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Biological, clinical and population relevance of 95 loci for blood lipids
Open accessAbstract
Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.
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“thus implicating IDOL as a potential therapeutic target (35)(36)(37).”
From Distinct Functional Domains Contribute to Degradation of the Low Density Lipoprotein Receptor (LDLR) by the E3 Ubiquitin Ligase Inducible Degrader of the LDLR (IDOL) (2011) · cites this paper as [36]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Recent genome-wide association studies (GWASs) in cohorts of mixed European descent have identified noncoding SNPs in the region of the MYLIP gene that are associated with LDL-C levels (6)(7)(8), thus demonstrating for the first time genetic association between the MYLIP gene and lipid levels in humans.”
From The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans (2011) · cites this paper as [6]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“In recent GWASs and a GWAS meta-analysis of populations of mixed European descent (6-8), there were 3 independent (r 2 < 0.3) genome-wide significant signals in the MYLIP region, none of which resides within the MYLIP gene.”
From The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans (2011) · cites this paper as [6]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“We also examined the direct association evidence for rs9370867 in the large GWAS meta-analysis of cohorts of mixed European descent (6): rs9370867 was associated with LDL-C levels for the same A risk allele (MAF 50%) as in Mexicans (P = 5.8 × 10 -06 ; Figure 2A).”
From The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans (2011) · cites this paper as [6]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Another GWAS signal was detected by the SNPs rs2327951 (6) and rs2142672 (8) that mapped and tagged variants 48-49 kb downstream from MYLIP.”
From The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans (2011) · cites this paper as [6]
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“common genetic variants near SCARB1 have been found to be correlated with plasma HDL-C levels (57, 58)”
From The hepatic WASH complex is required for efficient plasma LDL and HDL cholesterol clearance (2019) · cites this paper as [57]
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“However, several genome wide studies have identified polymorphisms in the IDOL genomic region that are linked to total and LDL cholesterol levels140–142,”
From Pathways and Molecular Mechanisms Governing LDL Receptor Regulation (2025) · cites this paper as [141]
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“There are over 300 loci uncovered to be associated with plasma lipid levels in humans (Klarin et al., 2018; Liu et al., 2017; Teslovich et al., 2010; Willer et al., 2013).”
From GPR146 Deficiency Protects against Hypercholesterolemia and Atherosclerosis (2019) · cites this paper as Teslovich et al., 2010
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“SORT1 is a recently identified hepatic clearance receptor for LDL, which also regulates VLDL secretion and plasma triglycerides.16,20–22,38”
From (Pro)renin Receptor Inhibition Reprograms Hepatic Lipid Metabolism and Protects Mice From Diet-Induced Obesity and Hepatosteatosis (2018) · cites this paper as [38]
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“The association between triglycerides and cardiovascular (CV) risk is well established from epidemiological studies,1-5 genome-wide analyses,6-8 and Mendelian randomization studies.9,10”
The cited source says what the claim attributes to it.
In the citing paper
“Recent genome-wide association studies identify IDOL as a novel modulator of LDL in humans, thus implicating IDOL as a potential therapeutic target (35)(36)(37).”
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In the citing paper
“Hence, this calculation demonstrated that the sample size of rs9370867 may not have been sufficiently powered to meet the genome-wide significance level in the meta-analysis GWAS (6).”
From The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans (2011) · cites this paper as [6]
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“The HFE rs1800562 variant that we use as an instrument for systemic iron status has previously been associated with low-density lipoprotein cholesterol in GWAS meta-analysis [39].”
From Associations of genetically determined iron status across the phenome: A mendelian randomization study (2019) · cites this paper as [39]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Thus, our study demonstrated, for the first time to our knowledge, that the amino acid change rs9370867 is most likely the functional mechanism underlying these previous GWAS variants, rs2294261 and rs2480 (6,7).”
From The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans (2011) · cites this paper as [6]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Importantly, our LD analyses also demonstrated that the most strongly associated variant in Mexicans, rs9370867, was in strong LD with the GWAS associated variants rs2480 (7) and rs2294261 (6) in the CEU founders with European ancestry and, to a lesser extent, in the Mexican controls (r 2 = 0.73 and r 2 = 0.49, respectively; Figure 3).”
From The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans (2011) · cites this paper as [6]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Taken together, these trans-ethnic LD and association data suggest that the nonsynonymous SNP rs9370867 is more likely the true underlying functional variant accounting for the genome-wide significant signals rs2480 and rs2294261 observed in the previous GWASs (6,7).”
