A Systems Biology Framework Identifies Molecular Underpinnings of Coronary Heart Disease
Open accessAbstract
Objective—: Genetic approaches have identified numerous loci associated with coronary heart disease (CHD). The molecular mechanisms underlying CHD gene–disease associations, however, remain unclear. We hypothesized that genetic variants with both strong and subtle effects drive gene subnetworks that in turn affect CHD. Approach and Results—: We surveyed CHD-associated molecular interactions by constructing coexpression networks using whole blood gene expression profiles from 188 CHD cases and 188 age- and sex-matched controls. Twenty-four coexpression modules were identified, including 1 case-specific and 1 control-specific differential module (DM). The DMs were enriched for genes involved in B-cell activation, immune response, and ion transport. By integrating the DMs with gene expression–associated single-nucleotide polymorphisms and with results of genome-wide association studies of CHD and its risk factors, the control-specific DM was implicated as CHD causal based on its significant enrichment for both CHD and lipid expression–associated single-nucleotide polymorphisms. This causal DM was further integrated with tissue-specific Bayesian networks and protein–protein interaction networks to identify regulatory key driver genes. Multitissue key drivers ( SPIB and TNFRSF13C ) and tissue-specific key drivers (eg, EBF1 ) were identified. Conclusions—: Our network-driven integrative analysis not only identified CHD-related genes, but also defined network structure that sheds light on the molecular interactions of genes associated with CHD risk.
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Networks can be modeled as graphs consisting of elements that exhibit specific interactions with other elements.
“One way to model such networks is as graphs consisting of elements that exhibit specific interactions with other elements [60–64].”
From Multi-omics approaches to disease (2017) · cites this paper as [61]
Communities of co-expressed proteins can be linked to disease processes, and hub proteins within co-expression modules are enriched in key drivers of disease pathogenesis.
“Communities of co-expressed proteins can be linked to disease processes, and the most strongly correlated proteins, or “hubs,” within these co-expression modules are enriched in key drivers of disease pathogenesis5–10.”
Systems-based approaches such as WGCNA can be used to analyze biochemical and cellular changes in brain and are useful to capture the complexity of perturbations in biological networks related to disease.
“Systems-based approaches such as weighted gene co-expression network analysis (WGCNA) can be used to analyze biochemical and cellular changes in brain, and are useful to help capture the complexity of perturbations in biological networks that are related to disease [2–4].”
From Deep proteomic network analysis of Alzheimer’s disease brain reveals alterations in RNA binding proteins and RNA splicing associated with disease (2018) · cites this paper as [2]
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Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206 · see citing works
KEGG: Kyoto Encyclopedia of Genes and Genomes
Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., & Kanehisa, M. (1999) · Nucleic Acids Research · doi:10.1093/nar/27.1.29 · Cited by 31,232 · see citing works
WGCNA: an R package for weighted correlation network analysis
Langfelder, P., & Horvath, S. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-559 · Cited by 27,252 · see citing works
