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Exome sequencing identifies rare LDLR and APOA5 alleles conferring risk for myocardial infarction
Open accessAbstract
Myocardial infarction (MI), a leading cause of death around the world, displays a complex pattern of inheritance. When MI occurs early in life, genetic inheritance is a major component to risk. Previously, rare mutations in low-density lipoprotein (LDL) genes have been shown to contribute to MI risk in individual families, whereas common variants at more than 45 loci have been associated with MI risk in the population. Here we evaluate how rare mutations contribute to early-onset MI risk in the population. We sequenced the protein-coding regions of 9,793 genomes from patients with MI at an early age (≤50 years in males and ≤60 years in females) along with MI-free controls. We identified two genes in which rare coding-sequence mutations were more frequent in MI cases versus controls at exome-wide significance. At low-density lipoprotein receptor (LDLR), carriers of rare non-synonymous mutations were at 4.2-fold increased risk for MI; carriers of null alleles at LDLR were at even higher risk (13-fold difference). Approximately 2% of early MI cases harbour a rare, damaging mutation in LDLR; this estimate is similar to one made more than 40 years ago using an analysis of total cholesterol. Among controls, about 1 in 217 carried an LDLR coding-sequence mutation and had plasma LDL cholesterol > 190 mg dl(-1). At apolipoprotein A-V (APOA5), carriers of rare non-synonymous mutations were at 2.2-fold increased risk for MI. When compared with non-carriers, LDLR mutation carriers had higher plasma LDL cholesterol, whereas APOA5 mutation carriers had higher plasma triglycerides. Recent evidence has connected MI risk with coding-sequence mutations at two genes functionally related to APOA5, namely lipoprotein lipase and apolipoprotein C-III (refs 18, 19). Combined, these observations suggest that, as well as LDL cholesterol, disordered metabolism of triglyceride-rich lipoproteins contributes to MI risk.
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“Mendelian randomization studies focused on variants in the genes encoding apoAV, apoCIII, lipoprotein lipase (LpL) and the angiopoietin-like proteins 3, 4, and 8 (ANGPTL3, ANGPTL4, and ANGPTL8) have been highly informative.29–35”
From Triglyceride-rich lipoproteins and their remnants: metabolic insights, role in atherosclerotic cardiovascular disease, and emerging therapeutic strategies—a consensus statement from the European Atherosclerosis Society (2021) · cites this paper as [29]
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“In contrast, apo A-V, which promotes LPL activity through partially defined mechanisms, is a strong genetically validated target for ASCVD.95,96”
From Clinical review on triglycerides (2020) · cites this paper as [96]
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Cites
The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041
Self-citationFast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089
ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data
Wang, K., Li, M., & Hakonarson, H. H. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq603 · Cited by 14,724
Self-citationCingolani, P., Platts, A., Wang, L. L., Coon, M., Nguyen, T., Wang, L., Land, S. J., Lu, X., & Ruden, D. M. (2012) · Fly · doi:10.4161/fly.19695 · Cited by 11,816
A framework for variation discovery and genotyping using next-generation DNA sequencing data
DePristo, M. A., Banks, E., Poplin, R. E., Garimella, K. V., Maguire, J., Hartl, C., Philippakis, A., del Angel, G., Rivas, M. A., Hanna, M., et al. (2011) · Nature Genetics · doi:10.1038/ng.806 · Cited by 11,457
Self-citationPrincipal components analysis corrects for stratification in genome-wide association studies
Price, A. L., Patterson, N. J., Plenge, R. M., Weinblatt, M. E., Shadick, N. A., & Reich, D. (2006) · Nature Genetics · doi:10.1038/ng1847 · Cited by 10,248
A map of human genome variation from population-scale sequencing.
