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
Flagged first, then by citations
Cited by
Sorted by citations
Items 801–900 of 1,028
Mozaffarian, D., Kabagambe, E. K., Johnson, C. O., Lemaître, R. N., Manichaikul, A. W., Sun, Q., Foy, M., Wang, L., Wiener, H. W., Irvin, M. R., et al. (2014) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.114.094557 · Cited by 64
Self-citationCommon and Low-Frequency Genetic Variants in the PCSK9 Locus Influence Circulating PCSK9 Levels
Chernogubova, E., Strawbridge, R. J., Mahdessian, H., Mälarstig, A., Krapivner, S., Gigante, B., Hellénius, M.-L., Fairé, U. D., Franco‐Cereceda, A., Syvänen, A.-C., et al. (2012) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.111.240549 · Cited by 66
Mente, A., Meyre, D., Lanktree, M. B., Heydarpour, M., Davis, A. D., Miller, R., Gerstein, H. C., Hegele, R. A., Yusuf, S., Anand, S. S., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0066808 · Cited by 64
Self-citationHuang, J., Johnson, A. D., & O’Donnell, C. J. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr116 · Cited by 64
Self-citationTRIB1 downregulates hepatic lipogenesis and glycogenesis via multiple molecular interactions
Ishizuka, Y., Nakayama, K., Ogawa, A., Makishima, S., Boonvisut, S., Hirao, A., Iwasaki, Y., Yada, T., Yanagisawa, Y., Miyashita, H., et al. (2014) · Journal of Molecular Endocrinology · doi:10.1530/jme-13-0243 · Cited by 65
Lu, X., Huang, J., Mo, Z., He, J., Wang, L., Yang, X., Tan, A., Chen, S., Chen, J., Gu, C. C., et al. (2015) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.115.001096 · Cited by 64
ABCA8 Regulates Cholesterol Efflux and High-Density Lipoprotein Cholesterol Levels
Trigueros‐Motos, L., van Capelleveen, J. C., Torta, F. T., Castaño, D., Zhang, L., Chai, E. C., Kang, M. H., Dimova, L. G., Schimmel, A. W. M., Tietjen, I., et al. (2017) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.117.309574 · Cited by 64
Macrophage fatty acid metabolism and atherosclerosis: The rise of PUFAs
Ménégaut, L., Jalil, A., Thomas, C., & Masson, D. (2019) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2019.10.002 · Cited by 64
Self-citationNordestgaard, B. G., & Tybjærg‐Hansen, A. (2011) · Current Opinion in Lipidology · doi:10.1097/mol.0b013e32834477d2 · Cited by 64
Gill, D., Benyamin, B., Moore, L. S. P., Monori, G., Zhou, A., Koskeridis, F., Evangelou, E., Laffan, M., Walker, A. P., Tsilidis, K. K., et al. (2019) · PLOS Medicine · doi:10.1371/journal.pmed.1002833 · Cited by 63
Self-citationPolygenic link between blood lipids and amyotrophic lateral sclerosis
Chen, X., Yazdani, S., Piehl, F., Magnusson, P. K. E., & Fang, F. (2018) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2018.03.022 · Cited by 63
Self-citationKanoni, S., Graham, S. E., Wang, Y., Surakka, I. L., Ramdas, S., Zhu, X., Clarke, S. L., Bhatti, K. F., Vedantam, S., Winkler, T. W., et al. (2022) · Genome biology · doi:10.1186/s13059-022-02837-1 · Cited by 65
Self-citationMortality and cancer in relation to ABO blood group phenotypes in the Golestan Cohort Study
Etemadi, A., Kamangar, F., Islami, F., Poustchi, H., Pourshams, A., Brennan, P., Boffetta, P., Malekzadeh, R., Dawsey, S. M., Abnet, C. C., et al. (2015) · BMC Medicine · doi:10.1186/s12916-014-0237-8 · Cited by 63