Lozano, R., Naghavi, M., Foreman, K., Lim, S., Shibuya, K., Aboyans, V., Abraham, J., Adair, T., Aggarwal, R., Ahn, S. Y., et al. (2012) · The Lancet · doi:10.1016/s0140-6736(12)61728-0 · Cited by 14,070 · see citing works
Genetics of Food Intake Self-Regulation in Childhood: Literature Review and Research Opportunities
Faith, M. S., Carnell, S., & Kral, T. V. E. (2013) · Human Heredity · doi:10.1159/000353879 · Cited by 7,628 · see citing works
A General Framework for Weighted Gene Co-Expression Network Analysis
Zhang, B., & Horvath, S. (2005) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1128 · Cited by 5,684 · see citing works
Self-citationProgress and challenges in translating the biology of atherosclerosis
Libby, P., Ridker, P. M., & Hansson, G. K. (2011) · Nature · doi:10.1038/nature10146 · Cited by 4,010 · see citing works
Biological, clinical and population relevance of 95 loci for blood lipids
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., et al. (2010) · Nature · doi:10.1038/nature09270 · Cited by 3,487 · see citing works
Self-citationGlass, C. K., & Witztum, J. L. (2001) · Cell · doi:10.1016/s0092-8674(01)00238-0 · Cited by 3,049 · see citing works
Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index
MAGIC, Speliotes, E. K., on behalf of Procardis Consortium, Willer, C. J., Berndt, S. I., Monda, K. L., Thorleifsson, G., Jackson, A. U., Allen, H. L., Lindgren, C. M., et al. (2010) · Nature Genetics · doi:10.1038/ng.686 · Cited by 2,912 · see citing works
The immune response in atherosclerosis: a double-edged sword
Hansson, G. K., & Libby, P. (2006) · Nature reviews. Immunology · doi:10.1038/nri1882 · Cited by 2,176 · see citing works
Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk
The International Consortium for Blood Pressure Genome-Wide Association Studies (2011) · Nature · doi:10.1038/nature10405 · Cited by 2,033 · see citing works
Self-citationDefining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R
Langfelder, P., Zhang, B., & Horvath, S. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btm563 · Cited by 1,892 · see citing works
Self-citationLarge-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-citationTwelve type 2 diabetes susceptibility loci identified through large-scale association analysis
The MAGIC investigators, Voight, B. F., The GIANT Consortium, Scott, L. J., Steinthorsdottir, V., Morris, A. P., Dina, C., Welch, R. P., Zeggini, E., Huth, C., et al. (2010) · Nature Genetics · doi:10.1038/ng.609 · Cited by 1,761 · see citing works
Genome-wide association study of blood pressure and hypertension
Levy, D., Ehret, G. B., Rice, K., Verwoert, G. C., Launer, L. J., Dehghan, A., Glazer, N. L., Morrison, A. C., Johnson, A. D., Aspelund, T., et al. (2009) · Nature Genetics · doi:10.1038/ng.384 · Cited by 1,364 · see citing works
Self-citationGenetics of gene expression and its effect on disease
Emilsson, V., Thorleifsson, G., Zhang, B., Leonardson, A. S., Zink, F., Zhu, J., Carlson, S., Helgason, A., Walters, G. B., Gunnarsdottir, S., et al. (2008) · Nature · doi:10.1038/nature06758 · Cited by 1,296 · see citing works
Self-citationGenome-wide association study identifies eight loci associated with blood pressure
Wellcome Trust Case Control Consortium, Newton-Cheh, C., Johnson, T., Gateva, V., Tobin, M. D., Bochud, M., Coin, L., Najjar, S. S., Zhao, J. H., Heath, S. C., et al. (2009) · Nature Genetics · doi:10.1038/ng.361 · Cited by 1,215 · see citing works
Self-citationMapping the Genetic Architecture of Gene Expression in Human Liver