The 1000 Genomes Project Consortium (2010) · Nature · doi:10.1038/nature09534 · Cited by 7,877
Self-citationA Receptor-Mediated Pathway for Cholesterol Homeostasis
Brown, M. S., & Goldstein, J. L. (1986) · Science · doi:10.1126/science.3513311 · Cited by 5,703
METAL: fast and efficient meta-analysis of genomewide association scans
Willer, C. J., Li, Y., & Abecasis, G. R. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq340 · Cited by 5,205
Self-citation
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Items 401–500 of 643
Wettinger, S. B., Karađuzović-Hadžiabdić, K., Attard, R., Farrugia, R. C., Wolford, B. N., Chierici, M., Jurman, G., Alexiou, P., Peñalvo, J. L., Costa, R. S., et al. (2025) · Briefings in Bioinformatics · doi:10.1093/bib/bbaf526 · Cited by 9
Shared Genetic Aetiology of Coronary Artery Disease and Atherosclerotic Stroke—2015
Kessler, T., Erdmann, J., Dichgans, M., & Schunkert, H. (2015) · Current Atherosclerosis Reports · doi:10.1007/s11883-015-0498-5 · Cited by 9
Self-citationSystems Medicine as an Emerging Tool for Cardiovascular Genetics
Haase, T., Börnigen, D., Müller, C., & Zeller, T. (2016) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2016.00027 · Cited by 9
Fang, H., Hu, D., Li, Q., & Tu, S. (2020) · Molecular Medicine Reports · doi:10.3892/mmr.2020.11247 · Cited by 9
Jia, Q., Xu, L., Shen, J., Wei, Y., Xu, H., Shi, J., Jia, Z., Zhao, X., Liu, C., Qin, Z., et al. (2020) · Medical Science Monitor · doi:10.12659/msm.925401 · Cited by 9
Faria, M. S. D. S. N., Pimentel, V. E., Helaehil, J. V., Bertolo, M. C., Santos, N. T. H., Silva-Neto, P. V. D., Thomazini, B. F., de Oliveira, C. A., & do Amaral, M. E. C. (2022) · Molecular Biology Reports · doi:10.1007/s11033-022-07370-9 · Cited by 9
Ibi, D., Boot, M., Dollé, M. E. T., Jukema, J. W., Rosendaal, F. R., Christodoulides, C., Neville, M. J., Koivula, R., Rensen, P. C. N., Karpe, F., et al. (2022) · Journal of Lipid Research · doi:10.1016/j.jlr.2022.100193 · Cited by 9
Thériault, S., Don-Wauchope, A., Chong, M., Lali, R., Morrison, K. M., & Paré, G. (2016) · Journal of clinical lipidology · doi:10.1016/j.jacl.2016.07.009 · Cited by 9
Polyphenolic Compounds and Gut Microbiome in Cardiovascular Diseases
McGrail, L., & Garelnabi, M. (2019) · Current Pharmaceutical Biotechnology · doi:10.2174/1389201020666191111150239 · Cited by 9
Zhou, Y., Bai, K., Wang, Y., Meng, Z., Zhou, S., Jiang, S., Wang, H., Wang, J., Yang, M., Wang, Q., et al. (2022) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2021.811156 · Cited by 9
Self-citationSönmez, A., Demirci, İ., Haymana, C., Taşçı, İ., Ayvalı, M. O., Ata, N., Ezgü, F. S., Bayram, F., Barçın, C., Çağlayan, M., et al. (2023) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2023.04.011 · Cited by 9
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Prudente, S., Bailetti, D., Mendonça, C., Mannino, G. C., Fontana, A., Andreozzi, F., Hastings, T., Mercuri, L., Alberico, F., Basile, G., et al. (2015) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2015.07.030 · Cited by 9
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Ferrières, J., Bruckert, É., Béliard, S., Rabès, J., Farnier, M., Krempf, M., Cariou, B., & Danchin, N. (2017) · Annales de Cardiologie et d Angéiologie · doi:10.1016/j.ancard.2017.04.015 · Cited by 9