Gaidukov, L., Nager, A. R., Xu, S., Penman, M., & Krieger, M. (2011) · Journal of Biological Chemistry · doi:10.1074/jbc.m111.229872 · Cited by 63
Guo, S., Vollesen, A. L. H., Hansen, Y. B. L., Frandsen, E., Andersen, M. R., Amin, F. M., Fahrenkrug, J., Olesen, J., & Ashina, M. (2016) · Cephalalgia · doi:10.1177/0333102416639517 · Cited by 63
Liang, X., Yee, S. W., Chien, H., Chen, E. C., Luo, Q., Zou, L., Piao, M., Mifune, A., Chen, L., Calvert, M., et al. (2018) · PLoS Biology · doi:10.1371/journal.pbio.2002907 · Cited by 66
Self-citationThormaehlen, A. S., Schuberth, C. E., Won, H., Blattmann, P., Joggerst-Thomalla, B., Theiß, S., Asselta, R., Duga, S., Merlini, P. A., Ardissino, D., et al. (2016) · Figshare · doi:10.1371/journal.pgen.1004855 · Cited by 63
Self-citationFrom genotype to phenotype in human atherosclerosis - recent findings
Holdt, L. M., & Teupser, D. (2013) · Current Opinion in Lipidology · doi:10.1097/mol.0b013e3283654e7c · Cited by 62
Efstathiadou, A., Gill, D., McGrane, F., Quinn, T. J., & Dawson, J. (2019) · Journal of the American Heart Association · doi:10.1161/jaha.119.012738 · Cited by 63
Cheng, Q., Yang, Y., Shi, X., Yeung, K.-F., Yang, C., Peng, H., & Liu, J. (2020) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqaa028 · Cited by 63
Vrablı́k, M., Dlouhá, D., Todorovová, V., Stefler, D., & Hubacek, J. A. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22084182 · Cited by 67
Connolly, J. J., Glessner, J., & Hakonarson, H. H. (2012) · Child Development · doi:10.1111/j.1467-8624.2012.01838.x · Cited by 66
Bottolo, L., Chadeau‐Hyam, M., Hastie, D. I., Zeller, T., Liquet, B., Newcombe, P. J., Yengo, L., Wild, P. S., Schillert, A., Ziegler, A., et al. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003657 · Cited by 64
Self-citationNeve, E. P. A., Nordling, Å., Andersson, T. B., Hellman, U., Diczfalusy, U., Johansson, I., & Ingelman‐Sundberg, M. (2011) · Journal of Biological Chemistry · doi:10.1074/jbc.m111.328237 · Cited by 62
HNRNPA1 regulates HMGCR alternative splicing and modulates cellular cholesterol metabolism
Yu, C.-Y., Theusch, E., Lo, K., Mangravite, L. M., Naidoo, D., Kutilova, M., & Medina, M. W. (2013) · Human Molecular Genetics · doi:10.1093/hmg/ddt422 · Cited by 62
Several genetic polymorphisms interact with overweight/obesity to influence serum lipid levels
Yin, R., Wu, D., Miao, L., Aung, L. H. H., Cao, X., Yan, T.-T., Long, X., Liu, W., Zhang, L., & Li, M. (2012) · Cardiovascular Diabetology · doi:10.1186/1475-2840-11-123 · Cited by 62
Self-citationJoshi, H. J., Hansen, L. H., Narimatsu, Y., Freeze, H. H., Henrissat, B., Bennett, E., Wandall, H. H., Clausen, H., & Schjoldager, K. T.-B. G. (2018) · Glycobiology · doi:10.1093/glycob/cwy015 · Cited by 62
Angiopoietin-Like 3 (ANGPTL3) and Atherosclerosis: Lipid and Non-Lipid Related Effects
Lupo, M. G., & Ferri, N. (2018) · Journal of Cardiovascular Development and Disease · doi:10.3390/jcdd5030039 · Cited by 64
Lectin Domains of Polypeptide GalNAc Transferases Exhibit Glycopeptide Binding Specificity