Schadt, E. E., Molony, C. M., Chudin, E., Hao, K., Yang, X., Lum, P. Y., Kasarskis, A., Zhang, B., Wang, S. S.-M., Suver, C., et al. (2008) · PLoS Biology · doi:10.1371/journal.pbio.0060107 · Cited by 909 · see citing works
Self-citationVariations in DNA elucidate molecular networks that cause disease
Chen, Y., Zhu, J., Lum, P. Y., Yang, X., Pinto, S., MacNeil, D. J., Zhang, C., Lamb, J., Edwards, S., Sieberts, S. K., et al. (2008) · Nature · doi:10.1038/nature06757 · Cited by 887 · see citing works
Self-citationAssociation analyses of 249,796 individuals reveal 18 new loci associated with body mass index
Speliotes, E. K., Willer, C. J., Berndt, S. I., Monda, K. L., Þorleifsson, G., Jackson, A., Allen, H. L., Lindgren, C. M., Luan, J., Mägi, R., et al. (2010) · Carolina Digital Repository (University of North Carolina at Chapel Hill) · doi:10.17615/d3bn-7g86 · Cited by 767 · see citing works
Park, J.-H., Wacholder, S., Gail, M. H., Peters, U., Jacobs, K. B., Chanock, S. J., & Chatterjee, N. (2010) · Nature Genetics · doi:10.1038/ng.610 · Cited by 678 · see citing works
Human protein reference database--2006 update
Mishra, G. (2005) · Nucleic Acids Research · doi:10.1093/nar/gkj141 · Cited by 601 · see citing works
Protective immunity against atherosclerosis carried by B cells of hypercholesterolemic mice
Caligiuri, G., Nicoletti, A., Poirier, B., & Hansson, G. K. (2002) · Journal of Clinical Investigation · doi:10.1172/jci7272 · Cited by 531 · see citing works
B cell depletion reduces the development of atherosclerosis in mice
Ait‐Oufella, H., Herbin, O., Bouaziz, J., Binder, C. J., Uyttenhove, C., Laurans, L., Taleb, S., Vré, E. A. V., Esposito, B., Vilar, J., et al. (2010) · The Journal of Experimental Medicine · doi:10.1084/jem.20100155 · Cited by 469 · see citing works
Segrè, A. V., DIAGRAM Consortium, MAGIC investigators, Groop, L., Mootha, V. K., Daly, M. J., & Altshuler, D. (2010) · PLoS Genetics · doi:10.1371/journal.pgen.1001058 · Cited by 463 · see citing works
A Genome-Wide Association Study of Hypertension and Blood Pressure in African Americans
Adeyemo, A., Gerry, N., Chen, G.-J., Herbert, A., Doumatey, A., Huang, H.-X., Zhou, J., Lashley, K., Chen, Y.-X., Christman, M., et al. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000564 · Cited by 412 · see citing works
Kyaw, T. S., Tay, C., Krishnamurthi, S., Kanellakis, P., Agrotis, A., Tipping, P. G., Bobik, A., & Toh, B. (2011) · Circulation Research · doi:10.1161/circresaha.111.248542 · Cited by 333 · see citing works
Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks
Yang, X., Deignan, J. L., Qi, H., Zhu, J., Qian, S., Zhong, J., Torosyan, G., Majid, S., Falkard, B., Kleinhanz, R. R., et al. (2009) · Nature Genetics · doi:10.1038/ng.325 · Cited by 288 · see citing works
Self-citationSystematic genetic and genomic analysis of cytochrome P450 enzyme activities in human liverPreprint
Yang, X., Zhang, B., Molony, C. M., Chudin, E., Hao, K., Zhu, J., Gaedigk, A., Suver, C., Zhong, H., Leeder, J. S., et al. (2010) · Genome Research · doi:10.1101/gr.103341.109 · Cited by 271 · see citing works
Self-citationHuman Protein Reference Database
Wilson, N. (2004) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm1305 · Cited by 253 · see citing works
Integrating Pathway Analysis and Genetics of Gene Expression for Genome-wide Association Studies
Zhong, H., Yang, X., Kaplan, L. M., Molony, C. M., & Schadt, E. E. (2010) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2010.02.020 · Cited by 234 · see citing works