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Deaton, A. M., Sulem, P., Nioi, P., Benónísdóttir, S., Ward, L. D., Davidsson, O. B., Lao, S., Helgadóttir, A., Fan, F., Jensson, B. Ö., et al. (2018) · Communications Biology · doi:10.1038/s42003-018-0015-9 · Cited by 11
Khounphinith, E., Yin, R., Cao, X., Huang, F., Wu, J., & Li, H. (2019) · International Journal of Medical Sciences · doi:10.7150/ijms.31729 · Cited by 9
Liu, S., Wang, X., Yu, S., Yan, M., Peng, Y., Zhang, G., & Xu, Z. (2020) · Frontiers in Physiology · doi:10.3389/fphys.2020.539288 · Cited by 9
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Humphries, S. E. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-809633-8.06415-3 · Cited by 9
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Vasiluev, P. A., Ivanova, O. N., Semenova, N. A., Строкова, Т. В., Taran, N. N., Чубыкина, У. В., Владиславович, Е. М., Zakharova, E. Y., Dadli, E. L., & Kutsev, S. I. (2022) · Genes · doi:10.3390/genes13061062 · Cited by 9
Jha, C. K., Mir, R., Banu, S., Elfaki, I., & Chahal, S. M. S. (2019) · Endocrine Metabolic & Immune Disorders - Drug Targets · doi:10.2174/1871530319666191015164505 · Cited by 9
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Aragam, K. G., & Kathiresan, S. (2017) · Elsevier eBooks · doi:10.1016/b978-0-323-42880-4.00003-0 · Cited by 9
Self-citationStatins in Familial Hypercholesterolemia
Knowles, J. W. (2016) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2016.05.024 · Cited by 9
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Facchi, D., Rimoldi, V., Straniero, L., Paraboschi, E. M., Soldà, G., Zecchinelli, A., Cilia, R., Duga, S., Pezzoli, G., & Asselta, R. (2020) · Brain · doi:10.1093/brain/awaa213 · Cited by 9
Self-citationElahimanesh, M., Shokri, N., Mahdinia, E., Mohammadi, P., Parvaz, N., & Najafi, M. (2024) · Scientific Reports · doi:10.1038/s41598-024-54086-w · Cited by 8
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Wulff, A. B., & Nordestgaard, B. G. (2025) · Current Opinion in Lipidology · doi:10.1097/mol.0000000000000991 · Cited by 8
Genetics for the Identification of Lipid Targets Beyond PCSK9
Wang, L. R., & Hegele, R. A. (2016) · Canadian Journal of Cardiology · doi:10.1016/j.cjca.2016.11.003 · Cited by 8
Self-citationRecent Advances in the Genetics of Atherothrombotic Disease and Its Determinants
Dron, J. S., Ho, R., & Hegele, R. A. (2017) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.117.309934 · Cited by 8
Self-citationDeng, H., Li, J., Shah, A. A., Ge, L., & Ouyang, W. (2023) · Genomics · doi:10.1016/j.ygeno.2023.110567 · Cited by 8
Petrazzini, B. O., Balick, D. J., Forrest, I. S., Cho, J. H., Rocheleau, G., Jordan, D. M., & Do, R. (2024) · Cell Reports Methods · doi:10.1016/j.crmeth.2024.100914 · Cited by 10
Self-citationCrandell, J. R., Tartaglia, C., & Tartaglia, J. (2016) · Postgraduate Medicine · doi:10.1080/00325481.2016.1241129 · Cited by 8
Kang, G., Bi, W., Zhang, H., Pounds, S. B., Cheng, C., Shete, S. S., Zou, F., Zhao, Y., Zhang, J., & Yue, W. (2017) · Genetics · doi:10.1534/genetics.116.192377 · Cited by 8
Xu, J., Song, Y., Jiang, P. X., Jiang, L., Zhao, X.-Y., Gao, Z., Li, J., Qiao, S., Gao, R.-L., Yang, Y., et al. (2020) · World Journal of Emergency Medicine · doi:10.5847/wjem.j.1920-8642.2021.01.006 · Cited by 8
