Genetic Regulatory Mechanisms of Smooth Muscle Cells Map to Coronary Artery Disease Risk Loci
Open accessPublished version of a preprint
Abstract
Coronary artery disease (CAD) is the leading cause of death globally. Genome-wide association studies (GWASs) have identified more than 95 independent loci that influence CAD risk, most of which reside in non-coding regions of the genome. To interpret these loci, we generated transcriptome and whole-genome datasets using human coronary artery smooth muscle cells (HCASMCs) from 52 unrelated donors, as well as epigenomic datasets using ATAC-seq on a subset of 8 donors. Through systematic comparison with publicly available datasets from GTEx and ENCODE projects, we identified transcriptomic, epigenetic, and genetic regulatory mechanisms specific to HCASMCs. We assessed the relevance of HCASMCs to CAD risk using transcriptomic and epigenomic level analyses. By jointly modeling eQTL and GWAS datasets, we identified five genes (SIPA1, TCF21, SMAD3, FES, and PDGFRA) that may modulate CAD risk through HCASMCs, all of which have relevant functional roles in vascular remodeling. Comparison with GTEx data suggests that SIPA1 and PDGFRA influence CAD risk predominantly through HCASMCs, while other annotated genes may have multiple cell and tissue targets. Together, these results provide tissue-specific and mechanistic insights into the regulation of a critical vascular cell type associated with CAD in human populations.
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
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?
Given the key role of VSMCs in atherosclerosis, a number of loci have been predicted to modulate disease risk through mechanisms specific to VSMCs.
“Unsurprisingly, given the key role of VSMCs in atherosclerosis, a number of loci have been predicted to modulate disease risk through mechanisms specific to VSMCs 200 .”
From Vascular smooth muscle cells in atherosclerosis (2019) · cites this paper as [200]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400 · see citing works
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709 · see citing works
Cutadapt removes adapter sequences from high-throughput sequencing reads
Martin, M. (2011) · EMBnet.journal · doi:10.14806/ej.17.1.200 · Cited by 33,889 · see citing works
Model-based Analysis of ChIP-Seq (MACS)
Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-9-r137 · Cited by 18,386 · see citing works
Heart Disease and Stroke Statistics—2017 Update: A Report From the American Heart Association
Benjamin, E. J., Blaha, M. J., Chiuve, S. E., Cushman, M., Das, S. R., Deo, R., de Ferranti, S. D., Floyd, J., Fornage, M., Gillespie, C., et al. (2017) · Circulation · doi:10.1161/cir.0000000000000485 · Cited by 12,591 · see citing works
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 11,216 · see citing works
Statistical significance for genomewide studies
Storey, J. D., & Tibshirani, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1530509100 · Cited by 9,692 · see citing works
Van der Auwera, G. A., Carneiro, M. O., Hartl, C., Poplin, R., del Angel, G., Levy‐Moonshine, A., Jordan, T., Shakir, K., Roazen, D., Thibault, J., et al. (2013) · Current Protocols in Bioinformatics · doi:10.1002/0471250953.bi1110s43 · Cited by 6,687 · see citing works
Integrative analysis of 111 reference human epigenomes
Roadmap Epigenomics Consortium, Kundaje, A., Meuleman, W., Ernst, J., Bilenky, M., Yen, A., Heravi-Moussavi, A., Kheradpour, P., Zhang, Z., Wang, J., et al. (2015) · Nature · doi:10.1038/nature14248 · Cited by 6,368 · see citing works
Self-citationChen, X., Xiu, M., Xing, J., Yu, S., Min, D., & Guo, F. (2017) · Cellular Physiology and Biochemistry · doi:10.1159/000479439 · Cited by 5,759 · see citing works
xCell: digitally portraying the tissue cellular heterogeneity landscape