Self-citationAdaptive immunity in atherosclerosis: mechanisms and future therapeutic targets
Lahoute, C., Herbin, O., Mallat, Z., & Tedgui, A. (2011) · Nature Reviews Cardiology · doi:10.1038/nrcardio.2011.62 · Cited by 229 · see citing works
An integrative genomics approach to the reconstruction of gene networks in segregating populations
Zhu, J., Lum, P. Y., Lamb, J., GuhaThakurta, D., Edwards, S. W., Thieringer, R., Berger, J. P., Wu, M. S., Thompson, J., Sachs, A. B., et al. (2004) · Cytogenetic and Genome Research · doi:10.1159/000078209 · Cited by 221 · see citing works
Self-citationZhu, J., Wiener, M. C., Zhang, C., Fridman, A., Minch, E., Lum, P. Y., Sachs, J. R., & Schadt, E. E. (2007) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0030069 · Cited by 209 · see citing works
Self-citationCorrelation of Peripheral-Blood Gene Expression With the Extent of Coronary Artery Stenosis
Wingrove, J. A., Daniels, S. E., Sehnert, A. J., Tingley, W. G., Elashoff, M. R., Rosenberg, S. J., Buellesfeld, L., Grube, E., Newby, L. K., Ginsburg, G. S., et al. (2008) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.108.782730 · Cited by 194 · see citing works
GSEA-SNP: applying gene set enrichment analysis to SNP data from genome-wide association studies
Holden, M., Deng, S., Wojnowski, L., & Kulle, B. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn516 · Cited by 187 · see citing works
Rosenberg, S. J., Elashoff, M. R., Beineke, P., Daniels, S. E., Wingrove, J. A., Tingley, W. G., Sager, P. T., Sehnert, A. J., Yau, M., Kraus, W. E., et al. (2010) · Annals of Internal Medicine · doi:10.7326/0003-4819-153-7-201010050-00005 · Cited by 172 · see citing works
Gene Expression Patterns in Peripheral Blood Correlate with the Extent of Coronary Artery Disease
Sinnaeve, P., Donahue, M., Grass, P., Seo, D., Vonderscher, J., Chibout, S., Kraus, W. E., Sketch, M. H., Nelson, C. L., Ginsburg, G. S., et al. (2009) · PLoS ONE · doi:10.1371/journal.pone.0007037 · Cited by 167 · see citing works
Liver and Adipose Expression Associated SNPs Are Enriched for Association to Type 2 Diabetes
Zhong, H., Beaulaurier, J., Lum, P. Y., Molony, C. M., Yang, X., MacNeil, D. J., Weingarth, D. T., Zhang, B., Greenawalt, D. M., Dobrin, R., et al. (2010) · PLoS Genetics · doi:10.1371/journal.pgen.1000932 · Cited by 164 · see citing works
Self-citationBAFF Receptor Deficiency Reduces the Development of Atherosclerosis in Mice—Brief Report
Sage, A. P., Tsiantoulas, D., Baker, L. L., Harrison, J. E., Masters, L. M., Murphy, D., Loinard, C., Binder, C. J., & Mallat, Z. (2012) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.111.244731 · Cited by 154 · see citing works
Multiple Loci Are Associated with White Blood Cell Phenotypes
Nalls, M. A., Couper, D. J., Tanaka, T., van Rooij, F. J. A., Chen, M., Smith, A. V., Toniolo, D., Zakai, N. A., Yang, Q., Greinacher, A., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002113 · Cited by 123 · see citing works
Self-citationSNP-based pathway enrichment analysis for genome-wide association studies
Weng, L., Macciardi, F. M., Subramanian, A., Guffanti, G., Potkin, S. G., Yu, Z., & Xie, X. S. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-99 · Cited by 121 · see citing works
Gene Expression Signatures of Coronary Heart Disease
Joehanes, R., Ying, S., Huan, T., Johnson, A. D., Raghavachari, N., Wang, R., Liu, P., Woodhouse, K. A., Sen, S. K., Tanrıverdi, K., et al. (2013) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.112.301169 · Cited by 114 · see citing works
Self-citationCADgene: a comprehensive database for coronary artery disease genes