From The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans (2011) · cites this paper as [6]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“It is worth noting that the expression levels of MYLIP were not significantly different with respect to the rs3757354 genotypes in the fat biopsies of Mexican subjects or in fat or liver biopsies from subjects of mixed European descent (6).”
From The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans (2011) · cites this paper as [6]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“We observed that the nonsynonymous rs9370867 variant was in strong LD with 2 upstream genome-wide significant GWAS variants, rs2294261 (6) and rs2480 (7), in Europeans.”
From The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans (2011) · cites this paper as [6]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“The GWAS variants of the other 2 associated LD groups, rs3757354 (6) and the SNPs rs2327951 (6) and rs2142672 (8), which are in full LD (r 2 ≥ 0.97) in both Europeans and Mexicans, were nominally associated with high TC in the Mexican dyslipidemic study sample for the same risks allele as in Europeans (Figure 2B and Supplemental Table 4).”
From The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans (2011) · cites this paper as [6]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“GPR146, a susceptible gene associated with plasma total cholesterol (TC), LDL-C and high density lipoprotein cholesterol (HDL-C) levels”
From GPR146 Deficiency Protects against Hypercholesterolemia and Atherosclerosis (2019) · cites this paper as Teslovich et al., 2010
Experimental — accuracy not yet measuredIn the citing paper
“Profiling plasma lipids in large populations has uncovered sequence variations that substantially impact lipid phenotypes (Cohen et al., 2005; Teslovich et al., 2010).”
From Cellular Metabolism and Disease: What Do Metabolic Outliers Teach Us? (2012) · cites this paper as Teslovich et al., 2010
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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
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Saxena, R., Voight, B. F., Lyssenko, V., Burtt, N. P., de Bakker, P. I. W., Chen, H., Roix, J. J., Kathiresan, S., Hirschhorn, J. N., Daly, M. J., et al. (2007) · Science · doi:10.1126/science.1142358 · Cited by 2,843
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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
Self-citationKathiresan, S., Melander, O., Guiducci, C., Surti, A., Burtt, N. P., Rieder, M. J., Cooper, G. M., Roos, C., Voight, B. F., Havulinna, A. S., et al. (2008) · Nature Genetics · doi:10.1038/ng.75 · Cited by 1,386
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Goldstein, D. B. (2009) · New England Journal of Medicine · doi:10.1056/nejmp0806284 · Cited by 918
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Schadt, E. E., Molony, C. M., Chudin, E., Hao, K., Yang, X., Lum, P. Y., Kasarskis, A., Zhang, B., Wang, S. S.-M., Suver, C., et al. (2008) · PLoS Biology · doi:10.1371/journal.pbio.0060107 · Cited by 918
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Self-citationChen, P., Takeuchi, F., Lee, J., Li, H., Wu, J., Liang, J., Long, J., Tabara, Y., Goodarzi, M. O., Pereira, M. A., et al. (2014) · Diabetes · doi:10.2337/db13-1815 · Cited by 72
Self-citationCohort Profile: The Corogene study
Vaara, S. M., Nieminen, M. S., Lokki, M., Perola, M., Pussinen, P. J., Allonen, J., Parkkonen, O., & Sinisalo, J. P. (2011) · International Journal of Epidemiology · doi:10.1093/ije/dyr090 · Cited by 71
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Timpson, N. J., Walter, K., Min, J. L., Tachmazidou, I., Malerba, G., Shin, S., Chen, L., Futema, M., Southam, L., Iotchkova, V., et al. (2014) · Nature Communications · doi:10.1038/ncomms5871 · Cited by 70
