The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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]
Experimental — accuracy not yet measured
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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]
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
“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]
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
“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
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
“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]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“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).”
The cited source says what the claim attributes to it.
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
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Effects 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
Self-citationGenome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels
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
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
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
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
Self-citationFrom noncoding variant to phenotype via SORT1 at the 1p13 cholesterol locus
Musunuru, K., Strong, A., Frank-Kamenetsky, M., Lee, N. E., Ahfeldt, T., Sachs, K. V., Li, X., Li, H., Kuperwasser, N., Ruda, V. M., et al. (2010) · Nature · doi:10.1038/nature09266 · Cited by 1,140
Self-citationCommon Genetic Variation and Human Traits
Goldstein, D. B. (2009) · New England Journal of Medicine · doi:10.1056/nejmp0806284 · Cited by 918
Mapping the Genetic Architecture of Gene Expression in Human Liver
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
Self-citationLoci influencing lipid levels and coronary heart disease risk in 16 European population cohorts
Aulchenko, Y. S., Janssens, A. C. J. W., Albert Hofman, D., Isaacs, A. J., Sijbrands, E. J. G., Witteman, J. C. M., van Duijn, C. M., Ripatti, S., Lindqvist, I., Perola, M., et al. (2008) · Nature Genetics · doi:10.1038/ng.269 · Cited by 860
Self-citationLXR Regulates Cholesterol Uptake Through Idol-Dependent Ubiquitination of the LDL Receptor
Zelcer, N., Hong, C., Boyadjian, R., & Tontonoz, P. (2009) · Science · doi:10.1126/science.1168974 · Cited by 848
Cited by
Sorted by citations
Items 501–600 of 1,028
Human genetics and genomics a decade after the release of the draft sequence of the human genome
Naidoo, N., Yudi Pawitan, Y., Soong, R., Cooper, D. N., & Ku, C. (2011) · Human Genomics · doi:10.1186/1479-7364-5-6-577 · Cited by 117
GPR146 Deficiency Protects against Hypercholesterolemia and Atherosclerosis
Yu, H., Rimbert, A., Palmer, A. E., Toyohara, T., Xia, Y., Xia, F., Ferreira, L. M. R., Chen, Z., Chen, T., Loaiza, N., et al. (2019) · Cell · doi:10.1016/j.cell.2019.10.034 · Cited by 113
Angelakopoulou, A., Shah, T., Sofat, R., Shah, S. H., Berry, D. J., Cooper, J. A., Palmen, J., Tzoulaki, I., Wong, A., Jefferis, B. J. M. H., et al. (2011) · European Heart Journal · doi:10.1093/eurheartj/ehr225 · Cited by 114
Self-citationTranslating genome-wide association findings into new therapeutics for psychiatry
