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Biological, clinical and population relevance of 95 loci for blood lipids
Open accessAbstract
Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.
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“thus implicating IDOL as a potential therapeutic target (35)(36)(37).”
From Distinct Functional Domains Contribute to Degradation of the Low Density Lipoprotein Receptor (LDLR) by the E3 Ubiquitin Ligase Inducible Degrader of the LDLR (IDOL) (2011) · cites this paper as [36]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Recent genome-wide association studies (GWASs) in cohorts of mixed European descent have identified noncoding SNPs in the region of the MYLIP gene that are associated with LDL-C levels (6)(7)(8), thus demonstrating for the first time genetic association between the MYLIP gene and lipid levels in humans.”
From The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans (2011) · cites this paper as [6]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“In recent GWASs and a GWAS meta-analysis of populations of mixed European descent (6-8), there were 3 independent (r 2 < 0.3) genome-wide significant signals in the MYLIP region, none of which resides within the MYLIP gene.”
From The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans (2011) · cites this paper as [6]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“We also examined the direct association evidence for rs9370867 in the large GWAS meta-analysis of cohorts of mixed European descent (6): rs9370867 was associated with LDL-C levels for the same A risk allele (MAF 50%) as in Mexicans (P = 5.8 × 10 -06 ; Figure 2A).”
From The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans (2011) · cites this paper as [6]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Another GWAS signal was detected by the SNPs rs2327951 (6) and rs2142672 (8) that mapped and tagged variants 48-49 kb downstream from MYLIP.”
From The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans (2011) · cites this paper as [6]
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“common genetic variants near SCARB1 have been found to be correlated with plasma HDL-C levels (57, 58)”
From The hepatic WASH complex is required for efficient plasma LDL and HDL cholesterol clearance (2019) · cites this paper as [57]
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]
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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
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“SORT1 is a recently identified hepatic clearance receptor for LDL, which also regulates VLDL secretion and plasma triglycerides.16,20–22,38”
From (Pro)renin Receptor Inhibition Reprograms Hepatic Lipid Metabolism and Protects Mice From Diet-Induced Obesity and Hepatosteatosis (2018) · cites this paper as [38]
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“The association between triglycerides and cardiovascular (CV) risk is well established from epidemiological studies,1-5 genome-wide analyses,6-8 and Mendelian randomization studies.9,10”
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In the citing paper
“Recent genome-wide association studies identify IDOL as a novel modulator of LDL in humans, thus implicating IDOL as a potential therapeutic target (35)(36)(37).”
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In the citing paper
“Hence, this calculation demonstrated that the sample size of rs9370867 may not have been sufficiently powered to meet the genome-wide significance level in the meta-analysis GWAS (6).”
From The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans (2011) · cites this paper as [6]
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“The HFE rs1800562 variant that we use as an instrument for systemic iron status has previously been associated with low-density lipoprotein cholesterol in GWAS meta-analysis [39].”
From Associations of genetically determined iron status across the phenome: A mendelian randomization study (2019) · cites this paper as [39]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Thus, our study demonstrated, for the first time to our knowledge, that the amino acid change rs9370867 is most likely the functional mechanism underlying these previous GWAS variants, rs2294261 and rs2480 (6,7).”
From The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans (2011) · cites this paper as [6]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Importantly, our LD analyses also demonstrated that the most strongly associated variant in Mexicans, rs9370867, was in strong LD with the GWAS associated variants rs2480 (7) and rs2294261 (6) in the CEU founders with European ancestry and, to a lesser extent, in the Mexican controls (r 2 = 0.73 and r 2 = 0.49, respectively; Figure 3).”
From The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans (2011) · cites this paper as [6]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Taken together, these trans-ethnic LD and association data suggest that the nonsynonymous SNP rs9370867 is more likely the true underlying functional variant accounting for the genome-wide significant signals rs2480 and rs2294261 observed in the previous GWASs (6,7).”