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Eslam, M., & George, J. (2019) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2019.05.002 · Cited by 68
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Chen, J., Su, Y., Pi, S., Hu, B., & Mao, L. (2021) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2021.682389 · Cited by 70
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Tseng, Y., Yeh, Y., Chen, W.-J., & Lin, K. (2014) · International Journal of Molecular Sciences · doi:10.3390/ijms151223640 · Cited by 68
Yao, C., Chen, B. H., Joehanes, R., Otlu, B., Zhang, X., Liu, C., Huan, T., Taştan, Ö., Cupples, L. A., Meigs, J. B., et al. (2014) · Circulation · doi:10.1161/circulationaha.114.010696 · Cited by 68
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Salari, K., Watkins, H. C., & Ashley, E. A. (2012) · European Heart Journal · doi:10.1093/eurheartj/ehs112 · Cited by 76
Bochem, A. E., van Wijk, D. F., Holleboom, A. G., Duivenvoorden, R., Motazacker, M. M., Dallinga‐Thie, G. M., de Groot, E., Kastelein, J. J. P., Nederveen, A. J., Hovingh, G. K., et al. (2012) · European Heart Journal · doi:10.1093/eurheartj/ehs376 · Cited by 70
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Wells, J. C. K. (2012) · International Journal of Epidemiology · doi:10.1093/ije/dyr239 · Cited by 69
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Musunuru, K., Domian, I. J., & Chien, K. R. (2010) · Annual Review of Cell and Developmental Biology · doi:10.1146/annurev-cellbio-100109-103948 · Cited by 71
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Self-citationBlanco‐Gómez, A., Castillo‐Lluva, S., Sáez‐Freire, M. D. M., Hontecillas‐Prieto, L., Mao, J., Castellanos‐Martín, A., & Pérez‐Losada, J. (2016) · BioEssays · doi:10.1002/bies.201600084 · Cited by 72
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Ray, D., & Boehnke, M. (2017) · Genetic Epidemiology · doi:10.1002/gepi.22105 · Cited by 72
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Self-citationBarylski, M., Toth, P. P., Nikolic, D., Banach, M., Rizzo, M., & Montalto, G. (2014) · Best Practice & Research Clinical Endocrinology & Metabolism · doi:10.1016/j.beem.2013.11.001 · Cited by 67
Elements of ‘missing heritability’
Marian, A. J. (2012) · Current Opinion in Cardiology · doi:10.1097/hco.0b013e328352707d · Cited by 73
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Roth, S. M., Rankinen, T., Hagberg, J. M., Loos, R. J. F., Përusse, L., Sarzynski, M. A., Wolfarth, B., & Bouchard, C. (2012) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e31824f28b6 · Cited by 67
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Havemeyer, A., Lang, J., & Clement, B. (2011) · Drug Metabolism Reviews · doi:10.3109/03602532.2011.608682 · Cited by 67
Pathophysiology of hypertriglyceridemia
Hassing, H. C., Surendran, R. P., Mooij, H. L., Stroes, E. S. G., Nieuwdorp, M., & Dallinga‐Thie, G. M. (2011) · Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids · doi:10.1016/j.bbalip.2011.11.010 · Cited by 71
Robciuc, M. R., Naukkarinen, J., Ortega‐Alonso, A., Tyynismaa, H., Raivio, T., Rissanen, A., Kaprio, J. A., Ehnholm, C., Jauhiainen, M., & Pietiläinen, K. H. (2011) · Journal of Lipid Research · doi:10.1194/jlr.p015867 · Cited by 67
Self-citationHwang, L., Lawlor, D. A., Freathy, R. M., Evans, D. M., & Warrington, N. M. (2019) · International Journal of Epidemiology · doi:10.1093/ije/dyz160 · Cited by 70
The schizophrenia risk locus in SLC39A8 alters brain metal transport and plasma glycosylation
Mealer, R. G., Jenkins, B. G., Chen, C., Daly, M. J., Ge, T., Lehoux, S. D., Marquardt, T., Palmer, C. D., Park, J. H., Parsons, P. J., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-70108-9 · Cited by 69