Breen, G. D., Li, Q. S., Roth, B. L., O’Donnell, P., Didriksen, M., Dolmetsch, R. E., O’Reilly, P. F., Gaspar, H. A., Manji, H. K., Hüebel, C., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4411 · Cited by 116
Genetic Architecture of Familial Hypercholesterolaemia
Sharifi, M., Futema, M., Nair, D. R., & Humphries, S. E. (2017) · Current Cardiology Reports · doi:10.1007/s11886-017-0848-8 · Cited by 116
Polypeptide GalNAc-Ts: from redundancy to specificity
Rivas, M. D. L., Lira‐Navarrete, E., Gerken, T. A., & Hurtado‐Guerrero, R. (2019) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2018.12.007 · Cited by 112
Efficient set tests for the genetic analysis of correlated traits
Casale, F. P., Rakitsch, B., Lippert, C., & Stegle, O. (2015) · Nature Methods · doi:10.1038/nmeth.3439 · Cited by 116
Wu, Y., Waite, L. L., Jackson, A., Sheu, W. H., Buyske, S. G., Absher, D., Arnett, D. K., Boerwinkle, E., Bonnycastle, L. L., Carty, C. L., et al. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003379 · Cited by 112
Self-citationBriot, A., Civelek, M., Seki, A., Hoi, K. K., Mack, J. J., Lee, S. D., Kim, J., Hong, C., Yu, J., Fishbein, G. A., et al. (2015) · The Journal of Experimental Medicine · doi:10.1084/jem.20150603 · Cited by 116
Neuroinflammation and comorbidities are frequently ignored factors in CNS pathology
Popa‐Wagner, A., Sandu, R. E., Buga, A.-M., Uzoni, A., & Petcu, E. B. (2015) · Neural Regeneration Research · doi:10.4103/1673-5374.165208 · Cited by 112
Multiancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions
de Vries, P. S., Brown, M. R., Bentley, A. R., Sung, Y. J., Winkler, T. W., Ντάλλα, Ι., Schwander, K., Kraja, A. T., Guo, X., Franceschini, N., et al. (2019) · American Journal of Epidemiology · doi:10.1093/aje/kwz005 · Cited by 113
Self-citationReceptor-Mediated ER Export of Lipoproteins Controls Lipid Homeostasis in Mice and Humans
Wang, X., Wang, H., Xu, B., Huang, D., Nie, C., Pu, L., Zajac, G. J. M., Yan, H., Zhao, J., Shi, F., et al. (2020) · Cell Metabolism · doi:10.1016/j.cmet.2020.10.020 · Cited by 115
Self-citationTang, C. S.-M., Zhang, H., Cheung, C. Y. Y., Xu, M., Ho, J. C.-Y., Zhou, W., Cherny, S. S., Zhang, Y., Holmen, O. L., Au, K., et al. (2015) · Nature Communications · doi:10.1038/ncomms10206 · Cited by 111
Self-citationGenetics of Triglycerides and the Risk of Atherosclerosis
Dron, J. S., & Hegele, R. A. (2017) · Current Atherosclerosis Reports · doi:10.1007/s11883-017-0667-9 · Cited by 114
Self-citationThe genetics of familial combined hyperlipidaemia
Brouwers, M. C. G. J., van Greevenbroek, M. M. J., Stehouwer, C. D. A., de Graaf, J., & Stalenhoef, A. F. H. (2012) · Nature Reviews Endocrinology · doi:10.1038/nrendo.2012.15 · Cited by 109
Obesity genomics: assessing the transferability of susceptibility loci across diverse populations
Lu, Y., & Loos, R. J. F. (2013) · Genome Medicine · doi:10.1186/gm459 · Cited by 111
Self-citationChallenges in Elucidating the Genetics of Diabetic Retinopathy
Kuo, J. Z.-C., Wong, T. Y., & Rotter, J. I. (2013) · JAMA Ophthalmology · doi:10.1001/jamaophthalmol.2013.5024 · Cited by 111
