to therapeutic modification.
“With increasing availability of large-scale phenotyping (and genotyping), MR is being widely applied to quantitative traits (e.g. markers or adiposity, such as body mass index 13-16 ; blood lipids such as HDL-cholesterol 17-19 ; inflammation-related proteins such as interleukin-6 receptor 20,21 12 ) with the aim of discovering modifiable risk factors for disease that are causal and amenable to the”
From Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development (2021) · cites this paper as [20]
MR has been able to test whether particular elements in the inflammatory response cause or are caused by disease.
“For example, whilst inflammation in general has long been postulated to influence vascular disease 49,50 , MR has been able to test whether particular elements in the inflammatory response cause 20 or are caused by 51 disease.”
From Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development (2021) · cites this paper as [20]
The interleukin 6 receptor (IL6R) is a drug target that alters CRP, and genetic evidence supports a causal role of IL6R in CHD.
“The interleukin 6 receptor (IL6R) is a drug target that alters CRP (see Figure 3 ), and for which genetic evidence supports a causal role of IL6R in CHD 20 54”
From Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development (2021) · cites this paper as [20]
Recent studies have failed to demonstrate that high HDL-C acquired naturally or pharmacologically is associated with reduced CVD risk.
“In contrast, recent studies have failed to demonstrate that high HDL-C acquired naturally or pharmacologically, is associated with reduced CVD risk.5-11,18”
From Is Isolated Low High-Density Lipoprotein Cholesterol a Cardiovascular Disease Risk Factor?: New Insights From the Framingham Offspring Study (2016) · cites this paper as [11]
A Mendelian randomization study failed to identify polymorphisms associated with high HDL-C that correlate with reduced CVD risk.
“Similarly, a Mendelian randomization study failed to identify polymorphisms associated with high HDL-C that correlate with reduced CVD risk.11”
From Is Isolated Low High-Density Lipoprotein Cholesterol a Cardiovascular Disease Risk Factor?: New Insights From the Framingham Offspring Study (2016) · cites this paper as [11]
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Cites
Quantifying heterogeneity in a meta‐analysis
Higgins, J. P. T., & Thompson, S. G. (2002) · Statistics in Medicine · doi:10.1002/sim.1186 · Cited by 36,763 · see citing works
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089 · see citing works
Self-citationExpert Panel on Detection, E. (2001) · JAMA: The Journal of the American Medical Association · doi:10.1001/jama.285.19.2486 · Cited by 26,011 · see citing works
Hulley, S. (1998) · JAMA · doi:10.1001/jama.280.7.605 · Cited by 6,216 · see citing works
Davey Smith, G., & Ebrahim, S. (2003) · International Journal of Epidemiology · doi:10.1093/ije/dyg070 · Cited by 5,882 · see citing works
Mendelian randomization: Using genes as instruments for making causal inferences in epidemiology
Lawlor, D. A., Harbord, R. M., Sterne, J. A. C., Timpson, N., & Davey Smith, G. (2008) · Statistics in Medicine · doi:10.1002/sim.3034 · Cited by 4,618 · see citing works
Biological, clinical and population relevance of 95 loci for blood lipids
Teslovich, T. M., Musunuru, K., Smith, A. V., Edmondson, A. C., Stylianou, I. M., Koseki, M., Pirruccello, J. P., Ripatti, S., Chasman, D. I., Willer, C. J., et al. (2010) · Nature · doi:10.1038/nature09270 · Cited by 3,487 · see citing works
Self-citationSequence Variations in <i>PCSK9,</i> Low LDL, and Protection against Coronary Heart Disease
Cohen, J. C., Boerwinkle, E., Mosley, T. H., & Hobbs, H. H. (2006) · New England Journal of Medicine · doi:10.1056/nejmoa054013 · Cited by 3,181 · see citing works
Self-citationEffects of torcetrapib in patients at high risk for coronary events
Barter, P. J., Caulfield, M., Eriksson, M., Grundy, S. M., Kastelein, J. J. P., Komajda, M., Lopez-Sendon, J., Mosca, L., Tardif, J.-C., Waters, D. D., et al. (2007) · New England Journal of Medicine · doi:10.1056/nejmoa0706628 · Cited by 3,139 · see citing works
Niacin in Patients with Low HDL Cholesterol Levels Receiving Intensive Statin Therapy
The AIM-HIGH Investigators (2011) · New England Journal of Medicine · doi:10.1056/nejmoa1107579 · Cited by 2,911 · see citing works
Major lipids, apolipoproteins, and risk of vascular disease
The Emerging Risk Factors Collaboration* (2009) · JAMA · doi:10.1001/jama.2009.1619 · Cited by 2,731 · see citing works
Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk
The International Consortium for Blood Pressure Genome-Wide Association Studies (2011) · Nature · doi:10.1038/nature10405 · Cited by 2,033 · see citing works
Self-citationCholesterol efflux capacity, high-density lipoprotein function, and atherosclerosis
Khera, A. V., Cuchel, M., de la Llera-Moya, M., Rodrigues, A., Burke, M. F., Jafri, K., French, B. C., Phillips, J. A., Mucksavage, M. L., Wilensky, R. L., et al. (2011) · New England Journal of Medicine · doi:10.1056/nejmoa1001689 · Cited by 1,943 · see citing works
Self-citationLarge-scale association analysis identifies 13 new susceptibility loci for coronary artery disease