Liu, H., Liu, W., Liao, Y., Cheng, L., Liu, Q., Ren, X. S., Shi, L., Tu, X., Wang, Q. K., & Guo, A. Y. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq1106 · Cited by 83 · see citing works
Altered Metabolism and Lipodystrophy in the Early B-Cell Factor 1-Deficient Mouse
Fretz, J. A., Nelson, T., Xi, Y., Adams, D. J., Rosen, C. J., & Horowitz, M. C. (2010) · Endocrinology · doi:10.1210/en.2009-0987 · Cited by 61 · see citing works
Identification and validation of genes affecting aortic lesions in mice
Yang, X., Peterson, L. L., Thieringer, R., Deignan, J. L., Wang, X., Zhu, J., Wang, S. S.-M., Zhong, H., Stepaniants, S., Beaulaurier, J., et al. (2010) · Journal of Clinical Investigation · doi:10.1172/jci42742 · Cited by 56 · see citing works
Self-citationDerry, J. M. J., Zhong, J., Molony, C. M., MacNeil, D., GuhaThakurta, D., Zhang, B., Mudgett, J. S., Small, K. M., Fertak, L. E., Guimond, A., et al. (2010) · PLoS ONE · doi:10.1371/journal.pone.0014319 · Cited by 42 · see citing works
Self-citationProteoLens: a visual analytic tool for multi-scale database-driven biological network data mining
Huan, T., Sivachenko, A., Harrison, S. H., & Chen, J. Y. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-s9-s5 · Cited by 37 · see citing works
Self-citationRefining the Role of B Cells in Atherosclerosis
Perry, H. M., & McNamara, C. A. (2012) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.112.249235 · Cited by 14 · see citing works
Addressing the complexity of cardiovascular disease by design
Lotta, L. A., & Peyvandi, F. (2011) · The Lancet · doi:10.1016/s0140-6736(10)62240-4 · Cited by 10 · see citing works
Sage, A. P., Harrison, J. E., Baker, L. A., Masters, L. M., Tsiantoulas, D., Binder, C. J., & Mallat, Z. (2011) · Circulation · doi:10.1161/circ.124.suppl_21.a9224 · Cited by 1 · see citing works
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Multi-omics approaches to disease
Hasin, Y., Seldin, M., & Lusis, A. (2017) · Genome Biology · doi:10.1186/s13059-017-1215-1 · Cited by 2,953 · see citing works
Johnson, E. C. B., Dammer, E. B., Duong, D. M., Ping, L., Zhou, M., Yin, L., Higginbotham, L. A., Guajardo, A., White, B., Troncoso, J. C., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0815-6 · Cited by 1,001 · see citing works
Self-citationSystems genetics approaches to understand complex traits
Civelek, M., & Lusis, A. J. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3575 · Cited by 621 · see citing works
Seyfried, N. T., Dammer, E. B., Swarup, V., Nandakumar, D., Duong, D. M., Yin, L., Deng, Q., Nguyen, T., Hales, C. M., Wingo, T., et al. (2017) · Cell Systems · doi:10.1016/j.cels.2016.11.006 · Cited by 477 · see citing works
Tsao, C. W., & Vasan, R. S. (2015) · International Journal of Epidemiology · doi:10.1093/ije/dyv337 · Cited by 457 · see citing works
Systems biology in cardiovascular disease: a multiomics approach
Joshi, A., Rienks, M., Theofilatos, K., & Mayr, M. (2020) · Nature Reviews Cardiology · doi:10.1038/s41569-020-00477-1 · Cited by 305 · see citing works
The role of B cells in atherosclerosis
Sage, A. P., Tsiantoulas, D., Binder, C. J., & Mallat, Z. (2019) · Nature Reviews Cardiology · doi:10.1038/s41569-018-0106-9 · Cited by 298 · see citing works
B Cells and Humoral Immunity in Atherosclerosis
Tsiantoulas, D., Diehl, C. J., Witztum, J. L., & Binder, C. J. (2014) · Circulation Research · doi:10.1161/circresaha.113.301145 · Cited by 297 · see citing works
Johnson, E. C. B., Dammer, E. B., Duong, D. M., Yin, L., Thambisetty, M., Troncoso, J. C., Lah, J. J., Levey, A. I., & Seyfried, N. T. (2018) · Molecular Neurodegeneration · doi:10.1186/s13024-018-0282-4 · Cited by 225 · see citing works