Self-citationvan Setten, J., Išgum, I., Smolonska, J., Ripke, S., de Jong, P. A., Oudkerk, M., de Koning, H. J., Lammers, J. J., Zanen, P., Groen, H. J. M., et al. (2013) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2013.02.039 · Cited by 110
Fall, T., Salihović, S., Brandmaier, S., Nowak, C., Ganna, A., Gustafsson, S., Broeckling, C. D., Prenni, J. E., Kastenmüller, G., Peters, A., et al. (2016) · Diabetologia · doi:10.1007/s00125-016-4041-1 · Cited by 109
Self-citationThe Changing Face of HDL and the Best Way to Measure It
Karathanasis, S. K., Freeman, L. A., Gordon, S. M., & Remaley, A. T. (2016) · Clinical Chemistry · doi:10.1373/clinchem.2016.257725 · Cited by 112
Type 2 diabetes, glucose, insulin, BMI, and ischemic stroke subtypes
Larsson, S. C., Scott, R. A., Traylor, M., Langenberg, C., Hindy, G., Melander, O., Orho‐Melander, M., Seshadri, S. S., Wareham, N. J., & Markus, H. S. (2017) · Neurology · doi:10.1212/wnl.0000000000004173 · Cited by 109
Self-citationDeciphering the Emerging Complexities of Molecular Mechanisms at GWAS Loci
Cannon, M. E., & Mohlke, K. L. (2018) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2018.10.001 · Cited by 111
Self-citationA Guide to Applying the Sex-Gender Perspective to Nutritional Genomics
Corella, D., Coltell, Ó., Portolés, O., Sotos‐Prieto, M., Fernández-Carrión, R., Sabio, J. B. R., Zanón‐Moreno, V., Mattei, J., Sorlí, J. V., & Ordovás, J. M. (2018) · Nutrients · doi:10.3390/nu11010004 · Cited by 113
A guide to genome‐wide association analysis and post‐analytic interrogation
Reed, E. R., Núñez, S., Kulp, D., Qian, J., Reilly, M. P., & Foulkes, A. S. (2015) · Statistics in Medicine · doi:10.1002/sim.6605 · Cited by 122
Self-citationLi, M. J., Wang, L. Y., Xia, Z., Sham, P. C., & Wang, J. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt456 · Cited by 110
Self-citationBridging the molecular and biological functions of the oxysterol-binding protein family
Pietrangelo, A., & Ridgway, N. D. (2018) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-018-2795-y · Cited by 109
Zhang, R., & Abou‐Samra, A. (2014) · Cardiovascular Diabetology · doi:10.1186/s12933-014-0133-8 · Cited by 107
Strategic Approaches to Unraveling Genetic Causes of Cardiovascular Diseases
Marian, A. J., & Belmont, J. W. (2011) · Circulation Research · doi:10.1161/circresaha.110.236067 · Cited by 109
Hopewell, J. C., Parish, S., Offer, A. R., Link, E. K., Clarke, R., Lathrop, M. G., Armitage, J., Collins, R., & on behalf of the MRC/BHF Heart Protection Study Collaborative Group (2012) · European Heart Journal · doi:10.1093/eurheartj/ehs344 · Cited by 107
A random forest approach to capture genetic effects in the presence of population structure
Stephan, J., Stegle, O., & Beyer, A. (2015) · Nature Communications · doi:10.1038/ncomms8432 · Cited by 115
Molecular Basis of Autosomal Dominant Hypercholesterolemia
van der Graaf, A., Avis, H. J., Kusters, D. M., Vissers, M. N., Hutten, B. A., Defesche, J. C., Huijgen, R., Fouchier, S. W., Wijburg, F. A., Kastelein, J. J. P., et al. (2011) · Circulation · doi:10.1161/circulationaha.110.979450 · Cited by 106
Self-citationTargeted next-generation sequencing in monogenic dyslipidemias
Hegele, R. A., Ban, M. R., Cao, H., McIntyre, A. D., Robinson, J. F., & Wang, J. (2015) · Current Opinion in Lipidology · doi:10.1097/mol.0000000000000163 · Cited by 106