From The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans (2011) · cites this paper as [6]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“It is worth noting that the expression levels of MYLIP were not significantly different with respect to the rs3757354 genotypes in the fat biopsies of Mexican subjects or in fat or liver biopsies from subjects of mixed European descent (6).”
From The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans (2011) · cites this paper as [6]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“We observed that the nonsynonymous rs9370867 variant was in strong LD with 2 upstream genome-wide significant GWAS variants, rs2294261 (6) and rs2480 (7), in Europeans.”
From The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans (2011) · cites this paper as [6]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“The GWAS variants of the other 2 associated LD groups, rs3757354 (6) and the SNPs rs2327951 (6) and rs2142672 (8), which are in full LD (r 2 ≥ 0.97) in both Europeans and Mexicans, were nominally associated with high TC in the Mexican dyslipidemic study sample for the same risks allele as in Europeans (Figure 2B and Supplemental Table 4).”
From The N342S MYLIP polymorphism is associated with high total cholesterol and increased LDL receptor degradation in humans (2011) · cites this paper as [6]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“GPR146, a susceptible gene associated with plasma total cholesterol (TC), LDL-C and high density lipoprotein cholesterol (HDL-C) levels”
From GPR146 Deficiency Protects against Hypercholesterolemia and Atherosclerosis (2019) · cites this paper as Teslovich et al., 2010
Experimental — accuracy not yet measuredIn the citing paper
“Profiling plasma lipids in large populations has uncovered sequence variations that substantially impact lipid phenotypes (Cohen et al., 2005; Teslovich et al., 2010).”
From Cellular Metabolism and Disease: What Do Metabolic Outliers Teach Us? (2012) · cites this paper as Teslovich et al., 2010
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Self-citationKathiresan, S., Melander, O., Guiducci, C., Surti, A., Burtt, N. P., Rieder, M. J., Cooper, G. M., Roos, C., Voight, B. F., Havulinna, A. S., et al. (2008) · Nature Genetics · doi:10.1038/ng.75 · Cited by 1,386
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Self-citationHuman metabolic individuality in biomedical and pharmaceutical research
CARDIoGRAM, Suhre, K., Shin, S.-Y., Petersen, A.-K., Mohney, R. P., Meredith, D., Wägele, B., Altmaier, E., Deloukas, P., Erdmann, J., et al. (2011) · Nature · doi:10.1038/nature10354 · Cited by 1,017
Self-citationSpeliotes, E. K., Yerges-Armstrong, L. M., Wu, J., Hernaez, R., Kim, L. J., Palmer, C. D., Gudnason, V., Eiriksdottir, G., Garcia, M. E., Launer, L. J., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1001324 · Cited by 984
Self-citationThe power of genetic diversity in genome-wide association studies of lipids
Graham, S. E., Clarke, S. L., Wu, K.-H. H., Kanoni, S., Zajac, G. J. M., Ramdas, S., Surakka, I., Ntalla, I., Vedantam, S., Winkler, T. W., et al. (2021) · Nature · doi:10.1038/s41586-021-04064-3 · Cited by 972
“The top-performing score from each GWAS was selected: PRS-CS for East Asian ancestry, European ancestry and European ancestry scores from a previous GLGC GWAS from 2010 4 ; and an optimized pruning and threshold-based score for all others.”