Vandiedonck, C., Taylor, M. S., Lockstone, H. E., Plant, K., Taylor, J. M., Durrant, C., Broxholme, J., Fairfax, B. P., & Knight, J. C. (2011) · Genome Research · doi:10.1101/gr.116681.110 · Cited by 70
Weissglas-Volkov, D., Calkin, A. C., Tusie-Luna, T., Sinsheimer, J. S., Zelcer, N., Riba, L., Tino, A. M. V., Ordoñez-Sánchez, M. L., Cruz-Bautista, I., Aguilar-Salinas, C. A., et al. (2011) · Journal of Clinical Investigation · doi:10.1172/jci45504 · Cited by 66
Future of Cholesteryl Ester Transfer Protein Inhibitors
Rader, D. J., & deGoma, E. M. (2014) · Annual Review of Medicine · doi:10.1146/annurev-med-050311-163305 · Cited by 66
Self-citationWright, M. B., Santos, J. V., Kemmer, C., Maugeais, C., Carralot, J., Roever, S., Molina, J., Ducasa, G. M., Mitrofanova, A. V., Sloan, A. J., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-24890-3 · Cited by 66
Hu, X., Cai, M., Xiao, J., Wan, X., Wang, Z., Zhao, H., & Yang, C. (2024) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2024.06.016 · Cited by 66
Tian, E., Hoffman, M. P., & Hagen, K. G. T. (2012) · Nature Communications · doi:10.1038/ncomms1874 · Cited by 66
Hall, M. A., Verma, A., Brown-Gentry, K. D., Goodloe, R., Boston, J., Wilson, S., McClellan, B., Sutcliffe, C. B., Dilks, H. H., Gillani, N. B., et al. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004678 · Cited by 66
Wei, Q., Yu, D., Liu, M., Wang, M., Zhao, M., Liu, M., Jia, W., Ma, H., Fang, J., Xu, W., et al. (2014) · Nature Genetics · doi:10.1038/ng.3090 · Cited by 66
Below, J. E., Parra, E. J., Gamazon, E. R., Torres, J., Krithika, S., Candille, S. I., Lu, Y., Manichakul, A., Peralta‐Romero, J., Duan, Q., et al. (2016) · Scientific Reports · doi:10.1038/srep19429 · Cited by 68
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Guardiola, M., & Ribalta, J. (2017) · Current Atherosclerosis Reports · doi:10.1007/s11883-017-0665-y · Cited by 69
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Andersen, S. L., Briggs, F. B. S., Winnike, J., Natanzon, Y., Maichle, S., Knagge, K. J., Newby, L. K., & Gregory, S. G. (2019) · Multiple Sclerosis and Related Disorders · doi:10.1016/j.msard.2019.03.006 · Cited by 66
New lipid-lowering drugs: an update
Wierzbicki, A. S., Hardman, T. C., & Viljoen, A. (2012) · International Journal of Clinical Practice · doi:10.1111/j.1742-1241.2011.02867.x · Cited by 65
Genetics of coronary artery disease: Genome-wide association studies and beyond
Prins, B. P., Lagou, V., Asselbergs, F. W., Snieder, H., & Fu, J. (2012) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2012.05.015 · Cited by 69
Luo, J. M., le Cessie, S., Blauw, G. J., Franceschi, C., Noordam, R., & van Heemst, D. (2022) · GeroScience · doi:10.1007/s11357-022-00602-7 · Cited by 65
Lipidome‐ and Genome‐Wide Study to Understand Sex Differences in Circulatory Lipids
Tabassum, R., Ruotsalainen, S., Ottensmann, L., Gerl, M. J., Klose, C. D., Tukiainen, T., Pirinen, M., Simons, K., Widén, E., & Ripatti, S. (2022) · Journal of the American Heart Association · doi:10.1161/jaha.122.027103 · Cited by 69
Self-citationEmerging roles of flavin monooxygenase 3 in cholesterol metabolism and atherosclerosis
Schugar, R. C., & Brown, J. M. (2015) · Current Opinion in Lipidology · doi:10.1097/mol.0000000000000215 · Cited by 67
Implications of discoveries from genome-wide association studies in current cardiovascular practice
Jeemon, P. (2011) · World Journal of Cardiology · doi:10.4330/wjc.v3.i7.230 · Cited by 65
Pierce, B. L., & VanderWeele, T. J. (2012) · International Journal of Epidemiology · doi:10.1093/ije/dys141 · Cited by 65
Alkan, C., Kavak, P., Somel, M., Gökçümen, Ö., Ugurlu, S., Saygı, C., Dal, E., Buğra, K., Güngör, T., Şahinalp, S. C., et al. (2014) · BMC Genomics · doi:10.1186/1471-2164-15-963 · Cited by 70