Self-citationLipidomics is providing new insight into the metabolic syndrome and its sequelae
Meikle, P. J., & Christopher, M. (2011) · Current Opinion in Lipidology · doi:10.1097/mol.0b013e3283453dbe · Cited by 106
Joshi, A. D., Andersson, C., Buch, S., Stender, S., Noordam, R., Weng, L.-C. C., Weeke, P., Auer, P. L., Boehm, B. O., Chen, C., et al. (2016) · Gastroenterology · doi:10.1053/j.gastro.2016.04.007 · Cited by 108
Self-citationAn ethnobotanical study of medicinal plants used to treat skin diseases in northern Pakistan
Malik, K., Ahmad, M., Zafar, M. N., Ullah, R., Mahmood, H. M., Parveen, B., Rashid, N., Sultana, S., Shah, S. N., & Lubna (2019) · BMC Complementary and Alternative Medicine · doi:10.1186/s12906-019-2605-6 · Cited by 112
Coronary Artery Disease Genetics Enlightened by Genome-Wide Association Studies
Kessler, T., & Schunkert, H. (2021) · JACC Basic to Translational Science · doi:10.1016/j.jacbts.2021.04.001 · Cited by 111
Self-citationPGC-1 Coactivators Regulate MITF and the Tanning Response
Shoag, J. E., Haq, R., Zhang, M., Liu, L., Rowe, G. C., Jiang, A., Koulisis, N., Farrel, C., Amos, C. I., Wei, Q., et al. (2012) · Molecular Cell · doi:10.1016/j.molcel.2012.10.027 · Cited by 107
Self-citationAgarwala, A., Rodrigues, A., Risman, M., McCoy, M., Trindade, K., Qu, L., Cuchel, M., Billheimer, J. T., & Rader, D. J. (2015) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.115.305504 · Cited by 109
Self-citationSayols-Baixeras, S., Subirana, I., Lluís-Ganella, C., Civeira, F., Roquer, J., Do, A., Absher, D., Cenarro, A., Muñoz, D., Soriano‐Tárraga, C., et al. (2016) · Human Molecular Genetics · doi:10.1093/hmg/ddw285 · Cited by 104
Cellular characterisation of the GCKR P446L variant associated with type 2 diabetes risk
Rees, M. G., Wincovitch, S., Schultz, J., Waterstradt, R., Beer, N. L., Baltrusch, S., Collins, F. S., & Gloyn, A. L. (2011) · Diabetologia · doi:10.1007/s00125-011-2348-5 · Cited by 103
Self-citationHolleboom, A. G., Karlsson, H., Lin, R.-S., Beres, T. M., Sierts, J. A., Herman, D. S., Stroes, E. S. G., Aerts, J. M. F. G., Kastelein, J. J. P., Motazacker, M. M., et al. (2011) · Cell Metabolism · doi:10.1016/j.cmet.2011.11.005 · Cited by 103
Self-citationJones, G. T., Bown, M. J., Grétarsdóttir, S., Romaine, S. P. R., Helgadóttir, A., Yu, G. Z., Tromp, G., Norman, P. E., Cao, J., Baas, A. F., et al. (2013) · Human Molecular Genetics · doi:10.1093/hmg/ddt141 · Cited by 105
Self-citationA decade in psychiatric GWAS research
Horwitz, T. B., Lam, K., Chen, Y., Xia, Y., & Liu, C. (2018) · Molecular Psychiatry · doi:10.1038/s41380-018-0055-z · Cited by 108
Self-citationIdentification of constrained sequence elements across 239 primate genomes
Kuderna, L. F. K., Ulirsch, J. C., Rashid, S., Ameen, M., Sundaram, L., Hickey, G., Cox, A. J., Gao, H., Kumar, A., Aguet, F., et al. (2024) · Nature · doi:10.1038/s41586-023-06798-8 · Cited by 129
Self-citationSafarova, M. S., Liu, H., & Kullo, I. (2016) · Journal of clinical lipidology · doi:10.1016/j.jacl.2016.08.001 · Cited by 102
Genetic Determinants Influencing Human Serum Metabolome among African Americans