Cardiogenics, Schunkert, H., the CARDIoGRAM Consortium, König, I. R., Kathiresan, S., Reilly, M. P., Assimes, T. L., Holm, H., Preuss, M., Stewart, A. F. R., et al. (2011) · Nature Genetics · doi:10.1038/ng.784 · Cited by 1,866 · see citing works
Self-citationNewly identified loci that influence lipid concentrations and risk of coronary artery disease
Willer, C. J., Sanna, S., Jackson, A. U., Scuteri, A., Bonnycastle, L. L., Clarke, R., Heath, S. C., Timpson, N. J., Najjar, S. S., Stringham, H. M., et al. (2008) · Nature Genetics · doi:10.1038/ng.76 · Cited by 1,585 · see citing works
Self-citationCommon variants at 30 loci contribute to polygenic dyslipidemia
Kathiresan, S., Willer, C. J., Peloso, G. M., Demissie, S., Musunuru, K., Schadt, E. E., Kaplan, L., Bennett, D., Li, Y., Tanaka, T., et al. (2009) · Nature Genetics · doi:10.1038/ng.291 · Cited by 1,364 · see citing works
Self-citationUsing multiple genetic variants as instrumental variables for modifiable risk factors
Palmer, T. M., Lawlor, D. A., Harbord, R. M., Sheehan, N. A., Tobias, J. H., Timpson, N. J., Smith, G. D., & Sterne, J. A. (2012) · Statistical Methods in Medical Research · doi:10.1177/0962280210394459 · Cited by 1,289 · see citing works
Mendelian randomization: prospects, potentials, and limitations
Smith, G. D. (2004) · International Journal of Epidemiology · doi:10.1093/ije/dyh132 · Cited by 1,222 · see citing works
Safety of anacetrapib in patients with or at high risk for coronary heart disease
Cannon, C. P., Shah, S., Dansky, H. M., Davidson, M., Brinton, E. A., Gotto, A. M., Stepanavage, M., Liu, S. X., Gibbons, P., Ashraf, T. B., et al. (2010) · New England Journal of Medicine · doi:10.1056/nejmoa1009744 · Cited by 749 · see citing works
Sex hormone-binding globulin and risk of type 2 diabetes in women and men
Ding, E. L., Song, Y., Manson, J. E., Hunter, D. J., Lee, C. C., Rifai, N., Buring, J. E., Gaziano, J. M., & Liu, S. (2009) · New England Journal of Medicine · doi:10.1056/nejmoa0804381 · Cited by 726 · see citing works
Self-citationPolymorphisms Associated with Cholesterol and Risk of Cardiovascular Events
Kathiresan, S., Melander, O., Anevski, D., Guiducci, C., Burtt, N. P., Roos, C., Hirschhorn, J. N., Berglund, G., Hedblad, B., Groop, L., et al. (2008) · New England Journal of Medicine · doi:10.1056/nejmoa0706728 · Cited by 696 · see citing works
Self-citationMonogenic hypercholesterolemia: new insights in pathogenesis and treatment
Rader, D. J., Cohen, J. C., & Hobbs, H. H. (2003) · Journal of Clinical Investigation · doi:10.1172/jci18925 · Cited by 555 · see citing works
Self-citationThompson, A. (2008) · JAMA · doi:10.1001/jama.299.23.2777 · Cited by 494 · see citing works
Monogenic hypercholesterolemia: new insights in pathogenesis and treatment
Rader, D. J., Cohen, J. C., & Hobbs, H. H. (2003) · Journal of Clinical Investigation · doi:10.1172/jci200318925 · Cited by 468 · see citing works
Self-citationFrikke-Schmidt, R. (2008) · JAMA · doi:10.1001/jama.299.21.2524 · Cited by 464 · see citing works
Self-citationAPOUPOPROTEIN E ISOFORMS, SERUM CHOLESTEROL, AND CANCER
Katan, M. (1986) · The Lancet · doi:10.1016/s0140-6736(86)92972-7 · Cited by 371 · see citing works
Endothelial lipase is a major determinant of HDL level
Ishida, T., Choi, S. Y., Kundu, R. K., Hirata, K., Rubin, E. M., Cooper, A. D., & Quertermous, T. (2003) · Journal of Clinical Investigation · doi:10.1172/jci16306 · Cited by 306 · see citing works
Haase, C. L., Tybjærg-Hansen, A., Ali Qayyum, A., Schou, J., Nordestgaard, B. G., & Frikke-Schmidt, R. (2012) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2011-1846 · Cited by 282 · see citing works
Self-citationNitsch, D., Molokhia, M., Smeeth, L. L., Stavola, B. L. D., Whittaker, J. C., & Leon, D. A. (2006) · American Journal of Epidemiology · doi:10.1093/aje/kwj062 · Cited by 228 · see citing works
Loss-of-function variants in endothelial lipase are a cause of elevated HDL cholesterol in humans
Edmondson, A. C., Brown, R., Kathiresan, S., Cupples, L. A., Demissie, S., Manning, A. K., Jensen, M. K., Rimm, E. B., Wang, J., Rodrigues, A., et al. (2009) · Journal of Clinical Investigation · doi:10.1172/jci37176 · Cited by 193 · see citing works
Self-citationHow to avoid bias when comparing bone marrow transplantation with chemotherapy.
Gray, R. G., & Wheatley, K. (1991) · PubMed · Cited by 158 · see citing works
deLemos, A. S., Wolfe, M. L., Long, C., Sivapackianathan, R., & Rader, D. J. (2002) · Circulation · doi:10.1161/01.cir.0000028423.07623.6a · Cited by 138 · see citing works
Self-citationEndothelial Lipase Modulates Susceptibility to Atherosclerosis in Apolipoprotein-E-deficient Mice
Ishida, T., Choi, S. Y., Kundu, R. K., Spin, J. M., Yamashita, T., Hirata, K., Kojima, Y., Yokoyama, M., Cooper, A. D., & Quertermous, T. (2004) · Journal of Biological Chemistry · doi:10.1074/jbc.m406360200 · Cited by 129 · see citing works
Johannsen, T. H., Kamstrup, P. R., Andersen, R. V., Jensen, G. B., Sillesen, H. H., Tybjærg‐Hansen, A., & Nordestgaard, B. G. (2008) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2008-1342 · Cited by 98 · see citing works
Ko, K. W. S., Paul, A., Ma, K., Li, L., & Chan, L. (2005) · Journal of Lipid Research · doi:10.1194/jlr.m500366-jlr200 · Cited by 71 · see citing works
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Bowden, J., Davey Smith, G., Haycock, P. C., & Burgess, S. (2016) · Genetic Epidemiology · doi:10.1002/gepi.21965 · Cited by 8,922 · see citing works