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Chait, A., & Feingold, K. R. (2022) · Best Practice & Research Clinical Endocrinology & Metabolism · doi:10.1016/j.beem.2022.101659 · Cited by 8
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Wierzbicki, A. S., & Reynolds, T. (2019) · Current Opinion in Cardiology · doi:10.1097/hco.0000000000000623 · Cited by 8
Experimental Biology for the Identification of Causal Pathways in Atherosclerosis
Guo, Y., Garcia-Barrio, M. T., Wang, L., & Chen, Y. (2016) · Cardiovascular Drugs and Therapy · doi:10.1007/s10557-016-6644-7 · Cited by 8
Reiman, A., Pandey, S., Lloyd, K. L., Dyer, N. P., Khan, M., Crockard, M. A., Latten, M. J., Watson, T. L., Cree, I. A., & Grammatopoulos, D. K. (2016) · Annals of Clinical Biochemistry International Journal of Laboratory Medicine · doi:10.1177/0004563216629170 · Cited by 8
Colesterol-no HDL como objetivo terapéutico
Brea, Á., Hernández‐Mijares, A., Millán, J., Ascaso, J. F., Blasco, M., Rodríguez, Á. D., Mantilla, T., Pedro‐Botet, J., & Pintó, X. (2019) · Clínica e Investigación en Arteriosclerosis · doi:10.1016/j.arteri.2019.07.002 · Cited by 8
Reducing Cardiovascular Risk Using Genomic Information in the Era of Precision Medicine
Natarajan, P., & O’Donnell, C. J. (2016) · Circulation · doi:10.1161/circulationaha.116.021765 · Cited by 8
Self-citation“Pheno”menal value for human health
Rader, D. J., & Damrauer, S. M. (2016) · Science · doi:10.1126/science.aal4573 · Cited by 8
Self-citationCan we afford not to screen for FH?
Stoekenbroek, R. M., Kastelein, J. J. P., & Hovingh, G. K. (2017) · European Heart Journal · doi:10.1093/eurheartj/ehx197 · Cited by 8
Self-citationPutting Into Perspective the Hazards of Untreated Familial Hypercholesterolemia
Hopkins, P. N. (2017) · Journal of the American Heart Association · doi:10.1161/jaha.117.006553 · Cited by 8
Multiomics: the intersection of personalized nutrition in cardiometabolic diseases
Çelik, E., Koçyiğit, E., Bingöl, F. G., Karaçolak, C., Cemali, Ö., Simonelli, M., Ağagündüz, D., & Capasso, R. (2026) · Journal of Translational Medicine · doi:10.1186/s12967-026-07836-5 · Cited by 8
Pan-Lizcano, R., Mariñas‐Pardo, L., Núñez, L., Rebollal-Leal, F., Vázquez, D. L., Pereira, A., Molina-Nieto, A., Calviño, R., Vázquez‐Rodríguez, J. M., & Hermida‐Prieto, M. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms232416127 · Cited by 8
Wang, C., Zhang, J., Veldsman, W. P., Zhou, X., & Zhang, L. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac552 · Cited by 7
Differential Lipid Response to Statins Is Associated With Variants in the BUD13–APOA5 Gene Region
OʼBrien, S. E., Schrodi, S. J., Ye, Z., Brilliant, M. H., Virani, S. S., & Brautbar, A. (2015) · Journal of Cardiovascular Pharmacology · doi:10.1097/fjc.0000000000000261 · Cited by 7
Tada, H., Kobayashi, J., Kawashiri, M., Miyashita, K., Nohara, A., Inazu, A., Nakajima, K., Mabuchi, H., & Yamagishi, M. (2016) · Lipids in Health and Disease · doi:10.1186/s12944-016-0238-z · Cited by 7
Jeff, J. M., Peloso, G. M., & Do, R. (2016) · Current Opinion in Lipidology · doi:10.1097/mol.0000000000000277 · Cited by 7
Self-citationYoung, E. P., & Stitziel, N. O. (2018) · Annual Review of Medicine · doi:10.1146/annurev-med-041717-085853 · Cited by 7
Self-citationPan‐risk factor for a comprehensive cardiovascular health management
Zheng, R., Xu, Y., Li, M., Lu, J., Xu, M., Wang, T., Zhao, Z., Wang, S., Lin, H., Zhang, X., et al. (2022) · Journal of Diabetes · doi:10.1111/1753-0407.13258 · Cited by 7