Yu, B., Zheng, Y., Alexander, D. C., Morrison, A. C., Coresh, J., & Boerwinkle, E. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004212 · Cited by 104
Self-citationAmerindian-specific regions under positive selection harbour new lipid variants in Latinos
Ko, A., Cantor, R. M., Weissglas‐Volkov, D., Nikkola, E., Reddy, P. M. V. L., Sinsheimer, J. S., Paşaniuc, B., Brown, R., Alvarez, M., Rodríguez, A., et al. (2014) · Nature Communications · doi:10.1038/ncomms4983 · Cited by 108
Self-citationRaffler, J., Friedrich, N., Arnold, M., Kacprowski, T., Rueedi, R., Altmaier, E., Bergmann, S., Budde, K., Gieger, C., Homuth, G., et al. (2015) · PLoS Genetics · doi:10.1371/journal.pgen.1005487 · Cited by 102
Self-citationHirschhorn, J. N., & Gajdos, Z. K. Z. (2010) · Annual Review of Medicine · doi:10.1146/annurev.med.091708.162036 · Cited by 105
Zeng, K., Chen, X., Hu, X., Liu, X., Xu, T., Sun, H., Pan, Y., He, B., & Wang, S. (2018) · Oncogene · doi:10.1038/s41388-018-0352-7 · Cited by 101
Zhu, X., & Stephens, M. (2018) · Nature Communications · doi:10.1038/s41467-018-06805-x · Cited by 103
Ji, Y., Yiorkas, A. M., Frau, F., Mook‐Kanamori, D. O., Staiger, H., Thomas, E. L., Atabaki‐Pasdar, N., Campbell, A., Tyrrell, J., Jones, S. E., et al. (2018) · Diabetes · doi:10.2337/db18-0708 · Cited by 102
Self-citationGurda, D., Handschuh, L., Kotkowiak, W., & Jakubowski, H. (2015) · Amino Acids · doi:10.1007/s00726-015-1956-7 · Cited by 104
Grallert, H., Dupuis, J., Bis, J. C., Dehghan, A., Barbalic, M., Baumert, J., Lu, C., Smith, N. L., Uitterlinden, A. G., Roberts, R., et al. (2012) · European Heart Journal · doi:10.1093/eurheartj/ehr372 · Cited by 83
Self-citationGenetic Predisposition to Dyslipidemia and Type 2 Diabetes Risk in Two Prospective Cohorts
Qi, Q., Liang, L., Doria, A., Hu, F. B., & Qi, L. (2012) · Diabetes · doi:10.2337/db11-1254 · Cited by 100
Genetic Basis of Atherosclerosis: Insights From Mice and Humans
Stylianou, I. M., Bauer, R. C., Reilly, M. P., & Rader, D. J. (2012) · Circulation Research · doi:10.1161/circresaha.110.230854 · Cited by 99
Self-citationComprehensive genetic study of the insulin resistance marker TG:HDL-C in the UK Biobank
Oliveri, A., Rebernick, R. J., Kuppa, A., Pant, A., Chen, Y., Du, X., Cushing, K. C., Bell, H. N., Raut, C., Prabhu, P., et al. (2024) · Nature Genetics · doi:10.1038/s41588-023-01625-2 · Cited by 103
Self-citationMiddelberg, R. P. S., Ferreira, M. A. R., Henders, A. K., Heath, A. C., Madden, P. A. F., Montgomery, G. W., Martin, N. G., & Whitfield, J. B. (2011) · BMC Medical Genetics · doi:10.1186/1471-2350-12-123 · Cited by 99
Self-citationAmundadottir, L. T. (2016) · International Journal of Biological Sciences · doi:10.7150/ijbs.15001 · Cited by 98
TTC39B deficiency stabilizes LXR reducing both atherosclerosis and steatohepatitis
Hsieh, J., Koseki, M., Molusky, M. M., Yakushiji, E., Ichi, I., Westerterp, M., Iqbal, J., Chan, R., Abramowicz, S., Tascau, L., et al. (2016) · Nature · doi:10.1038/nature18628 · Cited by 98
Self-citationFunctional Characterization of the GUCY1A3 Coronary Artery Disease Risk Locus
Kessler, T., Wobst, J., Wolf, B. A., Eckhold, J., Vilne, B., Hollstein, R., von Ameln, S., Dang, T. A., Sager, H. B., Rumpf, P. M., et al. (2017) · Circulation · doi:10.1161/circulationaha.116.024152 · Cited by 100