Fenwick, P. H., Jeejeebhoy, K. N., Dhaliwal, R., Royall, D., Brauer, P. M., Tremblay, A., Klein, D., & Mutch, D. M. (2018) · Critical Reviews in Food Science and Nutrition · doi:10.1080/10408398.2018.1437022 · Cited by 66
Morelli, M. B., Chavez, C., & Santulli, G. (2019) · Expert Opinion on Therapeutic Targets · doi:10.1080/14728222.2020.1707806 · Cited by 64
Mathieson, I., Day, F. R., Barban, N., Tropf, F. C., Brazel, D. M., van Heemst, D., Vaez, A., van Zuydam, N. R., Bitarello, B. D., Gardner, E. J., et al. (2023) · Nature Human Behaviour · doi:10.1038/s41562-023-01528-6 · Cited by 66
Self-citationThe phospholipase A2 superfamily as a central hub of bioactive lipids and beyond
Murakami, M. (2023) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2023.108382 · Cited by 66
Metadata
- Authors
- 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., Johansen, C. T., Fouchier, S. W., Isaacs, A., Peloso, G. M., Barbalic, M., Ricketts, S. L., Bis, J. C., Aulchenko, Y. S., Thorleifsson, G., Feitosa, M. F., Chambers, J., Orho-Melander, M., Melander, O., Johnson, T., Li, X., Guo, X., Li, M., Shin Cho, Y., Jin Go, M., Jin Kim, Y., Lee, J.-Y., Park, T., Kim, K., Sim, X., Twee-Hee Ong, R., Croteau-Chonka, D. C., Lange, L. A., Smith, J. D., Song, K., Hua Zhao, J., Yuan, X., Luan, J., Lamina, C., Ziegler, A., Zhang, W., Zee, R. Y. L., Wright, A. F., Witteman, J. C. M., Wilson, J. F., Willemsen, G., Wichmann, H.-E., Whitfield, J. B., Waterworth, D. M., Wareham, N. J., Waeber, G., Vollenweider, P., Voight, B. F., Vitart, V., Uitterlinden, A. G., Uda, M., Tuomilehto, J., Thompson, J. R., Tanaka, T., Surakka, I., Stringham, H. M., Spector, T. D., Soranzo, N., Smit, J. H., Sinisalo, J., Silander, K., Sijbrands, E. J. G., Scuteri, A., Scott, J., Schlessinger, D., Sanna, S., Salomaa, V., Saharinen, J., Sabatti, C., Ruokonen, A., Rudan, I., Rose, L. M., Roberts, R., Rieder, M., Psaty, B. M., Pramstaller, P. P., Pichler, I., Perola, M., Penninx, B. W. J. H., Pedersen, N. L., Pattaro, C., Parker, A. N., Pare, G., Oostra, B. A., O’Donnell, C. J., Nieminen, M. S., Nickerson, D. A., Montgomery, G. W., Meitinger, T., McPherson, R., McCarthy, M. I., McArdle, W., Masson, D., Martin, N. G., Marroni, F., Mangino, M., Magnusson, P. K. E., Lucas, G., Luben, R., Loos, R. J. F., Lokki, M.-L., Lettre, G., Langenberg, C., Launer, L. J., Lakatta, E. G., Laaksonen, R., Kyvik, K. O., Kronenberg, F., König, I. R., Khaw, K.-T., Kaprio, J., Kaplan, L. M., Johansson, Å., Jarvelin, M.-R., Cecile J. W. Janssens, A., Ingelsson, E., Igl, W., Kees Hovingh, G., Hottenga, J.-J., Hofman, A., Hicks, A. A., Hengstenberg, C., Heid, I. M., Hayward, C., Havulinna, A. S., Hastie, N. D., Harris, T. B., Haritunians, T., Hall, A. S., Gyllensten, U., Guiducci, C., Groop, L. C., Gonzalez, E., Gieger, C., Freimer, N. B., Ferrucci, L., Erdmann, J., Elliott, P., Ejebe, K. G., Döring, A., Dominiczak, A. F., Demissie, S., Deloukas, P., de Geus, E. J. C., de Faire, U., Crawford, G., Collins, F. S., Chen, Y.-D. I., Caulfield, M. J., Campbell, H., Burtt, N. P., Bonnycastle, L. L., Boomsma, D. I., Boekholdt, S. M., Bergman, R. N., Barroso, I., Bandinelli, S., Ballantyne, C. M., Assimes, T. L., Quertermous, T., Altshuler, D., Seielstad, M., Wong, T. Y., Tai, E.-S., Feranil, A. B., Kuzawa, C. W., Adair, L. S., Taylor Jr, H. A., Borecki, I. B., Gabriel, S. B., Wilson, J. G., Holm, H., Thorsteinsdottir, U., Gudnason, V., Krauss, R. M., Mohlke, K. L., Ordovas, J. M., Munroe, P. B., Kooner, J. S., Tall, A. R., Hegele, R. A., Kastelein, J. J. P., Schadt, E. E., Rotter, J. I., Boerwinkle, E., Strachan, D. P., Mooser, V., Stefansson, K., Reilly, M. P., Samani, N. J., Schunkert, H., Cupples, L. A., Sandhu, M. S., Ridker, P. M., Rader, D. J., van Duijn, C. M., Peltonen, L., Abecasis, G. R., Boehnke, M., & Kathiresan, S.