Mach, F., Baigent, C., Catapano, A. L., Koskinas, K. C., Casula, M., Badimon, L., Chapman, M. J., De Backer, G. G., Delgado, V., Ference, B. A., et al. (2019) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2019.08.014 · Cited by 4,854 · see citing works
Self-citationAn atlas of genetic correlations across human diseases and traits
ReproGen Consortium, Bulik-Sullivan, B., Psychiatric Genomics Consortium, Genetic Consortium for Anorexia Nervosa of the Wellcome Trust Case Control Consortium 3, Finucane, H. K., Anttila, V., Gusev, A., Day, F. R., Loh, P.-R., Duncan, L., et al. (2015) · Nature Genetics · doi:10.1038/ng.3406 · Cited by 4,255 · see citing works
Self-citationReading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians
Davies, N. M., Holmes, M. V., & Davey Smith, G. (2018) · BMJ · doi:10.1136/bmj.k601 · Cited by 4,404 · see citing works
Willer (2013) · doi:10.1038/ng.2797 · Cited by 2,983 · see citing works
2016 ESC/EAS Guidelines for the Management of Dyslipidaemias
Catapano, A. L., Graham, I., De Backer, G., Wiklund, O., Chapman, M. J., Drexel, H., Hoes, A. W., Jennings, C. S., Landmesser, U., Pedersen, T. R., et al. (2016) · European Heart Journal · doi:10.1093/eurheartj/ehw272 · Cited by 3,162 · see citing works
Self-citationThe changing landscape of atherosclerosis
Libby, P. (2021) · Nature · doi:10.1038/s41586-021-03392-8 · Cited by 2,873 · see citing works
Sanderson, E., Glymour, M. M., Holmes, M. V., Kang, H., Morrison, J., Munafò, M. R., Palmer, T., Schooling, C. M., Wallace, C., Zhao, Q., et al. (2022) · Nature Reviews Methods Primers · doi:10.1038/s43586-021-00092-5 · Cited by 2,229 · see citing works
Effects of extended-release niacin with laropiprant in high-risk patients
The HPS2-THRIVE Collaborative Group (2014) · New England Journal of Medicine · doi:10.1056/nejmoa1300955 · Cited by 1,668 · see citing works
Burgess, S., & Thompson, S. G. (2015) · American Journal of Epidemiology · doi:10.1093/aje/kwu283 · Cited by 1,605 · see citing works
Borén, J., Chapman, M. J., Krauss, R. M., Packard, C. J., Bentzon, J. F., Binder, C. J., Daemen, M. J., Demer, L. L., Hegele, R. A., Nicholls, S. J., et al. (2020) · European Heart Journal · doi:10.1093/eurheartj/ehz962 · Cited by 1,601 · see citing works
Self-citation2016 ESC/EAS Guidelines for the Management of Dyslipidaemias
Catapano, A. L., Graham, I., De Backer, G., Wiklund, O., Chapman, M. J., Drexel, H., Hoes, A. W., Jennings, C. S., Landmesser, U., Pedersen, T. R., et al. (2016) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2016.08.018 · Cited by 1,582 · see citing works
Self-citationThe Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease
Astle, W. J., Elding, H., Jiang, T., Allen, D., Ruklisa, D., Mann, A. L., Mead, D., Bouman, H., Riveros-Mckay, F., Kostadima, M. A., et al. (2016) · Cell · doi:10.1016/j.cell.2016.10.042 · Cited by 1,224 · see citing works
Self-citationHDL cholesterol efflux capacity and incident cardiovascular events
Rohatgi, A., Khera, A., Berry, J. D., Givens, E. G., Ayers, C. R., Wedin, K. E., Neeland, I. J., Yuhanna, I. S., Rader, D. R., de Lemos, J. A., et al. (2014) · New England Journal of Medicine · doi:10.1056/nejmoa1409065 · Cited by 1,390 · see citing works
Self-citationDietary fats and cardiovascular disease: a presidential advisory from the American Heart Association
Sacks, F. M., Lichtenstein, A. H., Wu, J. H. Y., Appel, L. J., Creager, M. A., Kris-Etherton, P. M., Miller, M., Rimm, E. B., Rudel, L. L., Robinson, J. G., et al. (2017) · Circulation · doi:10.1161/cir.0000000000000510 · Cited by 1,386 · see citing works
Self-citationDetection and interpretation of shared genetic influences on 42 human traits
Pickrell, J. K., Berisa, T., Liu, J. Z., Ségurel, L., Tung, J. Y., & Hinds, D. A. (2016) · Nature Genetics · doi:10.1038/ng.3570 · Cited by 1,151 · see citing works
Wood, A. M., Kaptoge, S., Butterworth, A. S., Willeit, P., Warnakula, S., Bolton, T., Paige, E., Paul, D. S., Sweeting, M., Burgess, S., et al. (2018) · The Lancet · doi:10.1016/s0140-6736(18)30134-x · Cited by 1,188 · see citing works
Self-citationNordestgaard, B. G. (2016) · Circulation Research · doi:10.1161/circresaha.115.306249 · Cited by 1,116 · see citing works
Causal associations between risk factors and common diseases inferred from GWAS summary data
Zhu, Z., Zheng, Z., Zhang, F., Wu, Y., Trzaskowski, M., Maier, R., Robinson, M. R., McGrath, J. J., Visscher, P. M., Wray, N. R., et al. (2018) · Nature Communications · doi:10.1038/s41467-017-02317-2 · Cited by 951 · see citing works
Ference, B. A., Yoo, W., Alesh, I., Mahajan, N., Mirowska, K. K., Mewada, A., Kahn, J., Afonso, L., Williams, K. A., & Flack, J. M. (2012) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2012.09.017 · Cited by 898 · see citing works
Common variants associated with plasma triglycerides and risk for coronary artery disease
Do, R., Willer, C. J., Schmidt, E. M., Sengupta, S., Gao, C., Peloso, G. M., Gustafsson, S., Kanoni, S., Ganna, A., Chen, J., et al. (2013) · Nature Genetics · doi:10.1038/ng.2795 · Cited by 862 · see citing works
Self-citationGenetic and Pharmacologic Inactivation of ANGPTL3 and Cardiovascular Disease
Dewey, F. E., Gusarova, V., Dunbar, R. L., O’Dushlaine, C., Schurmann, C., Gottesman, O., McCarthy, S., Van Hout, C. V., Bruse, S., Dansky, H. M., et al. (2017) · New England Journal of Medicine · doi:10.1056/nejmoa1612790 · Cited by 885 · see citing works