BackgroundMethodResultSelf-citationGenetics and epigenetics of NAFLD and NASH: Clinical impact
Eslam, M., Valenti, L., & Romeo, S. (2018) · Journal of Hepatology · doi:10.1016/j.jhep.2017.09.003 · Cited by 971
Cholesterol Efflux and Atheroprotection: Advancing the Concept of Reverse Cholesterol Transport
Rosenson, R. S., Brewer, H. B., Davidson, W. S., Fayad, Z. A., Fuster, V., Goldstein, J., Hellerstein, M., Jiang, X.-C., Phillips, M. C., Rader, D. J., et al. (2012) · Circulation · doi:10.1161/circulationaha.111.066589 · Cited by 953
Khera, A. V., Won, H.-H., Peloso, G. M., Lawson, K. S., Bartz, T. M., Deng, X., van Leeuwen, E. M., Natarajan, P., Emdin, C. A., Bick, A. G., et al. (2016) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2016.03.520 · Cited by 942
Self-citationBile acid signaling in metabolic disease and drug therapy
Li, T., & Chiang, J. Y. L. (2014) · Pharmacological Reviews · doi:10.1124/pr.113.008201 · Cited by 935
Ference, B. A., Yoo, W., Alesh, I., Mahajan, N., Mirowska, K. K., Mewada, A., Kahn, J., Afonso, L., Williams, K. A., & Flack, J. M. (2012) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2012.09.017 · Cited by 898
Genome partitioning of genetic variation for complex traits using common SNPs
Yang, J., Manolio, T. A., Pasquale, L. R., Boerwinkle, E., Caporaso, N., Cunningham, J. M., de Andrade, M., Feenstra, B., Feingold, E., Hayes, M. G., et al. (2011) · Nature Genetics · doi:10.1038/ng.823 · Cited by 890
Self-citationBennett, E. P., Mandel, U., Clausen, H., Gerken, T. A., Fritz, T. A., & Tabak, L. A. (2012) · Glycobiology · doi:10.1093/glycob/cwr182 · Cited by 876
Zheng, J., Erzurumluoglu, A. M., Elsworth, B. L., Kemp, J. P., Howe, L., Haycock, P. C., Hemani, G., Tansey, K., Laurin, C., Early Genetics and Lifecourse Epidemiology (EAGLE) Eczema Consortium, et al. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btw613 · Cited by 869
Common variants associated with plasma triglycerides and risk for coronary artery disease
Do, R., Willer, C. J., Schmidt, E. M., Sengupta, S., Gao, C., Peloso, G. M., Gustafsson, S., Kanoni, S., Ganna, A., Chen, J., et al. (2013) · Nature Genetics · doi:10.1038/ng.2795 · Cited by 862
Self-citationCellular Metabolism and Disease: What Do Metabolic Outliers Teach Us?
DeBerardinis, R. J., & Thompson, C. B. (2012) · Cell · doi:10.1016/j.cell.2012.02.032 · Cited by 858
A single-cell atlas of human and mouse white adipose tissue
Emont, M. P., Jacobs, C., Essene, A. L., Pant, D., Tenen, D., Colleluori, G., Di Vincenzo, A., Jørgensen, A. M., Dashti, H., Stefek, A., et al. (2022) · Nature · doi:10.1038/s41586-022-04518-2 · Cited by 840
Dysfunctional HDL and atherosclerotic cardiovascular disease
Rosenson, R. S., Brewer, H. B., Ansell, B. J., Barter, P., Chapman, M. J., Heinecke, J. W., Kontush, A., Tall, A. R., & Webb, N. R. (2016) · Nature Reviews Cardiology · doi:10.1038/nrcardio.2015.124 · Cited by 822
Self-citationScott, R. A., Lagou, V., Welch, R., Wheeler, E., Montasser, M. E., Luan, J., Mägi, R., Strawbridge, R. J., Rehnberg, E., Gustafsson, S., et al. (2012) · Nature Genetics · doi:10.1038/ng.2385 · Cited by 831
Self-citationManning, A. K., Hivert, M., Scott, R. A., Grimsby, J., Bouatia‐Naji, N., Chen, H., Rybin, D. V., Liu, C.-T., Bielak, L. F., Prokopenko, I., et al. (2012) · Nature Genetics · doi:10.1038/ng.2274 · Cited by 821
Self-citationHirschey, M. D., Shimazu, T., Jing, E., Grueter, C. A., Collins, A. M., Aouizerat, B., Stančáková, A., Goetzman, E., Lam, M. M., Schwer, B., et al. (2011) · Molecular Cell · doi:10.1016/j.molcel.2011.07.019 · Cited by 787
“, 2009), or cholesterol and lipid metabolism (Musunuru et al., 2010; Teslovich et al., 2010), we tested the possibility that SNPs in SIRT3 were associated with metabolic dysfunction in a Caucasian cohort diagnosed with fatty liver disease (The NASH CRN).”