- Affiliations
- University of Michigan (US)
- Broad Institute (US)
- University of Iceland (IS)
- University of Pennsylvania (US)
- Columbia University (US)
- University of Helsinki (FI)
- Brigham and Women's Hospital (US)
- Western University (CA)
- Amsterdam UMC Location University of Amsterdam (NL)
- Erasmus MC (NL)
- Boston University (US)
- University of Cambridge (GB)
- University of Washington (US)
- Washington University in St. Louis (US)
- Imperial College London (GB)
- Lund University (SE)
- Queen Mary University of London (GB)
- Cedars-Sinai Medical Center (US)
- Korea National Institute of Health (KR)
- Seoul National University (KR)
- Sookmyung Women's University (KR)
- National University of Singapore (SG)
- University of North Carolina at Chapel Hill (US)
- GlaxoSmithKline (United States) (US)
- Addenbrooke's Hospital (GB)
- Innsbruck Medical University (AT)
- University of Lübeck (DE)
- Institute of Genetics and Cancer (GB)
- University of Edinburgh (GB)
- Vrije Universiteit Amsterdam (NL)
- Helmholtz Munich (DE)
- QIMR Berghofer Medical Research Institute (AU)
- Centre Hospitalier Universitaire Vaudois (CH)
- Institute of Genetic and Biomedical Research (IT)
- Finnish Institute for Health and Welfare (FI)
- University of Leicester (GB)
- National Institutes of Health (US)
- King's College London (GB)
- Amsterdam Neuroscience (NL)
- Helsinki University Hospital (FI)
- Istituti di Ricovero e Cura a Carattere Scientifico (IT)
- Hammersmith Hospital (GB)
- National Institute on Aging (US)
- Stanford University (US)
- University of Oulu (FI)
- University of Ottawa (CA)
- Group Health Cooperative (US)
- Eurac Research (IT)
- Karolinska Institutet (SE)
- Amgen (United States) (US)
- Harvard University (US)
- TUM Klinikum (DE)
- Centre for Human Genetics (GB)
- University of Bristol (GB)
- Istituto di Genomica Applicata (IT)
- Municipal Institute for Medical Research (ES)
- Montreal Heart Institute (CA)
- Tampere University Hospital (FI)
- University of Southern Denmark (DK)
- Massachusetts General Hospital (US)
- Uppsala University (SE)
- University of Regensburg (DE)
- University of Leeds (GB)
- University of California, Los Angeles (US)
- University of Glasgow (GB)
- University of Southern California (US)
- Wellcome Sanger Institute (GB)
- Azienda Sanitaria di Firenze (IT)
- Baylor College of Medicine (US)
- Stanford Medicine (US)
- Genome Institute of Singapore (SG)
- University of San Carlos (PH)
- Northwestern University (US)
- University of Mississippi Medical Center (US)
- Sage Bionetworks (US)
- The University of Texas Health Science Center at Houston (US)
- St George's, University of London (GB)
- Corresponding author
- Kathiresan, Sekar
- ORCID
- Smith, Albert V.
- Edmondson, Andrew C.
- Stylianou, Ioannis M.
- Koseki, Masahiro
- Pirruccello, James P.
- Ripatti, Samuli
- Chasman, Daniel I.
- Willer, Cristen J.
- Fouchier, Sigrid W.
- Isaacs, Aaron
- Peloso, Gina M.
- Ricketts, Sally L.
- Bis, Joshua C.
- Aulchenko, Yurii S.
- Feitosa, Mary F.
- Chambers, John
- Melander, Olle
- Johnson, Toby
- Li, Xiaohui
- Guo, Xiuqing
- Li, Mingyao
- Lee, Jong-Young
- Park, Taesung
- Kim, Kyunga
- Sim, Xueling
- Lange, Leslie A.
- Smith, Joshua D.
- Yuan, Xin
- Luan, Jian’an
- Lamina, Claudia
- Ziegler, Andreas
- Zhang, Weihua
- Zee, Robert Y. L.
- Wilson, James F.
- Willemsen, Gonneke
- Wichmann, H.-Erich
- Whitfield, John B.
- Waterworth, Dawn M.
- Wareham, Nicholas J.
- Waeber, Gérard
- Voight, Benjamin F.
- Uda, Manuela
- Tuomilehto, Jaakko
- Tanaka, Toshiko
- Surakka, Ida
- Stringham, Heather M.
- Spector, Tim D.
- Soranzo, Nicole
- Smit, Johannes H.
- Sinisalo, Juha
- Sijbrands, Eric J. G.
- Scuteri, Angelo
- Scott, James
- Schlessinger, David
- Sanna, Serena
- Salomaa, Veikko
- Sabatti, Chiara
- Rudan, Igor
- Rose, Lynda M.
- Roberts, Robert
- Rieder, Mark
- Psaty, Bruce M.
- Pramstaller, Peter P.
- Pichler, Irene
- Perola, Markus
- Penninx, Brenda W. J. H.
- Pedersen, Nancy L.