Self-citationApplication of Genome-Wide Association Studies in Coronary Artery Disease
Zheng, H., Zeng, Z., Wen, H., Wang, P., Huang, C., Huang, P., Chen, Q., Gong, D., & Qiu, X. (2019) · Current Pharmaceutical Design · doi:10.2174/1381612825666191105125148 · Cited by 7
Pathophysiology of Atherosclerosis
Fernando, S., Bursill, C. A., Nicholls, S. J., & Psaltis, P. J. (2020) · Springer eBooks · doi:10.1007/978-3-030-43683-4_2 · Cited by 7
Functional and clinical implications of genetic structure in 1686 Italian exomes
Birolo, G., Aneli, S., Gaetano, C. D., Cugliari, G., RUSSO, A. E., Allione, A., Casalone, E., Giorgio, E., Paraboschi, E. M., Ardissino, D., et al. (2020) · Human Mutation · doi:10.1002/humu.24156 · Cited by 7
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Watts, G. F., Pang, J., & Santos, R. D. (2015) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2015.04.016 · Cited by 7
Using human genetics to discover new therapeutic targets for plasma lipids
Cohen, J. C. (2016) · Journal of Internal Medicine · doi:10.1111/joim.12521 · Cited by 7
Chen, G., Liu, L., Li, H., Lun, Z., Mai, Z., Lai, W., Chen, E., Zhou, C., Yu, S., Yang, J., et al. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.616492 · Cited by 7
Self-citationFamilial hypercholesterolaemia: a common disease
Ray, K. K., & Hovingh, G. K. (2016) · European Heart Journal · doi:10.1093/eurheartj/ehw130 · Cited by 7
Polygenic Risk Scores in Familial Hypercholesterolemia
Rader, D. J., & Sheth, S. (2019) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2019.06.006 · Cited by 7
Self-citationZhang, M. J., Price, A. L., Durvasula, A., Chiang, C., Koch, E., Schoech, A. P., Strober, B., Shi, H., Barton, A. R., Kim, S. S., et al. (2026) · Nature Genetics · doi:10.1038/s41588-026-02712-w · Cited by 6
Self-citationZhang, X., Seshadri, V. D., & Jiang, Q. (2023) · Pharmacognosy Magazine · doi:10.1177/09731296221139010 · Cited by 6
Mehvari, S., Fathi, N. K., Saki, S., Asadnezhad, M., Arzhangi, S., Ghodratpour, F., Mohseni, M., Ashrafi, F. Z., Sadeghian, S., Boroumand, M., et al. (2024) · Clinical Genetics · doi:10.1111/cge.14491 · Cited by 6
Familial hypercholesterolemia and young patients’ thoughts on own condition and treatment
Urke, E. B., Søbye, S. I., Ellingvåg, A., Langslet, G., Retterstøl, K., & Wandel, M. (2018) · Patient Education and Counseling · doi:10.1016/j.pec.2018.12.025 · Cited by 6
He, Y., Gu, X., Hu, Y., Jia, H., Zhao, Z., Jiang, H., Zheng, H., & Fu, Z. (2022) · Journal of Cardiology · doi:10.1016/j.jjcc.2021.10.020 · Cited by 6
Landmark position paper on paediatric familial hypercholesterolaemia from the EAS Consensus Panel
Stock, J. K. (2015) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2015.06.021 · Cited by 6
Lee, J.-Y., Moon, S., Kim, Y. K., Lee, S., Lee, B.-S., Park, M., Park, J. E., Jang, Y., & Han, B. (2017) · Journal of Genetics · doi:10.1007/s12041-017-0854-z · Cited by 6
Cheng, S., Lyu, J., Shi, X., Wang, K., Wang, Z., Deng, M., Sun, B., & Wang, C. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab572 · Cited by 6
Maron, B. A., & Leopold, J. A. (2016) · Global Cardiology Science and Practice · doi:10.21542/gcsp.2016.27 · Cited by 6
Should We Use Genetic Scores in the Determination of Treatment Strategies to Control Dyslipidemias?