Pedersen, J. W., Bennett, E., Schjoldager, K. T.-B. G., Meldal, M., Holmér, A. P., Blixt, O., Cló, E., Levery, S. B., Clausen, H., & Wandall, H. H. (2011) · Journal of Biological Chemistry · doi:10.1074/jbc.m111.273722 · Cited by 62
Long-Term Effectiveness of Liraglutide for Weight Management and Glycemic Control in Type 2 Diabetes
Mirabelli, M., Chiefari, E., Caroleo, P., Arcidiacono, B., Corigliano, D. M., Giuliano, S., Brunetti, F. S., Tanyolaç, S., Foti, D. P., Puccio, L., et al. (2019) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17010207 · Cited by 61
Relationship between genetic variation at PPP1R3B and levels of liver glycogen and triglyceride
Stender, S., Šmagris, Ē., Lauridsen, B. K., Kofoed, K. F., Nordestgaard, B. G., Tybjærg‐Hansen, A., Pennacchio, L. A., Dickel, D. E., Cohen, J. C., & Hobbs, H. H. (2017) · Hepatology · doi:10.1002/hep.29751 · Cited by 61
Feng, Q., Wei, W., Chaugai, S., Leon, B. G. C., Mosley, J. D., Leon, D. A. C., Jiang, L., Ihegword, A., Shaffer, C. M., Linton, M. F., et al. (2019) · JAMA Network Open · doi:10.1001/jamanetworkopen.2018.7223 · Cited by 61
Coordination of inter-organelle communication and lipid fluxes by OSBP-related proteins
Arora, A., Taskinen, J., & Olkkonen, V. M. (2022) · Progress in Lipid Research · doi:10.1016/j.plipres.2022.101146 · Cited by 64
The pathophysiology of intestinal lipoprotein production
Giammanco, A., Cefalu, A. B., Noto, D., & Averna, M. R. (2015) · Frontiers in Physiology · doi:10.3389/fphys.2015.00061 · Cited by 68
A Genome-Wide Association Study of Central Corneal Thickness in Latinos
Gao, X., Gauderman, W. J., Liu, Y., Marjoram, P., Torres, M., Haritunians, T., Kuo, J., Chen, Y. I., Allingham, R. R., Hauser, M. A., et al. (2013) · Investigative Ophthalmology & Visual Science · doi:10.1167/iovs.13-11692 · Cited by 62
Self-citationWu, X., Wang, L., Ye, Y., Aakre, J. A., Pu, X., Chang, G.-C., Yang, P., Roth, J. A., Marks, R. S., Lippman, S. M., et al. (2013) · Cancer Research · doi:10.1158/0008-5472.can-12-4033 · Cited by 61
Guay, S., Brisson, D., Lamarche, B., Marceau, P., Vohl, M., Gaudet, D., & Bouchard, L. (2013) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2013.03.033 · Cited by 61
Zhang, R., Witkowska, K., Guerra‐Assunção, J. A., Ren, M., Ng, F. L., Mauro, C., Tucker, A. T., Caulfield, M. J., & Ye, S. (2016) · Human Molecular Genetics · doi:10.1093/hmg/ddw236 · Cited by 61
Self-citationLoss of Cardioprotective Effects at the ADAMTS7 Locus as a Result of Gene-Smoking Interactions
Saleheen, D., Zhao, W., Young, R., Nelson, C. P., Ho, W.-K., Ferguson, J. F., Rasheed, A., Ou, K., Nürnberg, S., Bauer, R. C., et al. (2017) · Circulation · doi:10.1161/circulationaha.116.022069 · Cited by 61
Self-citationPeng, S., Deyssenroth, M. A., Narzo, A. F. D., Lambertini, L., Marsit, C. J., Chen, J., & Hao, K. (2017) · Human Molecular Genetics · doi:10.1093/hmg/ddx265 · Cited by 66
The contribution of GWAS loci in familial dyslipidemias
Ripatti, P., Rämö, J. T., Söderlund, S., Surakka, I., Matikainen, N., Pirinen, M., Pajukanta, P., Sarin, A.-P., Service, S. K., Laurila, P.-P., et al. (2016) · PLOS Genetics · doi:10.1371/journal.pgen.1006078 · Cited by 60