Aran, D., Hu, Z., & Butte, A. J. (2017) · Genome Biology · doi:10.1186/s13059-017-1349-1 · Cited by 4,397 · see citing works
Giambartolomei, C., Vukcevic, D., Schadt, E. E., Franke, L., Hingorani, A. D., Wallace, C., & Plagnol, V. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004383 · Cited by 4,261 · see citing works
Genetic effects on gene expression across human tissues
GTEx Consortium (2017) · Nature · doi:10.1038/nature24277 · Cited by 4,036 · see citing works
Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets
Zhu, Z., Zhang, F., Hu, H., Bakshi, A., Robinson, M. R., Powell, J. E., Montgomery, G. W., Goddard, M. E., Wray, N. R., Visscher, P. M., et al. (2016) · Nature Genetics · doi:10.1038/ng.3538 · Cited by 3,352 · see citing works
ATAC-seq: a method for assaying chromatin accessibility genome-wide
Buenrostro, J. D., Wu, B., Chang, H. Y., & Greenleaf, W. J. (2015) · Current Protocols in Molecular Biology · doi:10.1002/0471142727.mb2129s109 · Cited by 3,289 · see citing works
An Expanded View of Complex Traits: From Polygenic to Omnigenic
Boyle, E. A., Li, Y. I., & Pritchard, J. K. (2017) · Cell · doi:10.1016/j.cell.2017.05.038 · Cited by 2,851 · see citing works
Partitioning heritability by functional annotation using genome-wide association summary statistics
ReproGen Consortium, Finucane, H. K., Schizophrenia Working Group of the Psychiatric Genomics Consortium, The RACI Consortium, Bulik-Sullivan, B., Gusev, A., Trynka, G., Reshef, Y., Loh, P.-R., Anttila, V., et al. (2015) · Nature Genetics · doi:10.1038/ng.3404 · Cited by 2,604 · see citing works
A high-performance computing toolset for relatedness and principal component analysis of SNP data
Zheng, X., Levine, D., Shen, J., Gogarten, S. M., Laurie, C. C., & Weir, B. S. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts606 · Cited by 2,541 · see citing works
A comprehensive 1000 Genomes–based genome-wide association meta-analysis of coronary artery disease
the CARDIoGRAMplusC4D Consortium (2015) · Nature Genetics · doi:10.1038/ng.3396 · Cited by 2,447 · see citing works
Role of platelet-derived growth factors in physiology and medicinePreprint
Andræ, J., Gallini, R., & Betsholtz, C. (2008) · Genes & Development · doi:10.1101/gad.1653708 · Cited by 2,443 · see citing works
Adipose Tissue, Inflammation, and Cardiovascular Disease
Berg, A. H., & Scherer, P. E. (2005) · Circulation Research · doi:10.1161/01.res.0000163635.62927.34 · Cited by 2,113 · see citing works
Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease
Cardiogenics, Schunkert, H., the CARDIoGRAM Consortium, König, I. R., Kathiresan, S., Reilly, M. P., Assimes, T. L., Holm, H., Preuss, M., Stewart, A. F. R., et al. (2011) · Nature Genetics · doi:10.1038/ng.784 · Cited by 1,866 · see citing works
Self-citationLarge-scale association analysis identifies new risk loci for coronary artery disease
The CARDIoGRAMplusC4D Consortium, Deloukas, P., DIAGRAM Consortium, CARDIOGENICS Consortium, MuTHER Consortium, Wellcome Trust Case Control Consortium, Kanoni, S., Willenborg, C., Farrall, M., Assimes, T. L., et al. (2013) · Nature Genetics · doi:10.1038/ng.2480 · Cited by 1,614 · see citing works
Self-citationGenetic Risk, Adherence to a Healthy Lifestyle, and Coronary Disease
Khera, A. V., Emdin, C. A., Drake, I., Natarajan, P., Bick, A. G., Cook, N. R., Chasman, D. I., Baber, U., Mehran, R., Rader, D. J., et al. (2016) · New England Journal of Medicine · doi:10.1056/nejmoa1605086 · Cited by 1,460 · see citing works
Self-citation<i>FTO</i> Obesity Variant Circuitry and Adipocyte Browning in Humans
Claussnitzer, M., Dankel, S. N., Kim, K.-H., Quon, G., Meuleman, W., Haugen, C., Glunk, V., Sousa, I. S., Beaudry, J. L., Puviindran, V., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1502214 · Cited by 1,332 · see citing works
The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease
Astle, W. J., Elding, H., Jiang, T., Allen, D., Ruklisa, D., Mann, A. L., Mead, D., Bouman, H., Riveros-Mckay, F., Kostadima, M. A., et al. (2016) · Cell · doi:10.1016/j.cell.2016.10.042 · Cited by 1,224 · see citing works
Shankman, L. S., Gomez, D., Cherepanova, O. A., Salmon, M., Alencar, G. F., Haskins, R. M., Swiatlowska, P., Newman, A. A. C., Greene, E. S., Straub, A. C., et al. (2015) · Nature Medicine · doi:10.1038/nm.3866 · Cited by 1,218 · see citing works
van der Harst, P., & Verweij, N. (2018) · Circulation Research · doi:10.1161/circresaha.117.312086 · Cited by 1,141 · see citing works
From 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 · see citing works
Self-citationStegle, O., Parts, L., Piipari, M., Winn, J., & Durbin, R. (2012) · Nature Protocols · doi:10.1038/nprot.2011.457 · Cited by 1,049 · see citing works
Measuring reproducibility of high-throughput experiments
Li, Q., Brown, J. B., Huang, H., & Bickel, P. J. (2011) · The Annals of Applied Statistics · doi:10.1214/11-aoas466 · Cited by 1,008 · see citing works
Measuring reproducibility of high-throughput experiments
Li, Q., Brown, J. B., Huang, H., & Bickel, P. J. (2010) · UC Berkeley · Cited by 915 · see citing works
RNA-SeQC: RNA-seq metrics for quality control and process optimization
DeLuca, D. S., Levin, J. Z., Sivachenko, A., Fennell, T., Nazaire, M.-D., Williams, C., Reich, M., Winckler, W., & Getz, G. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts196 · Cited by 899 · see citing works
Shankman, L. S., Gomez, D. A., Cherepanova, O. A., Salmon, M., Alencar, G. F., Haskins, R. M., Swiatlowska, P., Newman, A. A. C., Greene, E. S., Straub, A. C., et al. (2016) · Nature Medicine · doi:10.1038/nm0216-217a · Cited by 775 · see citing works
Abundant quantitative trait loci exist for DNA methylation and gene expression in human brain
Gibbs, J. R., van der Brug, M. P., Hernandez, D. G., Traynor, B. J., Nalls, M. A., Lai, S.-L., Arepalli, S., Dillman, A., Rafferty, I. P., Troncoso, J., et al. (2010) · PLoS Genetics · doi:10.1371/journal.pgen.1000952 · Cited by 769 · see citing works
Annotation-free quantification of RNA splicing using LeafCutter
Li, Y. I., Knowles, D. A., Humphrey, J., Barbeira, A. N., Dickinson, S. P., Im, H. K., & Pritchard, J. K. (2018) · Nature Genetics · doi:10.1038/s41588-017-0004-9 · Cited by 765 · see citing works
Colocalization of GWAS and eQTL Signals Detects Target Genes
Hormozdiari, F., van de Bunt, M., Segrè, A. V., Li, X., Joo, J. W. J., Bilow, M., Sul, J. H., Sankararaman, S., Pasaniuc, B., & Eskin, E. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.10.003 · Cited by 697 · see citing works
Verrecchia, F., & Mauviel, A. (2002) · Journal of Investigative Dermatology · doi:10.1046/j.1523-1747.2002.01641.x · Cited by 669 · see citing works
Association analyses based on false discovery rate implicate new loci for coronary artery disease
Nelson, C. P., CARDIoGRAMplusC4D, Goel, A., Butterworth, A. S., Kanoni, S., Webb, T. R., Marouli, E., Zeng, L., Ντάλλα, Ι., Lai, F. Y., et al. (2017) · Nature Genetics · doi:10.1038/ng.3913 · Cited by 663 · see citing works
Self-citationRNA splicing is a primary link between genetic variation and disease
Li, Y. I., van de Geijn, B., Raj, A., Knowles, D. A., Petti, A. A., Golan, D., Gilad, Y., & Pritchard, J. K. (2016) · Science · doi:10.1126/science.aad9417 · Cited by 660 · see citing works
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 · see citing works
Ahola-Olli, A. V., Würtz, P., Havulinna, A. S., Aalto, K., Pitkänen, N., Lehtimäki, T., Kähönen, M., Lyytikäinen, L.-P., Raitoharju, E., Seppälä, I., et al. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.11.007 · Cited by 628 · see citing works
WASP: allele-specific software for robust molecular quantitative trait locus discovery