Lechner, K., Kessler, T., & Schunkert, H. (2020) · Current Cardiology Reports · doi:10.1007/s11886-020-01408-9 · Cited by 6
Self-citationSilbernagel, G., Higbie, H., Meininger, T., Lemen, D., Li, H., Chen, Y., Wen, Y., Zhen, Y., Qian, Y., Korovianskaia, P., et al. (2025) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2025.120485 · Cited by 5
Self-citationHiguchi, T., Oka, S., Shimada, K., Tsunoda, S., Ito, S., Okamoto, A., Fujimori, M., Nakamura, T., Katayama, M., Suzuki, M., et al. (2024) · Rheumatology · doi:10.1093/rheumatology/keae422 · Cited by 5
Bayesian Variable Selection for Post-Analytic Interrogation of Susceptibility Loci
Chen, S., Núñez, S., Reilly, M. P., & Foulkes, A. S. (2016) · Biometrics · doi:10.1111/biom.12620 · Cited by 5
Self-citationVolta, A., Hovingh, G. K., & Grefhorst, A. (2018) · Current Opinion in Lipidology · doi:10.1097/mol.0000000000000489 · Cited by 5
Treatment of newly diagnosed primary central nervous system lymphoma: current and emerging therapies
Sethi, T. K., & Reddy, N. M. (2018) · Leukemia & lymphoma/Leukemia and lymphoma · doi:10.1080/10428194.2018.1466296 · Cited by 5
Genomic Strategies Toward Identification of Novel Therapeutic Targets
Kessler, T., & Schunkert, H. (2020) · Handbook of experimental pharmacology · doi:10.1007/164_2020_360 · Cited by 5
Self-citationYao, K., Dai, Y., Shen, J., Wang, Y., Yang, H., Wu, R., Liao, Q., Wu, H., Fang, X., Shali, S., et al. (2022) · National Science Review · doi:10.1093/nsr/nwac102 · Cited by 5
Self-citationRegulatory Non-Coding RNAs in Familial Hypercholesterolemia, Theranostic Applications
Alikhani, H. K., Pourhamzeh, M., Seydi, H., Shokoohian, B., Hossein‐Khannazer, N., Jamshidi‐Adegani, F., Al‐Hashmi, S., Hassan, M., & Vosough, M. (2022) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2022.894800 · Cited by 5
Li, J., Tang, X., Xu, J., Liu, R., Jiang, L., Xu, L., Tian, J., Feng, X., Wu, Y., Zhang, Y., et al. (2023) · BMC Cardiovascular Disorders · doi:10.1186/s12872-023-03285-w · Cited by 5
Zhang, G. (2015) · Current Genetic Medicine Reports · doi:10.1007/s40142-015-0083-9 · Cited by 5
Using genomic approaches to identify CVD-causing variants
Arnett, D. K. (2016) · Nature Reviews Cardiology · doi:10.1038/nrcardio.2015.202 · Cited by 5
Bogari, N. M., Babalghith, A. O., Bouazzaoui, A., Aljohani, A., Dannoun, A. I., ElKhateeb, O. E., Amin, A. A., Bogari, M. K., Mazhar, A. A., Porqueddu, M., et al. (2021) · Saudi Pharmaceutical Journal · doi:10.1016/j.jsps.2021.11.007 · Cited by 5
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Gao, Y., Lee, C., Song, J., Li, S., Cui, Y., Liu, Y., Wang, J., Lu, F., & Chen, H. (2017) · Oncotarget · doi:10.18632/oncotarget.22045 · Cited by 5
Self-citationRodríguez, F., & Knowles, J. W. (2016) · Circulation · doi:10.1161/circulationaha.116.023010 · Cited by 5
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Rader, D. J., Bajaj, A., & Khetarpal, S. A. (2017) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2016.11.066 · Cited by 5
Self-citationBayesian model comparison for rare variant association studiesPreprint
Venkataraman, G. R., DeBoever, C., Tanigawa, Y., Aguirre, M., Ioannidis, A. G., Mostafavi, H., Spencer, C. C. A., Poterba, T., Bustamante, C. D., Daly, M. J., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/257162 · Cited by 5