Self-citationHigh-throughput multimodal automated phenotyping (MAP) with application to PheWAS
Liao, K. P., Sun, J., Cai, T. A., Link, N., Hong, C., Huang, J., Huffman, J. E., Gronsbell, J. L., Zhang, Y., Ho, Y.-L. A., et al. (2019) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocz066 · Cited by 98
Self-citationJohansen, C. T., Wang, J., Lanktree, M. B., McIntyre, A. D., Ban, M. R., Martins, R. A., Kennedy, B. A., Hassell, R. G., Visser, M. E., Schwartz, S. M., et al. (2011) · Arteriosclerosis, Thrombosis, and Vascular Biology · doi:10.1161/atvbaha.111.226365 · Cited by 97
Self-citationPerhexiline activates KLF14 and reduces atherosclerosis by modulating ApoA-I production
Guo, Y., Fan, Y., Zhang, J., Lomberk, G. A., Zhou, Z., Sun, L., Mathison, A., Garcia-Barrio, M. T., Zhang, J., Zeng, L., et al. (2015) · Journal of Clinical Investigation · doi:10.1172/jci79048 · Cited by 97
Self-citationScavenger Receptor class B type I (SR-BI): A versatile receptor with multiple functions and actions
Shen, W., Hu, J., Hu, Z., Kraemer, F. B., & Azhar, S. (2014) · Metabolism · doi:10.1016/j.metabol.2014.03.011 · Cited by 100
Increased High-Density Lipoprotein Cholesterol Levels in Mice With XX Versus XY Sex Chromosomes
Link, J. C., Chen, X., Prien, C., Borja, M. S., Hammerson, B., Oda, M. N., Arnold, A. P., & Reue, K. (2015) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.115.305460 · Cited by 97
Recurring exon deletions in the HP (haptoglobin) gene contribute to lower blood cholesterol levels
Boettger, L. M., Salem, R. M., Handsaker, R. E., Peloso, G. M., Kathiresan, S., Hirschhorn, J. N., & McCarroll, S. A. (2016) · Nature Genetics · doi:10.1038/ng.3510 · Cited by 98
Self-citationGenome-wide DNA methylation and long-term ambient air pollution exposure in Korean adults
Lee, M. K., Xu, C., Carnes, M. U., Nichols, C. E., Ward, J. M., Kwon, S. O., Kim, S., Kim, W. J., & London, S. J. (2019) · Clinical Epigenetics · doi:10.1186/s13148-019-0635-z · Cited by 96
Westra, H.-J., Jansen, R. C., Fehrmann, R. S. N., Meerman, G. J. T., van Heel, D. A., Wijmenga, C., & Franke, L. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr323 · Cited by 96
Population Structure of Hispanics in the United States: The Multi-Ethnic Study of Atherosclerosis
Manichaikul, A. W., Palmas, W., Rodríguez, C. J., Peralta, C. A., Divers, J., Guo, X., Chen, W., Wong, Q., Williams, K., Kerr, K. F., et al. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002640 · Cited by 96
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 104
Blood CSF1 and CXCL12 as Causal Mediators of Coronary Artery Disease
Sjaarda, J., Gerstein, H., Chong, M., Yusuf, S., Meyre, D., Anand, S. S., Hess, S., & Paré, G. (2018) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2018.04.067 · Cited by 94
Metabolic profiling in diabetes
Suhre, K. (2014) · Journal of Endocrinology · doi:10.1530/joe-14-0024 · Cited by 99
HDL Cholesterol Metabolism and the Risk of CHD: New Insights from Human Genetics
Vitali, C., Khetarpal, S. A., & Rader, D. J. (2017) · Current Cardiology Reports · doi:10.1007/s11886-017-0940-0 · Cited by 96