Self-citationDysfunctional HDL and atherosclerotic cardiovascular disease
Rosenson, R. S., Brewer, H. B., Ansell, B. J., Barter, P., Chapman, M. J., Heinecke, J. W., Kontush, A., Tall, A. R., & Webb, N. R. (2016) · Nature Reviews Cardiology · doi:10.1038/nrcardio.2015.124 · Cited by 822 · see citing works
Mendelian randomization of blood lipids for coronary heart disease
Holmes, M. V., Asselbergs, F. W., Palmer, T. M., Drenos, F., Lanktree, M. B., Nelson, C. P., Dale, C. E., Padmanabhan, S., Finan, C., Swerdlow, D. I., et al. (2015) · European Heart Journal · doi:10.1093/eurheartj/eht571 · Cited by 748 · see citing works
Self-citationA brief history of human disease genetics
Claussnitzer, M., Cho, J. H., Collins, R., Cox, N. J., Dermitzakis, E. T., Hurles, M. E., Kathiresan, S., Kenny, E. E., Lindgren, C. M., MacArthur, D. G., et al. (2020) · Nature · doi:10.1038/s41586-019-1879-7 · Cited by 697 · see citing works
Self-citationMendelian randomization in cardiometabolic disease: challenges in evaluating causality
Holmes, M. V., Ala-Korpela, M., & Smith, G. D. (2017) · Nature Reviews Cardiology · doi:10.1038/nrcardio.2017.78 · Cited by 679 · see citing works
Genetics of coronary artery disease: discovery, biology and clinical translation
Khera, A. V., & Kathiresan, S. (2017) · Nature Reviews Genetics · doi:10.1038/nrg.2016.160 · Cited by 659 · see citing works
Self-citationSandesara, P. B., Virani, S. S., Fazio, S., & Shapiro, M. D. (2019) · Endocrine Reviews · doi:10.1210/er.2018-00184 · Cited by 626 · see citing works
Morrison, J., Knoblauch, N., Marcus, J. H., Stephens, M., & He, X. (2020) · Nature Genetics · doi:10.1038/s41588-020-0631-4 · Cited by 578 · see citing works
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Hirano, T. (2018) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.rv17023 · Cited by 552 · see citing works
Zanoni, P., Khetarpal, S. A., Larach, D. B., Hancock-Cerutti, W. F., Millar, J. S., Cuchel, M., DerOhannessian, S., Kontush, A., Surendran, P., Saleheen, D., et al. (2016) · Science · doi:10.1126/science.aad3517 · Cited by 545 · see citing works
Self-citationSoy and Health Update: Evaluation of the Clinical and Epidemiologic Literature
Messina, M. (2016) · Nutrients · doi:10.3390/nu8120754 · Cited by 537 · see citing works
Lipids, lipoproteins, and metabolites and risk of myocardial infarction and stroke
Holmes, M. V., Millwood, I. Y., Kartsonaki, C., Hill, M. R., Bennett, D. A., Boxall, R., Guo, Y., Xu, X., Bian, Z., Hu, R., et al. (2018) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2017.12.006 · Cited by 508 · see citing works
Self-citationKeene, D., Price, C., Shun-Shin, M. J., & Francis, D. P. (2014) · BMJ · doi:10.1136/bmj.g4379 · Cited by 519 · see citing works
Hoogeveen, R. C., Gaubatz, J. W., Sun, W., Dodge, R. C., Crosby, J. R., Jiang, J., Couper, D., Virani, S. S., Kathiresan, S., Boerwinkle, E., et al. (2014) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.114.303284 · Cited by 507 · see citing works
Self-citationAnand, S. S., Hawkes, C., de Souza, R. J., Mente, A., Dehghan, M., Nugent, R., Zulyniak, M. A., Weis, T., Bernstein, A. M., Krauss, R. M., et al. (2015) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2015.07.050 · Cited by 507 · see citing works
“Dietary interventions that raise HDL-C may not necessarily translate into CVD risk reduction, as serum HDL-C has recently been called into question regarding its role in the causal pathway of CVD (110).”
BackgroundSelf-citationVitamin D and Risk of Multiple Sclerosis: A Mendelian Randomization Study
Mokry, L. E., Ross, S., Ahmad, O. S., Forgetta, V., Smith, G. D., Leong, A., Greenwood, C. M. T., Thanassoulis, G., & Richards, J. B. (2015) · PLOS Medicine · doi:10.1371/journal.pmed.1001866 · Cited by 445 · see citing works
Use of allele scores as instrumental variables for Mendelian randomization
Burgess, S., & Thompson, S. G. (2013) · International Journal of Epidemiology · doi:10.1093/ije/dyt093 · Cited by 452 · see citing works
Ference, B. A., Majeed, F., Penumetcha, R., Flack, J. M., & Brook, R. D. (2015) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2015.02.020 · Cited by 407 · see citing works
Lotta, L. A., Scott, R. A., Sharp, S. J., Burgess, S., Luan, J., Tillin, T., Schmidt, A. F., Imamura, F., Stewart, I. D., Perry, J. R. B., et al. (2016) · PLOS Medicine · doi:10.1371/journal.pmed.1002179 · Cited by 417 · see citing works
The TMAO-Generating Enzyme Flavin Monooxygenase 3 Is a Central Regulator of Cholesterol Balance
Warrier, M., Shih, D. M., Burrows, A. C., Ferguson, D., Gromovsky, A. D., Brown, A. L., Marshall, S., McDaniel, A., Schugar, R. C., Wang, Z., et al. (2015) · Cell Reports · doi:10.1016/j.celrep.2014.12.036 · Cited by 414 · see citing works
High-density lipoprotein revisited: biological functions and clinical relevance
von Eckardstein, A., Nordestgaard, B. G., Remaley, A. T., & Catapano, A. L. (2023) · European Heart Journal · doi:10.1093/eurheartj/ehac605 · Cited by 401 · see citing works
Distinguishing genetic correlation from causation across 52 diseases and complex traits
O’Connor, L. J., & Price, A. L. (2018) · Nature Genetics · doi:10.1038/s41588-018-0255-0 · Cited by 394 · see citing works
Selecting instruments for Mendelian randomization in the wake of genome-wide association studies.