Self-citationMolecular Genetics of Coronary Artery Disease
Ozaki, K. (2017) · Wiley eBooks · doi:10.1002/9780470015902.a0027329 · Cited by 5
Martín-Campos, J. M. (2021) · Biomedicines · doi:10.3390/biomedicines9111728 · Cited by 4
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Metadata
- Authors
- Do, R., Stitziel, N. O., Won, H.-H., Jørgensen, A. B., Duga, S., Angelica Merlini, P., Kiezun, A., Farrall, M., Goel, A., Zuk, O., Guella, I., Asselta, R., Lange, L. A., Peloso, G. M., Auer, P. L., NHLBI Exome Sequencing Project, Girelli, D., Martinelli, N., Farlow, D. N., DePristo, M. A., Roberts, R., Stewart, A. F. R., Saleheen, D., Danesh, J., Epstein, S. E., Sivapalaratnam, S., Kees Hovingh, G., Kastelein, J. J., Samani, N. J., Schunkert, H., Erdmann, J., Shah, S. H., Kraus, W. E., Davies, R., Nikpay, M., Johansen, C. T., Wang, J., Hegele, R. A., Hechter, E., Marz, W., Kleber, M. E., Huang, J., Johnson, A. D., Li, M., Burke, G. L., Gross, M., Liu, Y., Assimes, T. L., Heiss, G., Lange, E. M., Folsom, A. R., Taylor, H. A., Olivieri, O., Hamsten, A., Clarke, R., Reilly, D. F., Yin, W., Rivas, M. A., Donnelly, P., Rossouw, J. E., Psaty, B. M., Herrington, D. M., Wilson, J. G., Rich, S. S., Bamshad, M. J., Tracy, R. P., Adrienne Cupples, L., Rader, D. J., Reilly, M. P., Spertus, J. A., Cresci, S., Hartiala, J., Wilson Tang, W. H., Hazen, S. L., Allayee, H., Reiner, A. P., Carlson, C. S., Kooperberg, C., Jackson, R. D., Boerwinkle, E., Lander, E. S., Schwartz, S. M., Siscovick, D. S., McPherson, R., Tybjaerg-Hansen, A., Abecasis, G. R., Watkins, H., Nickerson, D. A., Ardissino, D., Sunyaev, S. R., O'Donnell, C. J., Altshuler, D., Gabriel, S., & Kathiresan, S.
- Affiliations
- Broad Institute (US)
- Washington University in St. Louis (US)
- University of Copenhagen (DK)
- University of Milan (IT)
- Centre for Human Genetics (GB)
- University of North Carolina at Chapel Hill (US)
- Fred Hutch Cancer Center (US)
- University of Verona (IT)
- Ottawa Heart Institute (CA)
- University of Cambridge (GB)
- Amsterdam UMC Location University of Amsterdam (NL)
- University of Leicester (GB)
- German Centre for Cardiovascular Research (DE)
- Duke University (US)
- Western University (CA)
- Heidelberg University (DE)
- National Heart, Lung, and Blood Institute (US)
- University of Alabama at Birmingham (US)
- University of Minnesota (US)
- Stanford Medicine (US)
- Karolinska Institutet (SE)
- Merck & Co., Inc., Rahway, NJ, USA (United States) (US)
- Group Health Cooperative (US)
- University of Mississippi Medical Center (US)
- Seattle Children's Hospital (US)
- University of Vermont (US)
- Boston University (US)
- University of Pennsylvania (US)
- University of Missouri–Kansas City (US)
- University of Southern California (US)
- University of Washington (US)
- The Ohio State University (US)
- ORCID
- Do, Ron
- Stitziel, Nathan O.
- Won, Hong-Hee
- Duga, Stefano
- Farrall, Martin
- Goel, Anuj
- Zuk, Or
- Asselta, Rosanna
- Peloso, Gina M.
- Auer, Paul L.
- Girelli, Domenico
- Martinelli, Nicola
- Roberts, Robert
- Saleheen, Danish
- Danesh, John
- Sivapalaratnam, Suthesh
- Kastelein, John J.
- Samani, Nilesh J.
- Schunkert, Heribert
- Erdmann, Jeanette
- Shah, Svati H.
- Kraus, William E.
- Nikpay, Majid
- Wang, Jian
- Hegele, Robert A.