Self-citationMendelson, M. M., Lyass, A., O’Donnell, C. J., D’Agostino, R. B., & Levy, D. (2016) · JAMA Cardiology · doi:10.1001/jamacardio.2015.0304 · Cited by 60
Self-citationTurner, S., Berg, R. L., Linneman, J. G., Peissig, P. L., Crawford, D. C., Denny, J. C., Roden, D. M., McCarty, C. A., Ritchie, M. D., & Wilke, R. A. (2011) · PLoS ONE · doi:10.1371/journal.pone.0019586 · Cited by 63
Tran, D. T., Zhang, L., Zhang, Y., Tian, E., Earl, L. A., & Hagen, K. G. T. (2011) · Journal of Biological Chemistry · doi:10.1074/jbc.m111.306159 · Cited by 60
Evidence of a Polygenic Origin of Extreme High-Density Lipoprotein Cholesterol Levels
Motazacker, M. M., Peter, J., Treskes, M., Shoulders, C. C., Kuivenhoven, J. A., & Hovingh, G. K. (2013) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.113.301505 · Cited by 62
Arvind, P., Nair, J., Jambunathan, S., Kakkar, V. V., & Shanker, J. (2014) · Journal of Cardiology · doi:10.1016/j.jjcc.2014.02.012 · Cited by 60
Zhang, X., Qi, Q., Bray, G. A., Hu, F. B., Sacks, F. M., & Qi, L. (2012) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.112.040907 · Cited by 60
Exome-chip meta-analysis identifies novel loci associated with cardiac conduction, including ADAMTS6
Prins, B. P., Mead, T. J., Brody, J. A., Sveinbjörnsson, G., Ντάλλα, Ι., Bihlmeyer, N. A., van den Berg, M., Bork‐Jensen, J., Cappellani, S., van Duijvenboden, S., et al. (2018) · Genome biology · doi:10.1186/s13059-018-1457-6 · Cited by 62
Self-citationSliz, E., Kalaoja, M., Ahola-Olli, A., Raitakari, O., Perola, M., Salomaa, V., Lehtimäki, T., Karhu, T., Viinamäki, H., Salmi, M., et al. (2019) · Journal of Medical Genetics · doi:10.1136/jmedgenet-2018-105965 · Cited by 60
Self-citationMendelian Randomization: Application to Cardiovascular Disease
Timpson, N. J., Wade, K. H., & Smith, G. D. (2011) · Current Hypertension Reports · doi:10.1007/s11906-011-0242-7 · Cited by 60
Singaraja, R. R., Sivapalaratnam, S., Hovingh, K., Dubé, M., Castro‐Perez, J. M., Collins, H. L., Adelman, S. J., Riwanto, M., Manz, J., Hubbard, B. K., et al. (2012) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.111.962613 · Cited by 60
Self-citationA glycogene mutation map for discovery of diseases of glycosylation
Hansen, L. H., Lind-Thomsen, A., Joshi, H. J., Borbye‐Lorenzen, N., Have, C. T., Kong, Y., Wang, S., Sparsø, T., Grarup, N., Vester-Christensen, M. B., et al. (2014) · Glycobiology · doi:10.1093/glycob/cwu104 · Cited by 59
Kolder, I. C. R. M., Tanck, M. W. T., & Bezzina, C. R. (2012) · Journal of Molecular and Cellular Cardiology · doi:10.1016/j.yjmcc.2011.12.014 · Cited by 59
Hirokawa, M., Morita, H., Tajima, T., Takahashi, A., Ashikawa, K., Miya, F., Shigemizu, D., Ozaki, K., Sakata, Y., Nakatani, D., et al. (2014) · European Journal of Human Genetics · doi:10.1038/ejhg.2014.110 · Cited by 59
Self-citationvan Leeuwen, E. M., Karssen, L. C., Deelen, J., Isaacs, A. J., Medina‐Gómez, C., Mbarek, H., Kanterakis, A., Trompet, S., Postmus, I., Verweij, N., et al. (2015) · Nature Communications · doi:10.1038/ncomms7065 · Cited by 61
Self-citationChang, M., Ned, R. M., Hong, Y., Yesupriya, A., Yang, Q., Liu, T., Janssens, A. C. J. W., & Dowling, N. F. (2011) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.111.959577 · Cited by 60