Self-citationTranslational regulation shapes the molecular landscape of complex disease phenotypes
Schäfer, S., Adami, E., Heinig, M., Rodrigues, K. E. C., Kreuchwig, F., Šilhavý, J., van Heesch, S., Šimaitė, D., Rajewsky, N., Cuppen, E. P. J. G., et al. (2015) · Nature Communications · doi:10.1038/ncomms8200 · Cited by 96
Proitsi, P., Lupton, M. K., Velayudhan, L., Newhouse, S., Fogh, I., Tsolaki, M., Daniilidou, M., Pritchard, M., Kłoszewska, I., Soininen, H. S., et al. (2014) · PLoS Medicine · doi:10.1371/journal.pmed.1001713 · Cited by 100
Repurposing drugs to treat cardiovascular disease in the era of precision medicine
Abdelsayed, M., Kort, E. J., Jovinge, S., & Mercola, M. (2022) · Nature Reviews Cardiology · doi:10.1038/s41569-022-00717-6 · Cited by 93
Assessing the utility of intermediate phenotypes for genetic mapping of psychiatric disease
Flint, J., Timpson, N. J., & Munafo, M. R. (2014) · Trends in Neurosciences · doi:10.1016/j.tins.2014.08.007 · Cited by 98
Tachmazidou, I., Dedoussis, G. V., Southam, L., Farmaki, A., Ritchie, G. R. S., Xifara, D. K., Matchan, A., Hatzikotoulas, K., Rayner, N. W., Chen, Y., et al. (2013) · Nature Communications · doi:10.1038/ncomms3872 · Cited by 96
Self-citationJohansen, C. T., Wang, J., McIntyre, A. D., Martins, R. A., Ban, M. R., Lanktree, M. B., Huff, M. W., Péterfy, M., Mehrabian, M., Lusis, A. J., et al. (2011) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.111.960864 · Cited by 93
Self-citationVrieze, S. I., McGue, M. K., Miller, M. B., Hicks, B. M., & Iacono, W. G. (2013) · Behavior Genetics · doi:10.1007/s10519-013-9584-z · Cited by 93
Krauss, R. M., Wojnooski, K., Orr, J., Geaney, J. C., Pinto, C. A., Liu, Y., Wagner, J. A., Luk, J. A. M., Johnson‐Levonas, A. O., Anderson, M. S., et al. (2011) · Journal of Lipid Research · doi:10.1194/jlr.m018010 · Cited by 94
Self-citationA Variant in LDLR Is Associated With Abdominal Aortic Aneurysm
Bradley, D., Hughes, A. E., Badger, S. A., Jones, G. T., Harrison, S. C., Wright, B. J., Bumpstead, S., Baas, A. F., Grétarsdóttir, S., Burnand, K. G., et al. (2013) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.113.000165 · Cited by 96
Self-citationIjssennagger, N., Janssen, A. W. F., Milona, A., Pittol, J. M. R., Hollman, D. A. A., Mokrý, M., Betzel, B., Berends, F. J., Janssen, I. M. C., van Mil, S. W. C., et al. (2016) · Journal of Hepatology · doi:10.1016/j.jhep.2016.01.016 · Cited by 94
Southam, L., Gilly, A., Süveges, D., Farmaki, A., Schwartzentruber, J., Tachmazidou, I., Matchan, A., Rayner, N. W., Tsafantakis, E., Karaleftheri, M., et al. (2017) · Nature Communications · doi:10.1038/ncomms15606 · Cited by 96
Current concepts and clinical applications of stroke genetics
Falcone, G. J., Malik, R., Dichgans, M., & Rosand, J. M. (2014) · The Lancet Neurology · doi:10.1016/s1474-4422(14)70029-8 · Cited by 98
Kirsten, H., Al-Hasani, H., Holdt, L. M., Gross, A., Beutner, F., Krohn, K., Horn, K., Ahnert, P., Burkhardt, R., Reiche, K., et al. (2015) · Human Molecular Genetics · doi:10.1093/hmg/ddv194 · Cited by 93
Stančáková, A., Paananen, J., Soininen, P., Kangas, A. J., Bonnycastle, L. L., Morken, M. A., Collins, F. S., Jackson, A., Boehnke, M., Kuusisto, J., et al. (2011) · Diabetes · doi:10.2337/db10-1655 · Cited by 92