Biological interpretation of genome-wide association studies using predicted gene functions
Pers, T. H., Karjalainen, J. M., Chan, Y., Westra, H.-J., Wood, A. R., Yang, J., Lui, J. C., Vedantam, S., Gustafsson, S., Esko, T., et al. (2015) · Nature Communications · doi:10.1038/ncomms6890 · Cited by 787
Self-citationBeyond GWASs: Illuminating the Dark Road from Association to Function
Edwards, S. L., Beesley, J., French, J. D., & Dunning, A. M. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2013.10.012 · Cited by 784
National Lipid Association Recommendations for Patient-Centered Management of Dyslipidemia: Part 2
Jacobson, T. A., Maki, K. C., Orringer, C. E., Jones, P. H., Kris-Etherton, P., Sikand, G., La Forge, R., Daniels, S. R., Wilson, D. P., Morris, P. B., et al. (2015) · Journal of Clinical Lipidology · doi:10.1016/j.jacl.2015.09.002 · Cited by 784
Exome Sequencing, ANGPTL3 Mutations, and Familial Combined Hypolipidemia
Musunuru, K., Pirruccello, J. P., Do, R., Peloso, G. M., Guiducci, C., Sougnez, C., Garimella, K. V., Fisher, S., Abreu, J., Barry, A. J., et al. (2010) · New England Journal of Medicine · doi:10.1056/nejmoa1002926 · Cited by 754
Self-citationMendelian randomization of blood lipids for coronary heart disease
Holmes, M. V., Asselbergs, F. W., Palmer, T. M., Drenos, F., Lanktree, M. B., Nelson, C. P., Dale, C. E., Padmanabhan, S., Finan, C., Swerdlow, D. I., et al. (2015) · European Heart Journal · doi:10.1093/eurheartj/eht571 · Cited by 748
Self-citationKettunen, J., Demirkan, A., Würtz, P., Draisma, H. H. M., Haller, T., Rawal, R., Vaarhorst, A., Kangas, A. J., Lyytikäinen, L.-P., Pirinen, M., et al. (2016) · Nature Communications · doi:10.1038/ncomms11122 · Cited by 738
Self-citationThe Genetics of Major Depression
Flint, J., & Kendler, K. S. (2014) · Neuron · doi:10.1016/j.neuron.2014.01.027 · Cited by 724
Burgess, S., Ference, B. A., Staley, J. R., Freitag, D. F., Mason, A. M., Nielsen, S. F., Willeit, P., Young, R., Surendran, P., Karthikeyan, S., et al. (2018) · JAMA Cardiology · doi:10.1001/jamacardio.2018.1470 · Cited by 689
Swerdlow, D. I., Preiss, D., Kuchenbaecker, K. B., Holmes, M. V., Engmann, J. E. L., Shah, T., Sofat, R., Stender, S., Johnson, P. C. D., Scott, R. A., et al. (2015) · The Lancet · doi:10.1016/s0140-6736(14)61183-1 · Cited by 680
Self-citationWinkler, T. W., Justice, A. E., Graff, M., Barata, L., Feitosa, M. F., Chu, S. H., Czajkowski, J., Esko, T., Fall, T., Kilpeläinen, T. O., et al. (2015) · PLoS Genetics · doi:10.1371/journal.pgen.1005378 · Cited by 681
Self-citationATUALIZAÇÃO DA DIRETRIZ BRASILEIRA DE DISLIPIDEMIAS E PREVENÇÃO DA ATEROSCLEROSE - 2017
Faludi, A., Izar, M. C. D. O., Saraiva, J., Chacra, A., Bianco, H. T., Neto, A. A., Bertolami, A., Pereira, A., Lottenberg, A., Sposito, A. C., et al. (2017) · Arquivos Brasileiros de Cardiologia · doi:10.5935/abc.20170121 · Cited by 690
Genetics of coronary artery disease: discovery, biology and clinical translation
Khera, A. V., & Kathiresan, S. (2017) · Nature Reviews Genetics · doi:10.1038/nrg.2016.160 · Cited by 659