Swerdlow, D. I., Kuchenbaecker, K. B., Shah, S., Sofat, R., Holmes, M. V., White, J., Mindell, J. S., Kivimaki, M., Brunner, E. J., Whittaker, J. C., et al. (2016) · International Journal of Epidemiology · doi:10.1093/ije/dyw088 · Cited by 387 · see citing works
Emdin, C. A., Khera, A. V., Natarajan, P., Klarin, D., Zekavat, S. M., Hsiao, A. J., & Kathiresan, S. (2017) · JAMA · doi:10.1001/jama.2016.21042 · Cited by 378 · see citing works
Deconstructing the sources of genotype-phenotype associations in humans
Young, A. I., Benonisdottir, S., Przeworski, M., & Kong, A. (2019) · Science · doi:10.1126/science.aax3710 · Cited by 288 · see citing works
Paradoxical association of enhanced cholesterol efflux with increased incident cardiovascular risks
Li, X.-M., Tang, W. H. W., Mosior, M. K., Huang, Y., Wu, Y., Matter, W., Gao, V., Schmitt, D., DiDonato, J. A., Fisher, E. A., et al. (2013) · Arteriosclerosis, Thrombosis, and Vascular Biology · doi:10.1161/atvbaha.113.301373 · Cited by 301 · see citing works
Association of Lipid Fractions With Risks for Coronary Artery Disease and Diabetes
White, J., Swerdlow, D. I., Preiss, D., Fairhurst-Hunter, Z., Keating, B. J., Asselbergs, F. W., Sattar, N., Humphries, S. E., Hingorani, A. D., & Holmes, M. V. (2016) · JAMA Cardiology · doi:10.1001/jamacardio.2016.1884 · Cited by 293 · see citing works
Davey Smith, G., Holmes, M. V., Davies, N. M., & Ebrahim, S. (2020) · European Journal of Epidemiology · doi:10.1007/s10654-020-00622-7 · Cited by 287 · see citing works
Gaudet, D., Karwatowska-Prokopczuk, E., Baum, S. J., Hurh, E., Kingsbury, J., Bartlett, V. J., Figueroa, A. L., Piscitelli, P., Singleton, W., Witztum, J. L., et al. (2020) · European Heart Journal · doi:10.1093/eurheartj/ehaa689 · Cited by 279 · see citing works
HDL cholesterol: reappraisal of its clinical relevance
März, W., Kleber, M. E., Scharnagl, H., Speer, T., Zewinger, S., Ritsch, A., Parhofer, K. G., von Eckardstein, A., Landmesser, U., & Laufs, U. (2017) · Clinical Research in Cardiology · doi:10.1007/s00392-017-1106-1 · Cited by 275 · see citing works
Afzal, S., Brøndum-Jacobsen, P., Bojesen, S. E., & Nordestgaard, B. G. (2014) · BMJ · doi:10.1136/bmj.g6330 · Cited by 269 · see citing works
High-density lipoproteins, reverse cholesterol transport and atherogenesis
Pownall, H. J., Rosales, C., Gillard, B. K., & Gotto, A. M. (2021) · Nature Reviews Cardiology · doi:10.1038/s41569-021-00538-z · Cited by 250 · see citing works
Ketogenic diets and chronic disease: weighing the benefits against the risks
Crosby, L., Davis, B., Joshi, S., Jardine, M., Paul, J., Neola, M., & Barnard, N. D. (2021) · Frontiers in Nutrition · doi:10.3389/fnut.2021.702802 · Cited by 229 · see citing works
Atherosclerotic cardiovascular disease prevention in rheumatoid arthritis
Semb, A. G., Ikdahl, E., Wibetoe, G., Crowson, C. S., & Rollefstad, S. (2020) · Nature Reviews Rheumatology · doi:10.1038/s41584-020-0428-y · Cited by 216 · see citing works
Cerebrospinal fluid APOE levels: an endophenotype for genetic studies for Alzheimer's disease
Cruchaga, C., Kauwe, J. S. K., Nowotny, P., Bales, K., Pickering, E. H., Mayo, K., Bertelsen, S., Hinrichs, A., Fagan, A. M., Holtzman, D. M., et al. (2012) · Human Molecular Genetics · doi:10.1093/hmg/dds296 · Cited by 207 · see citing works
Prins, B. P., Abbasi, A., Wong, A., Vaez, A., Nolte, I., Franceschini, N., Stuart, P. E., Guterriez Achury, J., Mistry, V., Bradfield, J. P., et al. (2016) · PLOS Medicine · doi:10.1371/journal.pmed.1001976 · Cited by 199 · see citing works
Self-citationHolmes, M. V., Richardson, T. G., Ference, B. A., Davies, N. M., & Davey Smith, G. (2021) · Nature Reviews Cardiology · doi:10.1038/s41569-020-00493-1 · Cited by 184 · see citing works
The Current State of Niacin in Cardiovascular Disease Prevention
Lavigne, P. M., & Karas, R. H. (2013) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2012.10.030 · Cited by 185 · see citing works
Annema, W., & von Eckardstein, A. (2013) · Circulation Journal · doi:10.1253/circj.cj-13-1025 · Cited by 182 · see citing works
Progress and promise in understanding the genetic basis of common diseases
Price, A. L., Spencer, C. C. A., & Donnelly, P. (2015) · Proceedings of the Royal Society B: Biological Sciences · doi:10.1098/rspb.2015.1684 · Cited by 147 · see citing works
Taylor, A. E., Davies, N. M., Ware, J. J., VanderWeele, T., Smith, G. D., & Munafò, M. R. (2014) · Economics & Human Biology · doi:10.1016/j.ehb.2013.12.002 · Cited by 166 · see citing works
Surprises from genetic analyses of lipid risk factors for atherosclerosis
Musunuru, K., & Kathiresan, S. (2016) · Circulation Research · doi:10.1161/circresaha.115.306398 · Cited by 159 · see citing works
Self-citationThe many weak instruments problem and Mendelian randomization
Davies, N. M., von Hinke Kessler Scholder, S., Farbmacher, H., Burgess, S., Windmeijer, F., & Smith, G. D. (2015) · Statistics in Medicine · doi:10.1002/sim.6358 · Cited by 140 · see citing works
Effects of hormonal contraception on systemic metabolism: cross-sectional and longitudinal evidence
Wang, Q., Würtz, P., Auro, K., Morin-Papunen, L., Kangas, A. J., Soininen, P., Tiainen, M., Tynkkynen, T., Joensuu, A., Havulinna, A. S., et al. (2016) · International Journal of Epidemiology · doi:10.1093/ije/dyw147 · Cited by 117 · see citing works
Self-citationNovel and future lipid-modulating therapies for the prevention of cardiovascular disease
Brandts, J., & Ray, K. K. (2023) · Nature Reviews Cardiology · doi:10.1038/s41569-023-00860-8 · Cited by 107 · see citing works
High resolution genetic mapping of putative causal interactions between regions of open chromatin
Kumasaka, N., Knights, A., & Gaffney, D. (2018) · Nature Genetics · doi:10.1038/s41588-018-0278-6 · Cited by 99 · see citing works