Macrophage Trafficking, Inflammatory Resolution, and Genomics in Atherosclerosis
Moore, K. J., Koplev, S., Fisher, E. A. A., Tabas, I. A., Björkegren, J., Doran, A. C., & Kovacic, J. C. (2018) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2018.08.2147 · Cited by 221 · see citing works
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Mäkinen, V.-P., Civelek, M., Meng, Q., Zhang, B., Zhu, J., Levian, C., Huan, T., Segrè, A. V., Ghosh, S., Vivar, J., et al. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004502 · Cited by 196 · see citing works
Self-citationWang, M., Li, A., Sekiya, M., Beckmann, N. D., Quan, X., Schrode, N., Fernando, M. B., Yu, A., Zhu, L., Cao, J., et al. (2021) · Neuron · doi:10.1016/j.neuron.2020.11.002 · Cited by 185 · see citing works
Self-citationKessler, T., Vilne, B., & Schunkert, H. (2016) · EMBO Molecular Medicine · doi:10.15252/emmm.201506174 · Cited by 172 · see citing works
Self-citationThe role of T and B cells in human atherosclerosis and atherothrombosis
Ammirati, E., Moroni, F., Magnoni, M., & Camici, P. G. (2014) · Clinical & Experimental Immunology · doi:10.1111/cei.12477 · Cited by 157 · see citing works
Shu, L., Zhao, Y., Kurt, Z., Byars, S., Tukiainen, T., Kettunen, J., Orozco, L. D., Pellegrini, M. A., Lusis, A. J., Ripatti, S., et al. (2016) · BMC Genomics · doi:10.1186/s12864-016-3198-9 · Cited by 129 · see citing works
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Chen, H., Tas, S. W., & de Winther, M. P. J. (2019) · The Journal of Experimental Medicine · doi:10.1084/jem.20190459 · Cited by 121 · see citing works
Meng, Q., Zhuang, Y., Ying, Z., Agrawal, R., Yang, X., & Gómez‐Pinilla, F. (2017) · EBioMedicine · doi:10.1016/j.ebiom.2017.01.046 · Cited by 117 · see citing works
Self-citationTargeting B Cells in Atherosclerosis
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Alizadehsani, R., Khosravi, A., Roshanzamir, M., Abdar, M., Sarrafzadegan, N., Shafie, D., Khozeimeh, F., Shoeibi, A., Nahavandi, S., Panahiazar, M., et al. (2020) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2020.104095 · Cited by 117 · see citing works
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Niu, X., Zhang, J., Zhang, L., Hou, Y., Pu, S., Chu, A., Bai, M., & Zhang, Z. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.01214 · Cited by 106 · see citing works
Morrow, J. D., Zhou, X., Lao, T., Jiang, Z., DeMeo, D. L., Cho, M. H., Qiu, W., Cloonan, S. M., Pinto-Plata, V., Celli, B., et al. (2017) · Scientific Reports · doi:10.1038/srep44232 · Cited by 104 · see citing works
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Huan, T., Meng, Q., Saleh, M. A., Norlander, A. E., Joehanes, R., Zhu, J., Chen, B. H., Zhang, B., Johnson, A. D., Ying, S., et al. (2015) · Molecular Systems Biology · doi:10.15252/msb.20145399 · Cited by 104 · see citing works
Self-citationDing, Y., Qian, L.-Y., Pang, J., Lin, J., Xu, Q., Wang, L., Huang, D., & Zou, H. (2017) · Oncotarget · doi:10.18632/oncotarget.18346 · Cited by 103 · see citing works
Pattarabanjird, T., Li, C., & McNamara, C. A. (2021) · JACC Basic to Translational Science · doi:10.1016/j.jacbts.2021.01.006 · Cited by 99 · see citing works
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Humoral immunity in atherosclerosis and myocardial infarction: from B cells to antibodies
Porsch, F., Mallat, Z., & Binder, C. J. (2021) · Cardiovascular Research · doi:10.1093/cvr/cvab285 · Cited by 86 · see citing works