Self-citationResearch Review: Polygenic methods and their application to psychiatric traits
Wray, N. R., Lee, S., Mehta, D., Vinkhuyzen, A. A. E., Dudbridge, F., & Middeldorp, C. M. (2014) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12295 · Cited by 683
Exome sequencing identifies rare LDLR and APOA5 alleles conferring risk for myocardial infarction
Do, R., Stitziel, N. O., Won, H.-H., Jørgensen, A. B., Duga, S., Angelica Merlini, P., Kiezun, A., Farrall, M., Goel, A., Zuk, O., et al. (2015) · Nature · doi:10.1038/nature13917 · Cited by 650
Self-citationSearching for missing heritability: Designing rare variant association studies
Zuk, O., Schaffner, S. F., Samocha, K., Do, R., Hechter, E., Kathiresan, S., Daly, M. J., Neale, B. M., Sunyaev, S. R., & Lander, E. S. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1322563111 · Cited by 635
Self-citationHegele, R. A., Ginsberg, H. N., Chapman, M. J., Nordestgaard, B. G., Kuivenhoven, J. A., Averna, M., Borén, J., Bruckert, E., Catapano, A. L., Descamps, O. S., et al. (2014) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(13)70191-8 · Cited by 635
Self-citationLiu, Y.-L., Reeves, H. L., Burt, A. D., Tiniakos, D., McPherson, S., Leathart, J. B. S., Allison, M. E. D., Alexander, G. J., Piguet, A.-C., Anty, R., et al. (2014) · Nature Communications · doi:10.1038/ncomms5309 · Cited by 623
Systems genetics approaches to understand complex traits
Civelek, M., & Lusis, A. J. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3575 · Cited by 621
Clinical Genetic Testing for Familial Hypercholesterolemia
Sturm, A. C., Knowles, J. W., Gidding, S. S., Ahmad, Z., Ahmed, C. D., Ballantyne, C. M., Baum, S. J., Bourbon, M., Carrié, A., Cuchel, M., et al. (2018) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2018.05.044 · Cited by 643
Self-citationRealizing the promise of cancer predisposition genes
Rahman, N. (2014) · Nature · doi:10.1038/nature12981 · Cited by 632
Cano-Gamez, E., & Trynka, G. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.00424 · Cited by 613
Genetics of blood lipids among ∼300,000 multi-ethnic participants of the Million Veteran Program
Global Lipids Genetics Consortium, Klarin, D., Myocardial Infarction Genetics (MIGen) Consortium, The Geisinger-Regeneron DiscovEHR Collaboration, Program, T. V. M. V., Damrauer, S. M., Cho, K., Sun, Y. V., Teslovich, T. M., Honerlaw, J., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0222-9 · Cited by 625
Self-citationTalmud, P. J., Shah, S. H., Whittall, R., Futema, M., Howard, P., Cooper, J. A., Harrison, S. C., Li, K., Drenos, F., Karpe, F., et al. (2013) · The Lancet · doi:10.1016/s0140-6736(12)62127-8 · Cited by 606
Self-citationLiver X receptors in lipid metabolism: opportunities for drug discovery
Hong, C., & Tontonoz, P. (2014) · Nature Reviews Drug Discovery · doi:10.1038/nrd4280 · Cited by 587
Chromatin marks identify critical cell types for fine mapping complex trait variants
Trynka, G., Sandor, C., Han, B., Xu, H., Stranger, B. E., Liu, X. S., & Raychaudhuri, S. (2013) · Nature Genetics · doi:10.1038/ng.2504 · Cited by 580