- Pattaro, Cristian
- Parker, Alex N.
- O’Donnell, Christopher J.
- Nieminen, Markku S.
- Nickerson, Deborah A.
- Montgomery, Grant W.
- Meitinger, Thomas
- McPherson, Ruth
- McCarthy, Mark I.
- Masson, David
- Martin, Nicholas G.
- Marroni, Fabio
- Mangino, Massimo
- Magnusson, Patrik K. E.
- Lucas, Gavin
- Luben, Robert
- Loos, Ruth J. F.
- Lokki, Marja-Liisa
- Lettre, Guillaume
- Langenberg, Claudia
- Launer, Lenore J.
- Lakatta, Edward G.
- Laaksonen, Reijo
- Kyvik, Kirsten O.
- Kronenberg, Florian
- König, Inke R.
- Khaw, Kay-Tee
- Kaprio, Jaakko
- Kaplan, Lee M.
- Johansson, Åsa
- Ingelsson, Erik
- Igl, Wilmar
- Hottenga, Jouke-Jan
- Hicks, Andrew A.
- Hengstenberg, Christian
- Heid, Iris M.
- Hayward, Caroline
- Havulinna, Aki S.
- Hastie, Nicholas D.
- Harris, Tamara B.
- Haritunians, Talin
- Hall, Alistair S.
- Gyllensten, Ulf
- Groop, Leif C.
- Gieger, Christian
- Freimer, Nelson B.
- Ferrucci, Luigi
- Erdmann, Jeanette
- Elliott, Paul
- Ejebe, Kenechi G.
- Dominiczak, Anna F.
- Demissie, Serkalem
- Collins, Francis S.
- Chen, Yii-der I.
- Caulfield, Mark J.
- Bonnycastle, Lori L.
- Boomsma, Dorret I.
- Boekholdt, S. Matthijs
- Bergman, Richard N.
- Barroso, Inês
- Bandinelli, Stefania
- Ballantyne, Christie M.
- Assimes, Themistocles L.
- Quertermous, Thomas
- Altshuler, David
- Seielstad, Mark
- Wong, Tien Y.
- Tai, E-Shyong
- Kuzawa, Christopher W.
- Adair, Linda S.
- Borecki, Ingrid B.
- Gabriel, Stacey B.
- Wilson, James G.
- Gudnason, Vilmundur
- Krauss, Ronald M.
- Mohlke, Karen L.
- Munroe, Patricia B.
- Kooner, Jaspal S.
- Tall, Alan R.
- Hegele, Robert A.
- Kastelein, John J.P.
- Rotter, Jerome I.
- Boerwinkle, Eric
- Strachan, David P.
- Mooser, Vincent
- Reilly, Muredach P.
- Samani, Nilesh J
- Schunkert, Heribert
- Cupples, L. Adrienne
- Sandhu, Manjinder S.
- Ridker, Paul M
- Rader, Daniel J.
- Peltonen, Leena
- Abecasis, Gonçalo R.
- Boehnke, Michael
- Kathiresan, Sekar
- Venue
- Nature
- Published
- 2010-08
- Volume
- 466
- Issue
- 7307
- Pages
- 707-713
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3039276
- OpenAlex
- W2115801316
- Cited by
- 3,487
- References
- 20
- Citations by year
- 2026: 69 · 2025: 82 · 2024: 111 · 2023: 151 · 2022: 180 · 2021: 178 · 2020: 170 · 2019: 214 · 2018: 257 · 2017: 249 · 2016: 272 · 2015: 322 · 2014: 325 · 2013: 297 · 2012: 308
- FWCI
- 126.99
- Type
- journal article
- Language
- en
- Open access
- green
- research.vu.nl
- Licence
- other-oa
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (publishedVersion)
- Bristol Research (University of Bristol) (publishedVersion)
- VU Research Portal (publishedVersion, other-oa)
- St George's Online Research Archive (St George's University of London) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- National University of Singapore (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
- RePub (Erasmus University Rotterdam) (submittedVersion, other-oa)
- RePEc: Research Papers in Economics (submittedVersion)
- Institutional Research Information System (University of Udine) (submittedVersion)
- Digital Academic REpository of VU University Amsterdam (Vrije Universiteit Amsterdam) (submittedVersion)
- ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- UNICA IRIS Institutional Research Information System (University of Cagliari) (submittedVersion)
- IRIS (submittedVersion)
- UnissResearch (Università degli Studi di Sassari) (submittedVersion)
- Minerva Access (University of Melbourne) (submittedVersion)
- Research Portal (King's College London) (submittedVersion)
- Leicester Research Archive (University of Leicester) (submittedVersion)
- Lund University Publications (Lund University) (submittedVersion)
- mediaTUM (Technical University of Munich) (submittedVersion)