Self-citationHepatic Transmembrane 6 Superfamily Member 2 Regulates Cholesterol Metabolism in Mice
Fan, Y., Lu, H., Guo, Y., Zhu, T., Garcia-Barrio, M. T., Jiang, Z., Willer, C. J., Zhang, J., & Chen, Y. (2016) · Gastroenterology · doi:10.1053/j.gastro.2016.01.005 · Cited by 92
Self-citationShen, X., Klarić, L., Sharapov, S., Mangino, M., Zheng, N., Wu, D., Trbojević‐Akmačić, I., Pučić‐Baković, M., Rudan, I., Polašek, O., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-00453-3 · Cited by 93
Self-citationSilva, N. M. G. D., Freathy, R. M., Palmer, T., Donnelly, L. A., Luan, J., Gaunt, T. R., Langenberg, C., Weedon, M. N., Shields, B. M., Knight, B. A., et al. (2011) · Diabetes · doi:10.2337/db10-1317 · Cited by 91
Self-citationKirchhof, P. F., Medicine, E. C. R. A. E. A. W. S. O. P., Sipido, K. R., Medicine, E. C. R. A. E. A. W. S. O. P., Cowie, M., Medicine, E. C. R. A. E. A. W. S. O. P., Eschenhagen, T., Medicine, E. C. R. A. E. A. W. S. O. P., Fox, K. A. A., Medicine, E. C. R. A. E. A. W. S. O. P., et al. (2014) · European Heart Journal · doi:10.1093/eurheartj/ehu312 · Cited by 93
Self-citationThe transferability of lipid loci across African, Asian and European cohorts
Kuchenbaecker, K. B., Telkar, N., Reiker, T., Walters, R. G., Lin, K., Eriksson, A., Gurdasani, D., Gilly, A., Southam, L., Tsafantakis, E., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-12026-7 · Cited by 91
Self-citationIRF2BP2 Reduces Macrophage Inflammation and Susceptibility to Atherosclerosis
Chen, H.-H., Keyhanian, K., Zhou, X., Vilmundarson, R. O., Almontashiri, N. A. M., Cruz, S. A., Pandey, N. R., Lerma Yap, N., Ho, T., Stewart, C. A., et al. (2015) · Circulation Research · doi:10.1161/circresaha.114.305777 · Cited by 91
Self-citationRoss, S., D’Mello, M., Anand, S. S., Eikelboom, J., CARDIoGRAMplusC4D Consortium*, Stewart, A. F. R., Samani, N. J., Roberts, R., & Paré, G. (2015) · Circulation: Cardiovascular Genetics · doi:10.1161/circgenetics.114.000952 · Cited by 90
Self-citationDetailed metabolic and genetic characterization reveals new associations for 30 known lipid loci
Tukiainen, T., Kettunen, J., Kangas, A. J., Lyytikäinen, L., Soininen, P., Sarin, A., Tikkanen, E., O’Reilly, P. F., Savolainen, M. J., Kaski, K. K., et al. (2011) · Human Molecular Genetics · doi:10.1093/hmg/ddr581 · Cited by 92
Self-citationTintle, N., Pottala, J. V., Lacey, S., Vasan, R. S., Westra, J., Rogers, A., Clark, J., Olthoff, B., Larson, M. G., Harris, W. S., et al. (2014) · Prostaglandins Leukotrienes and Essential Fatty Acids · doi:10.1016/j.plefa.2014.11.007 · Cited by 91
Mendelian Randomization Studies of Coffee and Caffeine Consumption
Cornelis, M. C., & Munafo, M. R. (2018) · Nutrients · doi:10.3390/nu10101343 · Cited by 89
Dron, J. S., Wang, J., McIntyre, A. D., Iacocca, M. A., Robinson, J. F., Ban, M. R., Cao, H., & Hegele, R. A. (2020) · BMC Medical Genomics · doi:10.1186/s12920-020-0669-2 · Cited by 93
Self-citationKONES, R. J. (2013) · Vascular Health and Risk Management · doi:10.2147/vhrm.s37119 · Cited by 91
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 ›
Are you an author, or do you see a problem with this page? Request a review