Relton, C. L., & Davey Smith, G. (2012) · International Journal of Epidemiology · doi:10.1093/ije/dyr233 · Cited by 567
Progress and promise of genome-wide association studies for human complex trait genetics
Stranger, B. E., Stahl, E. A., & Raj, T. (2011) · Genetics · doi:10.1534/genetics.110.120907 · Cited by 567
GWAS on family history of Alzheimer’s disease
Marioni, R. E., Harris, S. E., Zhang, Q., McRae, A. F., Hagenaars, S. P., Hill, W. D., Davies, G., Ritchie, C. W., Gale, C. R., Starr, J. M., et al. (2018) · Translational Psychiatry · doi:10.1038/s41398-018-0150-6 · Cited by 564
Genomic inflation factors under polygenic inheritance
Yang, J., Weedon, M. N., Purcell, S., Lettre, G., Estrada, K., Willer, C. J., Smith, A. V., Ingelsson, E., O’Connell, J. R., Mangino, M., et al. (2011) · European Journal of Human Genetics · doi:10.1038/ejhg.2011.39 · Cited by 571
Self-citationGenome-wide association study identifies multiple loci influencing human serum metabolite levels
Kettunen, J., Tukiainen, T., Sarin, A.-P., Ortega-Alonso, A., Tikkanen, E., Lyytikäinen, L.-P., Kangas, A. J., Soininen, P., Würtz, P., Silander, K., et al. (2012) · Nature Genetics · doi:10.1038/ng.1073 · Cited by 553
Self-citationEffect of host genetics on the gut microbiome in 7,738 participants of the Dutch Microbiome Project
Lopera-Maya, E. A., Kurilshikov, A., van der Graaf, A., Hu, S., Andreu-Sánchez, S., Chen, L., Vila, A. V., Gacesa, R., Sinha, T., Collij, V., et al. (2022) · Nature Genetics · doi:10.1038/s41588-021-00992-y · Cited by 553
Self-citationShim, H., Chasman, D. I., Smith, J. D., Mora, S., Ridker, P. M., Nickerson, D. A., Krauss, R. M., & Stephens, M. (2015) · PLoS ONE · doi:10.1371/journal.pone.0120758 · Cited by 563
Self-citationUnraveling the polygenic architecture of complex traits using blood eQTL metaanalysis
Võsa, U., Claringbould, A., Westra, H.-J., Bonder, M. J., Deelen, P., Zeng, B., Kirsten, H., Saha, A., Kreuzhuber, R., Kasela, S., et al. (2018) · doi:10.1101/447367 · Cited by 2,607
Self-citationGenome-wide association study identifies loci influencing concentrations of liver enzymes in plasma
Chambers, J. C., Study, D. G. R. A. M.-A. (., Zhang, W., Sehmi, J., Li, X., Wass, M. N., van der Harst, P., Hólm, H., Sanna, S., Kavousi, M., et al. (2011) · Nature Genetics · doi:10.1038/ng.970 · Cited by 556
Self-citationZanoni, P., Khetarpal, S. A., Larach, D. B., Hancock-Cerutti, W. F., Millar, J. S., Cuchel, M., DerOhannessian, S., Kontush, A., Surendran, P., Saleheen, D., et al. (2016) · Science · doi:10.1126/science.aad3517 · Cited by 545
Self-citationFoley, C. N., Staley, J. R., Breen, P. G., Sun, B. B., Kirk, P., Burgess, S., & Howson, J. M. M. (2021) · Nature Communications · doi:10.1038/s41467-020-20885-8 · Cited by 552
Glycosylation: mechanisms, biological functions and clinical implications
He, M., Zhou, X., & Wang, X. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-01886-1 · Cited by 585
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
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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.
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