van de Geijn, B., McVicker, G., Gilad, Y., & Pritchard, J. K. (2015) · Nature Methods · doi:10.1038/nmeth.3582 · Cited by 575 · see citing works
Fast and efficient QTL mapper for thousands of molecular phenotypes
Ongen, H., Buil, A., Brown, A. A., Dermitzakis, E. T., & Delaneau, O. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv722 · Cited by 571 · see citing works
ENCODE data at the ENCODE portal
Sloan, C. A., Chan, E. T., Davidson, J. M., Malladi, V. S., Strattan, J. S., Hitz, B. C., Gabdank, I., Narayanan, A. K., Ho, M., Lee, B. T., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1160 · Cited by 549 · see citing works
Heritability of death from coronary heart disease: a 36‐year follow‐up of 20 966 Swedish twins
Zdravkovic, S., Wienke, A., Pedersen, N. L., Marenberg, M. E., Yashin, A. I., & Fairé, U. D. (2002) · Journal of Internal Medicine · doi:10.1046/j.1365-2796.2002.01029.x · Cited by 512 · see citing works
Acharya, A., Baek, S. T., Huang, G., Eskiocak, B., Goetsch, S., Sung, C. Y., Banfi, S., Sauer, M. F., Olsen, G. S., Duffield, J. S., et al. (2012) · Development · doi:10.1242/dev.079970 · Cited by 498 · see citing works
Passive and active DNA methylation and the interplay with genetic variation in gene regulation
Gutierrez-Arcelus, M., Lappalainen, T., Montgomery, S. B., Buil, A., Ongen, H., Yurovsky, A., Bryois, J., Giger, T., Romano, L., Planchon, A., et al. (2013) · eLife · doi:10.7554/elife.00523 · Cited by 440 · see citing works
Self-citationNica, A. C., Montgomery, S. B., Dimas, A. S., Stranger, B. E., Beazley, C., Barroso, I., & Dermitzakis, E. T. (2010) · PLoS Genetics · doi:10.1371/journal.pgen.1000895 · Cited by 423 · see citing works
Self-citationFox transcription factors: from development to disease
Golson, M. L., & Kaestner, K. H. (2016) · Development · doi:10.1242/dev.112672 · Cited by 406 · see citing works
Iwafuchi-Doi, M., Donahue, G., Kakumanu, A., Watts, J. A., Mahony, S., Pugh, B. F., Lee, D., Kaestner, K. H., & Zaret, K. S. (2016) · Molecular Cell · doi:10.1016/j.molcel.2016.03.001 · Cited by 390 · see citing works
Endothelial function and coronary artery disease
Kinlay, S., Libby, P., & Ganz, P. (2001) · Current Opinion in Lipidology · doi:10.1097/00041433-200108000-00003 · Cited by 384 · see citing works
Monocytes in Coronary Artery Disease and Atherosclerosis
Ghattas, A., Griffiths, H. R., Devitt, A., Lip, G. Y. H., & Shantsila, E. (2013) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2013.07.043 · Cited by 376 · see citing works
Li, S., Weidenfeld, J., & Morrisey, E. E. (2003) · Molecular and Cellular Biology · doi:10.1128/mcb.24.2.809-822.2004 · Cited by 333 · see citing works
Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms
CARDIoGRAMplusC4D, Howson, J. M. M., EPIC-CVD, Zhao, W., Barnes, D. R., Ho, W.-K., Young, R., Paul, D. S., Waite, L. L., Freitag, D. F., et al. (2017) · Nature Genetics · doi:10.1038/ng.3874 · Cited by 304 · see citing works
Self-citationOrigin and differentiation of vascular smooth muscle cells
Wang, G., Jacquet, L., Karamariti, E., & Xu, Q. (2015) · The Journal of Physiology · doi:10.1113/jp270033 · Cited by 300 · see citing works
Fine-mapping cellular QTLs with RASQUAL and ATAC-seq
Kumasaka, N., Knights, A. J., & Gaffney, D. J. (2015) · Nature Genetics · doi:10.1038/ng.3467 · Cited by 259 · see citing works
Closing in on the biological functions of fps/fes and fer
Greer, P. A. (2002) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm783 · Cited by 248 · see citing works
Peeters, M.-P. F. M. V., Groot, A. C. G., Mentink, M. M. T., & Poelmann, R. E. (1999) · Anatomy and Embryology · doi:10.1007/s004290050235 · Cited by 242 · see citing works
Activation of the pluripotency factor OCT4 in smooth muscle cells is atheroprotective
Cherepanova, O. A., Gomez, D., Shankman, L. S., Swiatlowska, P., Williams, J., Sarmento, O. F., Alencar, G. F., Hess, D. L., Bevard, M. H., Greene, E. S., et al. (2016) · Nature Medicine · doi:10.1038/nm.4109 · Cited by 221 · see citing works