Genetics of coronary artery disease in the post‐GWAS era
Chen, Z., & Schunkert, H. (2021) · Journal of Internal Medicine · doi:10.1111/joim.13362 · Cited by 106 · see citing works
Self-citationDissecting polygenic signals from genome-wide association studies on human behaviour
Abdellaoui, A., & Verweij, K. J. H. (2021) · Nature Human Behaviour · doi:10.1038/s41562-021-01110-y · Cited by 95 · see citing works
Bartlett, J., Predazzi, I. M., Williams, S. M., Bush, W. S., Kim, Y., Havas, S., Toth, P. P., Fazio, S., & Miller, M. (2016) · Circulation: Cardiovascular Quality and Outcomes · doi:10.1161/circoutcomes.115.002436 · Cited by 96 · see citing works
KONES, R. J. (2013) · Vascular Health and Risk Management · doi:10.2147/vhrm.s37119 · Cited by 89 · see citing works
Rahmioglu, N., Macgregor, S., Drong, A. W., Hedman, A. K., Harris, H. R., Randall, J. C., Prokopenko, I., The International Endogene Consortium (IEC), T. G. C., Nyholt, D. R., Morris, A. P., et al. (2015) · Human Molecular Genetics · doi:10.1093/hmg/ddu516 · Cited by 85 · see citing works
Millwood, I. Y., Bennett, D., Holmes, M. V., Boxall, R., Guo, Y., Bian, Z., Yang, L., Sansome, S., Chen, Y., Du, H., et al. (2017) · JAMA Cardiology · doi:10.1001/jamacardio.2017.4177 · Cited by 83 · see citing works
Self-citationMethylation at CPT1A locus is associated with lipoprotein subfraction profiles
Wood, A. C., Aslibekyan, S. W., Absher, D., Hopkins, P. N., Sha, J., Tsai, M. Y., Tiwari, H. K., Waite, L. L., Zhi, D., & Arnett, D. K. (2014) · Journal of Lipid Research · doi:10.1194/jlr.m048504 · Cited by 79 · see citing works
Zhao, B., Cui, Y., Fan, X., Qi, P., Liu, C., Zhou, X., & Zhang, X. (2019) · PLOS ONE · doi:10.1371/journal.pone.0218543 · Cited by 69 · see citing works
Athinarayanan, S. J., Hallberg, S. J., McKenzie, A. L., Lechner, K., King, S. M., McCarter, J. P., Volek, J. S., Phinney, S. D., & Krauss, R. M. (2020) · Cardiovascular Diabetology · doi:10.1186/s12933-020-01178-2 · Cited by 69 · see citing works
Tang, Y., Wang, S., Yi, Q., Xia, Y., & Geng, B. (2021) · Lipids in Health and Disease · doi:10.1186/s12944-021-01497-7 · Cited by 69 · see citing works
Khoudary, S. R. E., Hutchins, P. M., Matthews, K. A., Brooks, M. M., Orchard, T. J., Ronsein, G. E., & Heinecke, J. W. (2016) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2016-2144 · Cited by 65 · see citing works
Lipid disorders in children living with overweight and obesity- large cohort study from Poland
Brzeziński, M., Metelska, P., Myśliwiec, M., & Szlagatys‐Sidorkiewicz, A. (2020) · Lipids in Health and Disease · doi:10.1186/s12944-020-01218-6 · Cited by 70 · see citing works
Riaz, H., Khan, S. U., Rahman, H., Shah, N. P., Kaluski, E., Lincoff, A. M., & Nissen, S. E. (2019) · European Journal of Preventive Cardiology · doi:10.1177/2047487318816495 · Cited by 61 · see citing works
Gender-specific associations between lipids and cognitive decline in the elderly
Ancelin, M., Ripoche, E., Dupuy, A., Samieri, C., Rouaud, O., Berr, C., Carrière, I., & Ritchie, K. A. (2014) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2014.02.003 · Cited by 61 · see citing works
van der Graaf, A., Claringbould, A., Rimbert, A., Heijmans, B. T., Hoen, P. A. C. ’., van Meurs, J. B. J., Jansen, R., Franke, L., Westra, H.-J., Li, Y., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18716-x · Cited by 57 · see citing works
Self-citationSystems genetics applications in metabolism research
Seldin, M. M., Yang, X., & Lusis, A. J. (2019) · Nature Metabolism · doi:10.1038/s42255-019-0132-x · Cited by 56 · see citing works
Duparc, T., Ruidavets, J., Genoux, A., Ingueneau, C., Najib, S., Ferrières, J., Perret, B., & Martinez, L. O. (2020) · Scientific Reports · doi:10.1038/s41598-020-65100-2 · Cited by 54 · see citing works
Lipoprotein signatures of cholesteryl ester transfer protein and HMG-CoA reductase inhibition
Kettunen, J., Holmes, M. V., Allara, E., Anufrieva, O., Ohukainen, P., Oliver-Williams, C., Wang, Q., Tillin, T., Hughes, A. D., Kähönen, M., et al. (2019) · PLOS Biology · doi:10.1371/journal.pbio.3000572 · Cited by 47 · see citing works
Self-citationPhenotypes and Genotypes of High Density Lipoprotein Cholesterol in Exceptional Longevity
Milman, S., Atzmon, G., Crandall, J. P., & Barzilai, N. (2013) · Current Vascular Pharmacology · doi:10.2174/1570161111666131219101551 · Cited by 44 · see citing works
Monitoring of lipids, enzymes, and creatine kinase in patients on lipid-lowering drug therapy
Wiklund, O., Pirazzi, C., & Romeo, S. (2013) · Current Cardiology Reports · doi:10.1007/s11886-013-0397-8 · Cited by 45 · see citing works
Dietary cholesterol increases paraoxonase 1 enzyme activity
Kim, D. S., Burt, A., Ranchalis, J., Richter, R. J., Marshall, J. K., Nakayama, K. S., Jarvik, E. R., Eintracht, J. F., Rosenthal, E. A., Furlong, C. E., et al. (2012) · Journal of Lipid Research · doi:10.1194/jlr.p030601 · Cited by 45 · see citing works
2016 ESC/EAS Guidelines for the Management of Dyslipidaemias
Catapano, A. L., Graham, I. M., Backer, G. D., Wiklund, O., Chapman, M. J., Drexel, H., Hoes, A. W., Jennings, C. S., Landmesser, U., Pedersen, T. R., et al. (2016) · Kardiologia Polska · doi:10.5603/kp.2016.0157 · Cited by 41 · see citing works
Self-citationTangier disease: update for 2020
Hooper, A. J., Hegele, R. A., & Burnett, J. R. (2020) · Current Opinion in Lipidology · doi:10.1097/mol.0000000000000669 · Cited by 42 · see citing works
Wu, Z., Lou, Y., Qiu, X., Liu, Y., Lu, L., Chen, Q., & Jin, W. (2014) · BMC Medical Genetics · doi:10.1186/s12881-014-0118-1 · Cited by 40 · see citing works
“[77] utilized the Asn396Ser polymorphism in the endothelial lipase gene (LIPG) and a genetic score containing 14 common single nucleotide polymorphisms (solely concerning HDL-C) as two instruments for Mendelian randomization.”