- Kleber, Marcus E.
- Huang, Jie
- Johnson, Andrew D.
- Li, Mingyao
- Assimes, Themistocles L.
- Heiss, Gerardo
- Lange, Ethan M.
- Folsom, Aaron R.
- Taylor, Herman A.
- Olivieri, Oliviero
- Hamsten, Anders
- Clarke, Robert
- Reilly, Dermot F.
- Rivas, Manuel A.
- Donnelly, Peter
- Rossouw, Jacques E.
- Psaty, Bruce M.
- Herrington, David M.
- Wilson, James G.
- Rich, Stephen S.
- Bamshad, Michael J.
- Tracy, Russell P.
- Rader, Daniel J.
- Reilly, Muredach P.
- Spertus, John A.
- Cresci, Sharon
- Hartiala, Jaana
- Hazen, Stanley L.
- Allayee, Hooman
- Reiner, Alex P.
- Carlson, Christopher S.
- Kooperberg, Charles
- Jackson, Rebecca D.
- Boerwinkle, Eric
- Lander, Eric S.
- Siscovick, David S.
- McPherson, Ruth
- Watkins, Hugh
- Nickerson, Deborah A.
- Ardissino, Diego
- Sunyaev, Shamil R.
- Altshuler, David
- Gabriel, Stacey
- Kathiresan, Sekar
- Venue
- Nature
- Published
- 2014-12-10
- Volume
- 518
- Issue
- 7537
- Pages
- 102-106
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC4319990
- OpenAlex
- W2050838276
- Cited by
- 650
- References
- 55
- Citations by year
- 2026: 22 · 2025: 14 · 2024: 29 · 2023: 30 · 2022: 50 · 2021: 42 · 2020: 64 · 2019: 68 · 2018: 63 · 2017: 87 · 2016: 111 · 2015: 65 · 2014: 2
- FWCI
- 87.31
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
- mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (submittedVersion)
- Pure Amsterdam UMC (submittedVersion, other-oa)
- Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
- Funders
- Massachusetts General Hospital (R01HL107816)
- Cleveland Clinic
- Foundation for Barnes-Jewish Hospital
- Donovan Family Foundation
- Wellcome Trust (095552, 090532)
- National Institute for Health and Care Research (NF-SI-0512-10165, NF-SI-0611-10170, NF-SI-0508-10235)
- British Heart Foundation (RG/08/014/24067)
- Parkinson's UK (G-0907)
- Fondation Leducq (T32HL007208)
- National Institutes of Health (1s10od020069-01, 1rc2hl103010-01, UL1TR000439, HL076491)
- Canadian Institutes of Health Research
- Medical Research Council (MR/L003120/1)
- National Institute on Aging (P30AG010129, R01AG033193)
- National Heart, Lung, and Blood Institute (HL 102923, RC2HL102925, HL-102924, K08HL114642, RC2HL102926, RC2HL102923, RC2HL-103010, HL 103010, P01HL076491, P01HL098055, RC2HL102924, T32HL00720, R01HL107816, T32HL007208, T32HL007604)
- National Human Genome Research Institute (U54HG003067)
- National Institute of Nursing Research (R01NR013396)
- National Institute of Neurological Disorders and Stroke (R01NS017950)
- National Center for Advancing Translational Sciences
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipoproteins and Cardiovascular Health
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipid metabolism and disorders
- Keywords
- early-onset myocardial infarction, LDL receptor, APOA5, rare variants, apolipoprotein A-V, LDL cholesterol, triglycerides, triglyceride-rich lipoproteins, genetic risk, exome sequencing, null alleles, cardiovascular genetics, familial hypercholesterolemia
- MeSH terms
- Apolipoprotein A-V, Age Factors, Alleles, Apolipoproteins A, Coronary Artery Disease, Female, Genetics, Population, Heterozygote, Humans, Cholesterol, LDL, Male, Middle Aged, Mutation, Myocardial Infarction, Receptors, LDL, Triglycerides, United States, Case-Control Studies, Age of Onset, Genetic Predisposition to Disease, National Heart, Lung, and Blood Institute (U.S.), Exome
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