Klarin, D., Zhu, Q., Emdin, C., Chaffin, M., Horner, S., McMillan, B., Leed, A. J., Weale, M., Spencer, C., Aguet, F., et al. (2017) · Nature Genetics · doi:10.1038/ng.3914 · Cited by 214 · see citing works
Browning, B. L., & Yu, Z. (2009) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2009.11.004 · Cited by 212 · see citing works
Interpreting Meta-Analyses of Genome-Wide Association Studies
Han, B., & Eskin, E. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002555 · Cited by 173 · see citing works
Schmidt, E. M., Zhang, J., Zhou, W., Chen, J., Mohlke, K. L., Chen, Y., & Willer, C. J. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv201 · Cited by 150 · see citing works
He, C., Medley, S. C., Hu, T., Hinsdale, M. E., Lupu, F., Virmani, R., & Olson, L. E. (2015) · Nature Communications · doi:10.1038/ncomms8770 · Cited by 150 · see citing works
Integrative functional genomics identifies regulatory mechanisms at coronary artery disease loci
Miller, C. L., Pjanic, M., Wang, T., Nguyen, T., Cohain, A. T., Lee, J. D., Matic, L. P., Hedin, U., Kundu, R. K., Majmudar, D., et al. (2016) · Nature Communications · doi:10.1038/ncomms12092 · Cited by 139 · see citing works
Self-citationBraitsch, C. M., Combs, M. D., Quaggin, S. E., & Yutzey, K. E. (2012) · Developmental Biology · doi:10.1016/j.ydbio.2012.06.002 · Cited by 137 · see citing works
Kurachi, H., Wada, Y., Tsukamoto, N., Maeda, M., KUBOTA, H. Y., Hattori, M., Iwaï, K., & Minato, N. (1997) · Journal of Biological Chemistry · doi:10.1074/jbc.272.44.28081 · Cited by 124 · see citing works
Hovland, A., Jonasson, L., Garred, P., Yndestad, A., Aukrust, P., Lappegård, K. T., Espevik, T., & Mollnes, T. E. (2015) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2015.05.038 · Cited by 113 · see citing works
Miller, C. L., Haas, U., Caceres, R. D., Leeper, N. J., Kundu, R. K., Patlolla, B., Assimes, T. L., Kaiser, F. J., Matic, L. P., Hedin, U., et al. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004263 · Cited by 112 · see citing works
Self-citationPu, X., Xiao, Q., Kiechl, S. J., Chan, K., Ng, F. L., Gor, S., Poston, R. N., Fang, C., Patel, A. S., Senver, E. C., et al. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2013.01.012 · Cited by 111 · see citing works
Nürnberg, S., Cheng, K. W., Raiesdana, A., Kundu, R. K., Miller, C. L., Kim, J. B., Arora, K., Carcamo‐Orive, I., Xiong, Y., Tellakula, N., et al. (2015) · PLoS Genetics · doi:10.1371/journal.pgen.1005155 · Cited by 97 · see citing works
Self-citationHogan, N. T., Whalen, M. B., Stolze, L. K., Hadeli, N. K., Lam, M. T. Y., Springstead, J. R., Glass, C. K., & Romanoski, C. E. (2017) · eLife · doi:10.7554/elife.22536 · Cited by 92 · see citing works
Won, H., Natarajan, P., Dobbyn, A. L., Jordan, D. M., Roussos, P., Lage, K., Raychaudhuri, S., Stahl, E. A., & Do, R. (2015) · PLoS Genetics · doi:10.1371/journal.pgen.1005622 · Cited by 90 · see citing works
Hattori, M., Tsukamoto, N., Nur-e-Kamal, M. S. A., Rubinfeld, B., Iwaï, K., KUBOTA, H. Y., Maruta, H., & Minato, N. (1995) · Molecular and Cellular Biology · doi:10.1128/mcb.15.1.552 · Cited by 89 · see citing works
Srivastava, R., Zhang, J., Go, G., Narayanan, A., Nottoli, T., & Mani, A. (2015) · Cell Reports · doi:10.1016/j.celrep.2015.09.028 · Cited by 74 · see citing works
Shaheen, R., Anazi, S., Ben‐Omran, T., Seidahmed, M. Z., Caddle, L. B., Palmer, K. J., Ali, R., Alshidi, T. A., Hagos, S. T., Goodwin, L. O., et al. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.02.010 · Cited by 72 · see citing works
Kim, J. B., Pjanic, M., Nguyen, T., Miller, C. L., Iyer, D., Liu, B., Wang, T., Sazonova, O., Carcamo‐Orive, I., Matic, L. P., et al. (2017) · PLoS Genetics · doi:10.1371/journal.pgen.1006750 · Cited by 71 · see citing works