Diet-derived antioxidants and nonalcoholic fatty liver disease: a Mendelian randomization study
Chen, L., Fan, Z., Sun, X., Qiu, W., Mu, W., Chai, K., Cao, Y., Wang, G., & Lv, G. (2022) · Hepatology International · doi:10.1007/s12072-022-10443-3 · Cited by 36 · see citing works
Self-citationChuang, S., Liu, S.-C., Chien, M.-N., Lee, C., Lee, Y., & Chien, K. (2024) · American Journal of Preventive Cardiology · doi:10.1016/j.ajpc.2024.100869 · Cited by 35 · see citing works
P2Y13 Receptor Regulates HDL Metabolism and Atherosclerosis In Vivo
Goffinet, M., Tardy, C., Boubekeur, N., Cholez, G., Bluteau, A., Oniciu, D. C., Lalwani, N. D., Dasseux, J., Barbaras, R., & Baron, R. (2014) · PLoS ONE · doi:10.1371/journal.pone.0095807 · Cited by 32 · see citing works
Biradar, M. I., Chiang, K.-M., Yang, H., Huang, Y., & Pan, W. (2019) · International Journal of Obesity · doi:10.1038/s41366-019-0487-9 · Cited by 32 · see citing works
Brassard, D., Arsenault, B. J., Boyer, M., Bernic, D., Tessier‐Grenier, M., Talbot, D. C., Tremblay, A., Levy, E. H., Asztalos, B. F., Jones, P. J. H., et al. (2018) · Journal of Nutrition · doi:10.1093/jn/nxy014 · Cited by 31 · see citing works
Current guidelines for high-density lipoprotein cholesterol in therapy and future directions
Michos, E. D., Subedi, B. H., Joshi, P. H., Jones, S. R., Martin, S. S., & Blaha, M. J. (2014) · Vascular Health and Risk Management · doi:10.2147/vhrm.s45648 · Cited by 30 · see citing works
Castaing-Berthou, A., Malet, N., Radojkovic, C., Cabou, C., Gayral, S., Martinez, L. O., & Laffargue, M. (2017) · Cellular Physiology and Biochemistry · doi:10.1159/000477607 · Cited by 30 · see citing works
Examining the paradox of high high-density lipoprotein and elevated cardiovascular risk
Singh, K., & Rohatgi, A. K. (2018) · Journal of Thoracic Disease · doi:10.21037/jtd.2017.12.97 · Cited by 29 · see citing works
Mendelian randomisation, lipids, and cardiovascular disease
Harrison, S. C., Holmes, M. V., & Humphries, S. E. (2012) · The Lancet · doi:10.1016/s0140-6736(12)60481-4 · Cited by 30 · see citing works
- Authors
- Voight, B. F., Peloso, G. M., Orho-Melander, M., Frikke-Schmidt, R., Barbalic, M., Jensen, M. K., Hindy, G., Hólm, H., Ding, E. L., Johnson, T., Schunkert, H., Samani, N. J., Clarke, R., Hopewell, J. C., Thompson, J. F., Li, M., Thorleifsson, G., Newton-Cheh, C., Musunuru, K., Pirruccello, J. P., Saleheen, D., Chen, L., Stewart, A. F., Schillert, A., Thorsteinsdottir, U., Thorgeirsson, G., Anand, S., Engert, J. C., Morgan, T., Spertus, J., Stoll, M., Berger, K., Martinelli, N., Girelli, D., McKeown, P. P., Patterson, C. C., Epstein, S. E., Devaney, J., Burnett, M.-S., Mooser, V., Ripatti, S., Surakka, I., Nieminen, M. S., Sinisalo, J., Lokki, M.-L., Perola, M., Havulinna, A., de Faire, U., Gigante, B., Ingelsson, E., Zeller, T., Wild, P., de Bakker, P. I. W., Klungel, O. H., Maitland-van der Zee, A.-H., Peters, B. J. M., de Boer, A., Grobbee, D. E., Kamphuisen, P. W., Deneer, V. H. M., Elbers, C. C., Onland-Moret, N. C., Hofker, M. H., Wijmenga, C., Verschuren, W. M., Boer, J. M., van der Schouw, Y. T., Rasheed, A., Frossard, P., Demissie, S., Willer, C., Do, R., Ordovas, J. M., Abecasis, G. R., Boehnke, M., Mohlke, K. L., Daly, M. J., Guiducci, C., Burtt, N. P., Surti, A., Gonzalez, E., Purcell, S., Gabriel, S., Marrugat, J., Peden, J., Erdmann, J., Diemert, P., Willenborg, C., König, I. R., Fischer, M., Hengstenberg, C., Ziegler, A., Buysschaert, I., Lambrechts, D., Van de Werf, F., Fox, K. A., El Mokhtari, N. E., Rubin, D., Schrezenmeir, J., Schreiber, S., Schäfer, A., Danesh, J., Blankenberg, S., Roberts, R., McPherson, R., Watkins, H., Hall, A. S., Overvad, K., Rimm, E., Boerwinkle, E., Tybjaerg-Hansen, A., Cupples, L. A., Reilly, M. P., Melander, O., Mannucci, P. M., Ardissino, D., Siscovick, D., Elosua, R., Stefansson, K., O'Donnell, C. J., Salomaa, V., Rader, D. J., Peltonen, L., Schwartz, S. M., Altshuler, D., & Kathiresan, S.