B Cell–Activating Factor Neutralization Aggravates Atherosclerosis
Tsiantoulas, D., Sage, A. P., Göderle, L., Ozsvár-Kozma, M., Murphy, D., Porsch, F., Pasterkamp, G., Menche, J., Schneider, P., Mallat, Z., et al. (2018) · Circulation · doi:10.1161/circulationaha.117.032790 · Cited by 83 · see citing works
Ahn, R. S., Gupta, R., Lai, K., Chopra, N., Arron, S. T., & Liao, W. J. (2016) · BMC Genomics · doi:10.1186/s12864-016-3188-y · Cited by 76 · see citing works
Tizioto, P. C., Kim, J., Seabury, C. M., Schnabel, R. D., Gershwin, L. J., Eenennaam, A. L. V., Toaff-Rosenstein, R. L., Neibergs, H. L., & Taylor, J. F. (2015) · PLoS ONE · doi:10.1371/journal.pone.0131459 · Cited by 72 · see citing works
Srikakulapu, P., & McNamara, C. A. (2017) · American Journal of Physiology-Heart and Circulatory Physiology · doi:10.1152/ajpheart.00859.2016 · Cited by 72 · see citing works
Molecular and genetic inflammation networks in major human diseases
Zhao, Y., Forst, C. V., Sayegh, C. E., Wang, I., Yang, X., & Zhang, B. (2016) · Molecular BioSystems · doi:10.1039/c6mb00240d · Cited by 71 · see citing works
Self-citationWillinger, C. M., Rong, J., Tanrıverdi, K., Courchesne, P. L., Huan, T., Wasserman, G. A., Lin, H., Dupuis, J., Joehanes, R., Jones, M. R., et al. (2017) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.116.001678 · Cited by 69 · see citing works
Self-citationRosenthal, S. B., Bush, K. T., & Nigám, S. K. (2019) · Scientific Reports · doi:10.1038/s41598-019-47798-x · Cited by 69 · see citing works
Network-Based Identification and Prioritization of Key Regulators of Coronary Artery Disease Loci
Zhao, Y., Chen, J., Freudenberg, J., Meng, Q., Rajpal, D. K., & Yang, X. (2016) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.115.306725 · Cited by 65 · see citing works
Self-citationChistiakov, D. A., Orekhov, A. N., & Bobryshev, Y. V. (2016) · Immunobiology · doi:10.1016/j.imbio.2016.05.010 · Cited by 65 · see citing works
Contributions of the Framingham Heart Study to the Epidemiology of Coronary Heart Disease
Chen, G., & Levy, D. A. (2016) · JAMA Cardiology · doi:10.1001/jamacardio.2016.2050 · Cited by 64 · see citing works
Self-citationWesterlund, A. M., Hawe, J. S., Heinig, M., & Schunkert, H. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms221910291 · Cited by 61 · see citing works
Self-citationThe why and how of adaptive immune responses in ischemic cardiovascular disease
Mallat, Z., & Binder, C. J. (2022) · Nature Cardiovascular Research · doi:10.1038/s44161-022-00049-1 · Cited by 61 · see citing works
Perry, H. M., Oldham, S. N., Fahl, S. P., Que, X., Gonen, A., Harmon, D. B., Tsimikas, S., Witztum, J. L., Bender, T. P., & McNamara, C. A. (2013) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.113.302571 · Cited by 57 · see citing works
Dissecting the Roles of MicroRNAs in Coronary Heart Disease via Integrative Genomic Analyses
Huan, T., Rong, J., Tanrıverdi, K., Meng, Q., Bhattacharya, A., McManus, D. D., Joehanes, R., Assimes, T. L., McPherson, R., Samani, N. J., et al. (2015) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.114.305176 · Cited by 56 · see citing works
Self-citationThe Adipokine-Cardiovascular-Lifestyle Network
Mechanick, J. I., Zhao, S., & Garvey, W. T. (2016) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2016.06.072 · Cited by 55 · see citing works
Infante, T., Viscovo, L. D., Rimini, M. L. D., Padula, S., Caso, P., & Claudio Napoli, A. (2019) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.52407 · Cited by 56 · see citing works