Self-citationTobacco smoking is associated with methylation of genes related to coronary artery disease
Steenaard, R. V., Ligthart, S., Stolk, L., Peters, M. J., van Meurs, J. B. J., Uitterlinden, A. G., Albert Hofman, D., Franco, O. H., & Dehghan, A. (2015) · Clinical Epigenetics · doi:10.1186/s13148-015-0088-y · Cited by 66 · see citing works
Turner, A. W., Martinuk, A., Silva, A., Lau, P., Nikpay, M., Eriksson, P. O., Folkersen, L., Matic, L. P., Hedin, U., Soubeyrand, S., et al. (2016) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.116.307294 · Cited by 54 · see citing works
TreeQTL: hierarchical error control for eQTL findings
Peterson, C. B., Bogomolov, M., Benjamini, Y., & Sabatti, C. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw198 · Cited by 36 · see citing works
Bot, P. T. G., Grundmann, S., Goumans, M., et al. (2011) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2011.05.017 · Cited by 29 · see citing works
LeafCutter: annotation-free quantification of RNA splicingPreprint
Li, Y., Knowles, D. A., Humphrey, J., et al. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/044107 · Cited by 28 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Corces, M. R., Shcherbina, A., Kundu, S., Gloudemans, M. J., Frésard, L., Granja, J. M., Louie, B. H., Eulalio, T., Shams, S., Bagdatli, S. T., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-00721-x · Cited by 358 · see citing works
Self-citationMosquera, J. V., Auguste, G., Wong, D., Turner, A. W., Hodonsky, C. J., Alvarez-Yela, A. C., Song, Y., Cheng, Q., Lino Cardenas, C. L., Theofilatos, K., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.113380 · Cited by 123 · see citing works
Self-citationThe <i>FES</i> Gene at the 15q26 Coronary-Artery-Disease Locus Inhibits Atherosclerosis
Karamanavi, E., McVey, D. G., van der Laan, S. W., Stanczyk, P. J., Morris, G. E., Wang, Y., Yang, W., Chan, K., Poston, R. N., Luo, J., et al. (2022) · Circulation Research · doi:10.1161/circresaha.122.321146 · Cited by 54 · see citing works
- Authors
- Liu, B., Pjanic, M., Wang, T., Nguyen, T., Gloudemans, M., Rao, A., Castano, V. G., Nurnberg, S., Rader, D. J., Elwyn, S., Ingelsson, E., Montgomery, S. B., Miller, C. L., & Quertermous, T.
- Affiliations
- Stanford Medicine (US)
- University of Pennsylvania (US)
- University of Virginia (US)
- Corresponding author
- Quertermous, Thomas
- ORCID
- Venue
- The American Journal of Human Genetics
- Publisher
- Elsevier BV
- Published
- 2018-09
- Volume
- 103
- Issue
- 3
- Pages
- 377-388
- ISSN
- 0002-9297 (ISSN-L)
- PMC
- PMC6128252
- OpenAlex
- W2951755171
- Cited by
- 94
- References
- 83
- Citations by year
- 2026: 7 · 2025: 7 · 2024: 9 · 2023: 17 · 2022: 15 · 2021: 11 · 2020: 11 · 2019: 13 · 2018: 4
- FWCI
- 5.98
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- The American Journal of Human Genetics (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (R00HL125912, R01DK107437, R01HL109512, R01HL134817, R01HL139478, R33HL120757)
- National Heart, Lung, and Blood Institute (U01HG009431)
- National Human Genome Research Institute (ENCODE4, R01HG008150, R01MH101814)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Immunology and Microbiology › Immunology › Atherosclerosis and Cardiovascular Diseases
- Keywords
- coronary artery disease, coronary artery smooth muscle cells, expression quantitative trait loci, epigenetic regulation, non-coding variants, SIPA1, TCF21, Smad3, FeS, PDGFRA, vascular remodeling, cell type specificity, tissue-specific gene regulation
- MeSH terms
- Cell Line, Coronary Artery Disease, Coronary Vessels, Gene Expression Regulation, Humans, Risk, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Genomics, Myocytes, Smooth Muscle, Quantitative Trait Loci, Genome-Wide Association Study
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