- Affiliations
- University of Pennsylvania (US)
- Boston University (US)
- Harvard University (US)
- Lund University (SE)
- deCODE Genetics (Iceland) (IS)
- Brigham and Women's Hospital (US)
- Queen Mary University of London (GB)
- University of Lübeck (DE)
- University of Leicester (GB)
- University of Oxford (GB)
- Broad Institute (US)
- University of Cambridge (GB)
- Ottawa Heart Institute (CA)
- Population Health Research Institute (CA)
- McGill University (CA)
- Vanderbilt University (US)
- University of Missouri–Kansas City (US)
- University of Münster (DE)
- University of Verona (IT)
- Queen's University Belfast (GB)
- MedStar Washington Hospital Center (US)
- GlaxoSmithKline (United States) (US)
- University of Helsinki (FI)
- Helsinki University Hospital (FI)
- Finnish Institute for Health and Welfare (FI)
- Karolinska Institutet (SE)
- Johannes Gutenberg University Mainz (DE)
- Utrecht University (NL)
- University Medical Center Utrecht (NL)
- University Medical Center Groningen (NL)
- St. Antonius Ziekenhuis (NL)
- National Institute for Public Health and the Environment (NL)
- Center for Non-Communicable Diseases (PK)
- University of Michigan (US)
- Massachusetts General Hospital (US)
- University of North Carolina at Chapel Hill (US)
- Hospital del Mar Research Institute (ES)
- University Hospital Regensburg (DE)
- Universitair Ziekenhuis Leuven (BE)
- University of Edinburgh (GB)
- University Hospital Schleswig-Holstein (DE)
- Max Rubner Institut (DE)
- Christian-Albrechts-Universität zu Kiel (DE)
- University of Leeds (GB)
- Aarhus University (DK)
- The University of Texas Health Science Center at Houston (US)
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico (IT)
- Ospedale di Parma (IT)
- University of Washington (US)
- Corresponding author
- Kathiresan, Sekar
- ORCID
- Voight, Benjamin F
- Peloso, Gina M
- Jensen, Majken K
- Hindy, George
- Hólm, Hilma
- Ding, Eric L
- Johnson, Toby
- Schunkert, Heribert
- Samani, Nilesh J
- Clarke, Robert
- Hopewell, Jemma C
- Thompson, John F
- Li, Mingyao
- Musunuru, Kiran
- Pirruccello, James P
- Saleheen, Danish
- Chen, Li
- Stewart, Alexandre FR
- Schillert, Arne
- Anand, Sonia
- Engert, James C
- Morgan, Thomas
- Spertus, John
- Stoll, Monika
- Martinelli, Nicola
- Girelli, Domenico
- McKeown, Pascal P
- Patterson, Christopher C
- Mooser, Vincent
- Ripatti, Samuli
- Surakka, Ida
- Nieminen, Markku S
- Sinisalo, Juha
- Lokki, Marja-Liisa
- Perola, Markus
- Havulinna, Aki
- Gigante, Bruna
- Ingelsson, Erik
- Zeller, Tanja
- Wild, Philipp
- Klungel, Olaf H
- Peters, Bas J M
- Grobbee, Diederick E
- Kamphuisen, Pieter W
- Deneer, Vera H M
- Elbers, Clara C
- Wijmenga, Cisca
- Verschuren, WM Monique
- Boer, Jolanda MA
- Demissie, Serkalem
- Willer, Cristen
- Do, Ron
- Abecasis, Gonçalo R
- Boehnke, Michael
- Mohlke, Karen L
- Daly, Mark J
- Burtt, Noël P
- Purcell, Shaun
- Gabriel, Stacey
- Marrugat, Jaume
- Erdmann, Jeanette
- König, Inke R
- Fischer, Marcus
- Hengstenberg, Christian
- Ziegler, Andreas
- Buysschaert, Ian
- Lambrechts, Diether
- Fox, Keith A
- Schreiber, Stefan
- Danesh, John
- Blankenberg, Stefan
- McPherson, Ruth
- Watkins, Hugh
- Hall, Alistair S
- Overvad, Kim
- Rimm, Eric
- Boerwinkle, Eric
- Cupples, L Adrienne
- Reilly, Muredach P
- Melander, Olle
- Mannucci, Pier M
- Ardissino, Diego
- Siscovick, David
- Salomaa, Veikko
- Rader, Daniel J
- Peltonen, Leena
- Altshuler, David
- Kathiresan, Sekar
- Venue
- The Lancet
- Publisher
- Elsevier BV
- Published
- 2012-08
- Volume
- 380
- Issue
- 9841
- Pages
- 572-580
- ISSN
- 0099-5355 (ISSN-L)
- 0140-6736
- PMC
- PMC3419820
- OpenAlex
- W1240353884
- Cited by
- 148
- References
- 36
- Citations by year
- 2026: 11 · 2025: 4 · 2024: 5 · 2023: 8 · 2022: 9 · 2021: 19 · 2020: 16 · 2019: 9 · 2018: 10 · 2017: 8 · 2016: 12 · 2015: 8 · 2014: 9 · 2013: 6 · 2012: 13
- FWCI
- 1.41
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- The Lancet (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (publishedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
- University of Regensburg Publication Server (University of Regensburg) (submittedVersion)
- Figshare (submittedVersion, cc-by)
- Leicester Research Archive (University of Leicester) (submittedVersion, other-oa)
- Lund University Publications (Lund University) (submittedVersion)
- mediaTUM (Technical University of Munich) (submittedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
- Research Portal (Queen's University Belfast) (submittedVersion)
- Rivm Repository (Netherlands National Institute for Public Health and the Environment) (submittedVersion)
- Hirsla (Landspítali University Hospital) (submittedVersion)
- STM:n Hallinnonalan avoin julkaisuarkisto (Julkari) (submittedVersion)
- OpenAgrar (submittedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion)
- WOS
- Funders
- Wellcome Trust (090532)
- British Heart Foundation (RG/08/014/24067)
- National Institutes of Health (n01hc25195-41-0-1)
- National Heart, Lung, and Blood Institute (N01-HC-025195)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Surgery › Lipoproteins and Cardiovascular Health
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Clinical Biochemistry › Paraoxonase enzyme and polymorphisms
- Keywords
- HDL cholesterol, myocardial infarction, causal inference, endothelial lipase, genetic score, LDL cholesterol, cardiovascular risk, genetic instruments, single nucleotide polymorphisms, lipid biomarkers, confounding by indication, reverse causality
- MeSH terms
- Gene Frequency, Humans, Lipase, Cholesterol, HDL, Cholesterol, LDL, Myocardial Infarction, Prospective Studies, Risk Factors, Biomarkers, Case-Control Studies, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Mendelian Randomization Analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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