- Pure Amsterdam UMC (submittedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
- RePub (Erasmus University Rotterdam) (submittedVersion)
- University of Southern Denmark Research Portal (University of Southern Denmark) (submittedVersion)
- SERVAL (Université de Lausanne) (submittedVersion)
- Spiral (Imperial College London) (submittedVersion)
- Open Research (University of Surrey) (submittedVersion)
- STM:n Hallinnonalan avoin julkaisuarkisto (Julkari) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- UNC Libraries
- Funders
- GlaxoSmithKline
- Wellcome Trust (068545/Z/02), 077016/Z/05/Z, 079895, 076113/B/04/Z)
- British Heart Foundation (PG/08/094/26019, SP/08/005/25115, PG/02/128, RG/07/005/23633, PG/08/094)
- National Institutes of Health (2r24hd050924-06, n01hc085082-026, n01hc085081-021, 5r01dk068336-03, n01hc045133-001, n01ag12100-57-0-2, n01hc085079-024, n01hc015103-009, n01hc085084-005, n01hc55021-47-0-1, n01hc085085-011, n01hc085083-027, n01hc55020-39-0-0, n01hc085080-026, n01hc55016-37-0-0, n01hc055022-024, n01hg065403-000, n01hc085086-022, 5r01hl087700-03, n01hc55019-35-0-1, 6r01hl087679-03, 5k99hl094535-02, n01hc55018-38-0-1, n01hc25195-41-0-1, 5r01hl088215-04, 5p20rr020649-03, 6u54rr020278-06, n01hc55222-0-0-0, n01hc075150-004, n01hc035129-010, n01hc55015-48-0-1)
- U.S. Public Health Service (HHSN 268200625226C)
- Medical Research Council (MC_qA137934)
- National Institute on Aging (N01-AG12100)
- National Heart, Lung, and Blood Institute (N01-HC-85081, N01HC85085, R01HL080467, N01-HC55022, N01HC-85083, N01-HC-55018, 5R01 HL087679-02, N01HC15103, 5R01 HL08770003, N01 HC 55020, N01‐HC25195, N01 HC 55019, RC2HL101864, N01HC85082, N01HC‐75150, N01 HC85086, R01HL087676, R01HL087652, R01HL089309, N01HC85080, N02- HL-64278, N01 HC55222, U01HL069757, N01‐HC‐45133, N01-HC55016, R01HL087641, R01HL059367, R01HL054776, U01HL080295, 5-R01-HL-08821502, K99HL098364, R01HL085144, K23HL004381, K99-HL094535, N01‐HC‐55015, RC1HL099634, N01-HC55021, RC1HL099793, R01HL089650, RC2HL102419, T32HL007208, R01HL086694, N01-HC85079, N01-HC85084, N01HC35129)
- National Human Genome Research Institute (Z01HG000024, U01HG004402, N01 HG-65403, T32HG000040)
- National Cancer Institute (R01CA047988)
- National Institute of General Medical Sciences (T32GM007092)
- Fogarty International Center (R01TW005596)
- National Institute of Diabetes and Digestive and Kidney Diseases (5R01 DK06833603, R01DK078150, R01DK072193, U01DK062370, R01DK075681, U01DK062418, DK-062370, P30DK063491, P30DK056350)
- National Institute of Environmental Health Sciences (P30ES010126)
- National Center for Research Resources (U54-RR020278, UL1RR025005, RR20649, M01RR000425)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R24 HD-050924)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipoproteins and Cardiovascular Health
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipid metabolism and disorders
- Keywords
- plasma lipids, genetic association, cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, coronary artery disease, lipoprotein metabolism, single nucleotide polymorphisms, CYP7A1, NPC1L1, scavenger receptor class B type I, GALNT2, PPP1R3B, cross-population validation, East Asians, South Asians, African Americans, mouse model
- MeSH terms
- Polypeptide N-acetylgalactosaminyltransferase, Animals, Black or African American, Coronary Artery Disease, Europe, Female, Genotype, Humans, Lipids, Cholesterol, HDL, Cholesterol, LDL, Liver, Male, Phenotype, Triglycerides, Reproducibility of Results, N-Acetylgalactosaminyltransferases, Polymorphism, Single Nucleotide, White People, Asian People, Lipid Metabolism, Mice, Protein Phosphatase 1, Genome-Wide Association Study, Genetic Loci
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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