Morag, A., Pasmanik, M., Oron‐Karni, V., Rehavi, M., Stingl, J., & Gurwitz, D. (2011) · Pharmacogenomics · doi:10.2217/pgs.10.185 · Cited by 64
Li, L., Kabesch, M., Bouzigon, E., Démenais, F., Farrall, M., Moffatt, M. F., Lin, X., & Liang, L. (2013) · Frontiers in Genetics · doi:10.3389/fgene.2013.00103 · Cited by 60
LDL cholesterol still a problem in old age? A Mendelian randomization study
Postmus, I., Deelen, J., Sedaghat, S., Trompet, S., de Craen, A. J. M., Heijmans, B. T., Franco, O. H., Albert Hofman, D., Dehghan, A., Slagboom, P. E., et al. (2015) · International Journal of Epidemiology · doi:10.1093/ije/dyv031 · Cited by 60
Roman, T. S., Marvelle, A. F., Fogarty, M. P., Vadlamudi, S., Gonzalez, A. J., Buchkovich, M. L., Huyghe, J. R., Fuchsberger, C., Jackson, A., Wu, Y., et al. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.10.016 · Cited by 59
Self-citationEhrhardt, N., Doche, M. E., Chen, S., Mao, H. Z., Walsh, M. T., Bedoya, C., Guindi, M. M., Xiong, W., Irudayam, J. I., Iqbal, J., et al. (2017) · Human Molecular Genetics · doi:10.1093/hmg/ddx159 · Cited by 60
Multiple Phenotype Association Tests Using Summary Statistics in Genome-wide Association Studies
Liu, Z., & Lin, X. (2017) · Biometrics · doi:10.1111/biom.12735 · Cited by 59
Toth, P. P., Philip, S., HULL, M. L., & Granowitz, C. B. (2019) · Mayo Clinic Proceedings · doi:10.1016/j.mayocp.2019.03.028 · Cited by 60
Pseudokinases: a tribble‐edged sword
Richmond, L., & Keeshan, K. (2019) · FEBS Journal · doi:10.1111/febs.15096 · Cited by 61
Ren, L., Sun, Y., Lu, H., Ye, D., Han, L., Wang, N., Daugherty, A., Li, F., Wang, M., Su, F., et al. (2018) · Circulation Research · doi:10.1161/circresaha.117.312422 · Cited by 59
Yeung, M. W., Wang, S., van de Vegte, Y. J., Borisov, O., van Setten, J., Snieder, H., Verweij, N., Said, M. A., & van der Harst, P. (2021) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.121.317007 · Cited by 58
ANGPTL3 inhibition, dyslipidemia, and cardiovascular diseases
Luo, F., Das, A., Khetarpal, S. A., Fang, Z., Zelniker, T. A., Rosenson, R. S., & Qamar, A. (2023) · Trends in Cardiovascular Medicine · doi:10.1016/j.tcm.2023.01.008 · Cited by 58
Miao, J., Guo, H., Song, G., Zhao, Z., Hou, L., & Lu, Q. (2023) · Nature Communications · doi:10.1038/s41467-023-36544-7 · Cited by 61
Phenotypic extremes in rare variant study designs
Peloso, G. M., Rader, D. J., Gabriel, S., Kathiresan, S., Daly, M. J., & Neale, B. M. (2016) · European Journal of Human Genetics · doi:10.1038/ejhg.2015.197 · Cited by 58
Self-citationBrunzell, J. D., Zambon, A., & Deeb, S. S. (2011) · Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids · doi:10.1016/j.bbalip.2011.09.008 · Cited by 61
Next Steps in Cardiovascular Disease Genomic Research—Sequencing, Epigenetics, and Transcriptomics
Schnabel, R. B., Baccarelli, A., Lin, H., Ellinor, P. T., & Benjamin, E. J. (2011) · Clinical Chemistry · doi:10.1373/clinchem.2011.170423 · Cited by 58
Yu, M., Romer, K. A., Nieland, T. J. F., Xu, S., Saenz-Vash, V., Penman, M., Yesilaltay, A., Carr, S. A., & Krieger, M. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1109078108 · Cited by 58
Sorrentino, V., Fouchier, S. W., Motazacker, M. M., Nelson, J. K., Defesche, J. C., Dallinga‐Thie, G. M., Kastelein, J. J. P., Hovingh, G. K., & Zelcer, N. (2013) · European Heart Journal · doi:10.1093/eurheartj/ehs472 · Cited by 59
Self-citationDevelopment and rescue of human familial hypercholesterolaemia in a xenograft mouse model
Bissig-Choisat, B., Wang, L., Legras, X. D., Saha, P., Chen, L. L., Bell, P. L., Pankowicz, F. P., Hill, M. C., Barzi, M., Leyton, C. K., et al. (2015) · Nature Communications · doi:10.1038/ncomms8339 · Cited by 58
Self-citationKim, D. S., Jackson, A. U., Li, Y. K., Stringham, H. M., Kuusisto, J., Kangas, A. J., Soininen, P., Ala‐Korpela, M., Burant, C., Salomaa, V. V., et al. (2017) · Journal of Lipid Research · doi:10.1194/jlr.p076034 · Cited by 60
Self-citationThe polygenic nature of telomere length and the anti-ageing properties of lithium
Coutts, F., Palmos, A., Duarte, R. R. R., de Jong, S., Lewis, C. M., Dima, D., & Powell, T. R. (2018) · Neuropsychopharmacology · doi:10.1038/s41386-018-0289-0 · Cited by 58
Hindy, G., Åkesson, K., Melander, O., Aragam, K. G., Haas, M. E., Nilsson, P. M., Kadam, U. T., & Orho‐Melander, M. (2019) · Arthritis & Rheumatology · doi:10.1002/art.40812 · Cited by 59
Self-citationThe evolution of genetic-based risk scores for lipids and cardiovascular disease
Dron, J. S., & Hegele, R. A. (2019) · Current Opinion in Lipidology · doi:10.1097/mol.0000000000000576 · Cited by 59
Self-citationAdvances in Exercise, Fitness, and Performance Genomics in 2012
Përusse, L., Rankinen, T., Hagberg, J. M., Loos, R. J. F., Roth, S. M., Sarzynski, M. A., Wolfarth, B., & Bouchard, C. (2013) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0b013e31828b28a3 · Cited by 58
Self-citationOrchard, P., Manickam, N., Varshney, A., Vadlamudi, S., Burant, C., Parker, S. C. J., Kaplan, J., Lalancette, C., Mohlke, K. L., Gallagher, K., et al. (2021) · Genome Research · doi:10.1101/gr.268482.120 · Cited by 58
Self-citationSegrè, A. V., Wei, N., MAGIC Investigators, Altshuler, D., & Florez, J. C. (2014) · Diabetes · doi:10.2337/db14-0703 · Cited by 57
Self-citationGenetic and Epigenetic Fine Mapping of Complex Trait Associated Loci in the Human Liver
Çalışkan, M., Manduchi, E., Rao, H. S., Segert, J. A., Beltrame, M. H., Trizzino, M., Park, Y., Baker, S. W., Chesi, A., Johnson, M. E., et al. (2019) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2019.05.010 · Cited by 57
Self-citationSorting through the extensive and confusing roles of sortilin in metabolic disease
Mitok, K. A., Keller, M. P., & Attie, A. (2022) · Journal of Lipid Research · doi:10.1016/j.jlr.2022.100243 · Cited by 60
Sortilin as a Regulator of Lipoprotein Metabolism
Strong, A., & Rader, D. J. (2012) · Current Atherosclerosis Reports · doi:10.1007/s11883-012-0248-x · Cited by 58
Self-citationMin, J. L., Nicholson, G., Hallgrímsdóttir, I. B., Almstrup, K., Petri, A., Barrett, A., Travers, M. E., Rayner, N. W., Mägi, R., Pettersson, F. H., et al. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002505 · Cited by 57
Self-citationSystems Biology Approaches and Applications in Obesity, Diabetes, and Cardiovascular Diseases
Meng, Q., Mäkinen, V., Luk, H., & Yang, X. (2012) · Current Cardiovascular Risk Reports · doi:10.1007/s12170-012-0280-y · Cited by 58
He, J., Li, H., Edmondson, A. C., Rader, D. J., & Li, M. (2011) · Biostatistics · doi:10.1093/biostatistics/kxr025 · Cited by 58
Self-citationKaraderi, T., Drong, A., & Lindgren, C. M. (2015) · Current Diabetes Reports · doi:10.1007/s11892-015-0648-8 · Cited by 57
Hypertriglyceridemia and Cardiovascular Diseases: Revisited
Han, S. H., Nicholls, S. J., Sakuma, I., Zhao, D. H., & Koh, K. K. (2016) · Korean Circulation Journal · doi:10.4070/kcj.2016.46.2.135 · Cited by 60
Lai, C., Wojczynski, M. K., Parnell, L. D., Hidalgo, B., Irvin, M. R., Aslibekyan, S. W., Province, M. A., Absher, D., Arnett, D. K., & Ordovás, J. M. (2016) · Journal of Lipid Research · doi:10.1194/jlr.m069948 · Cited by 58
Contribution of Gene Regulatory Networks to Heritability of Coronary Artery Disease
Zeng, L., Talukdar, H. A., Koplev, S., Giannarelli, C., Ivert, T., Gan, L., Ruusalepp, A., Schadt, E. E., Kovacic, J. C., Lusis, A. J., et al. (2019) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2019.03.520 · Cited by 56
Self-citationRemnant cholesterol and ischemic heart disease
Varbo, A., & Nordestgaard, B. G. (2014) · Current Opinion in Lipidology · doi:10.1097/mol.0000000000000093 · Cited by 56
Assessing and managing risk when sharing aggregate genetic variant data
Craig, D. W., Goor, R. M., Wang, Z., Paschall, J. E., Ostell, J., Feolo, M., Sherry, S. T., & Manolio, T. A. (2011) · Nature Reviews Genetics · doi:10.1038/nrg3067 · Cited by 56
Ramayo‐Caldas, Y., Ballester, M., Fortes, M. R. S., Esteve‐Codina, A., Castelló, A., Noguera, J. L., Fernández, A. I., Miguel Pérez-enciso, A., Reverter, A., & Folch, J. M. (2014) · BMC Genomics · doi:10.1186/1471-2164-15-232 · Cited by 61
Allelic and phenotypic spectrum of plasma triglycerides
Johansen, C. T., & Hegele, R. A. (2011) · Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids · doi:10.1016/j.bbalip.2011.10.007 · Cited by 59
Self-citationFessler, M. B., Rose, K. M., Zhang, Y., Jaramillo, R., & Zeldin, D. C. (2013) · Journal of Lipid Research · doi:10.1194/jlr.p037614 · Cited by 57
Amrutkar, M., Kern, M., Nuñez‐Durán, E., Ståhlman, M., Cansby, E., Chursa, U., Stenfeldt, E., Borén, J., Blüher, M., & Mahlapuu, M. (2015) · Diabetologia · doi:10.1007/s00125-015-3801-7 · Cited by 57
A genome-wide association study of brain lesion distribution in multiple sclerosis
Gourraud, P., Sdika, M., Khankhanian, P., Henry, R. G., Beheshtian, A., Matthews, P. M., Hauser, S. L., Oksenberg, J. R., Pelletier, D., & Baranzini, S. E. (2013) · Brain · doi:10.1093/brain/aws363 · Cited by 58
Gene-Centric Analysis of Preeclampsia Identifies Maternal Association at PLEKHG1
Gray, K. J., Kovacheva, V., Mirzakhani, H., Bjonnes, A., Almoguera, B., DeWan, A. T., Triche, E. W., Saftlas, A. F., Hoh, J. J., Bodian, D. L., et al. (2018) · Hypertension · doi:10.1161/hypertensionaha.117.10688 · Cited by 61
Zeng, P., & Zhou, X. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00618 · Cited by 57
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