Gijsberts, C. M., Ellenbroek, G. H. J. M., ten Berg, M. J., Huisman, A., van Solinge, W. W., Lam, C. S. P., Asselbergs, F. W., den Ruijter, H. M., Pasterkamp, G., Hoefer, I. E., et al. (2017) · The American Journal of Cardiology · doi:10.1016/j.amjcard.2017.06.020 · Cited by 53 · see citing works
The Contribution of Autoantibodies to Inflammatory Cardiovascular Pathology
Meier, L. A., & Binstadt, B. A. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.00911 · Cited by 51 · see citing works
Maas, S. C. E., Mens, M. M. J., Kühnel, B., van Meurs, J. B. J., Uitterlinden, A. G., Peters, A., Prokisch, H., Herder, C., Grallert, H., Kunze, S., et al. (2020) · Clinical Epigenetics · doi:10.1186/s13148-020-00951-0 · Cited by 51 · see citing works
Revealing Pathway Dynamics in Heart Diseases by Analyzing Multiple Differential Networks
Ma, X., Gao, L., Karamanlidis, G., Gao, P., Lee, C. F., Garcia‐Menendez, L., Tian, R., & Tan, K. (2015) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004332 · Cited by 49 · see citing works
Singh, A., Babyak, M. A., Nolan, D. K., Brummett, B. H., Jiang, R., Siegler, I. C., Kraus, W. E., Shah, S. H., Williams, R. B., & Hauser, E. R. (2014) · European Journal of Human Genetics · doi:10.1038/ejhg.2014.189 · Cited by 49 · see citing works
Transcriptome of blood cells as a reservoir of cardiovascular biomarkers
Devaux, Y. (2016) · Biochimica et Biophysica Acta (BBA) - Molecular Cell Research · doi:10.1016/j.bbamcr.2016.11.005 · Cited by 49 · see citing works
A genetic basis for coronary artery disease
Roberts, R. (2014) · Trends in Cardiovascular Medicine · doi:10.1016/j.tcm.2014.10.008 · Cited by 48 · see citing works
Multiple potential roles for B cells in atherosclerosis
Sage, A. P., & Mallat, Z. (2014) · Annals of Medicine · doi:10.3109/07853890.2014.900272 · Cited by 47 · see citing works
EPRS is a critical regulator of cell proliferation and estrogen signaling in ER+ breast cancer
Katsyv, I., Wang, M., Song, W. M., Zhou, X., Zhao, Y., Park, S., Zhu, J., Zhang, B., & Irie, H. Y. (2016) · Oncotarget · doi:10.18632/oncotarget.11870 · Cited by 47 · see citing works
Self-citationMulti-omics integration reveals molecular networks and regulators of psoriasis
Zhao, Y., Jhamb, D., Shu, L., Arneson, D. V., Rajpal, D. K., & Yang, X. (2019) · BMC Systems Biology · doi:10.1186/s12918-018-0671-x · Cited by 45 · see citing works
Self-citationMessenger RNA and MicroRNA transcriptomic signatures of cardiometabolic risk factors
McManus, D. D., Rong, J., Huan, T., Lacey, S., Tanrıverdi, K., Munson, P. J., Larson, M. G., Joehanes, R., Murthy, V. L., Shah, R. V., et al. (2017) · BMC Genomics · doi:10.1186/s12864-017-3533-9 · Cited by 42 · see citing works
Self-citationGenetics and Genomics of Coronary Artery Disease
Pjanic, M., Miller, C. L., Wirka, R. C., Kim, J. B., DiRenzo, D. M., & Quertermous, T. (2016) · Current Cardiology Reports · doi:10.1007/s11886-016-0777-y · Cited by 40 · see citing works
Genetics of Coronary Artery Disease: An Update
Roberts, R. (2014) · Methodist DeBakey Cardiovascular Journal · doi:10.14797/mdcj-10-1-7 · Cited by 39 · see citing works
Lorenzon, R., Mariotti‐Ferrandiz, E., Aheng, C., Ribet, C., Toumi, F., Pitoiset, F., Chaara, W., Dérian, N., Johanet, C., Drakos, I., et al. (2018) · BMJ Open · doi:10.1136/bmjopen-2017-021037 · Cited by 39 · see citing works
Markin, A. M., Sobenin, I. A., Grechko, A. V., Zhang, D., & Orekhov, A. N. (2020) · Frontiers in Pharmacology · doi:10.3389/fphar.2020.00642 · Cited by 39 · see citing works
CD200 Limits Monopoiesis and Monocyte Recruitment in Atherosclerosis
Kassiteridi, C., Cole, J. E., Griseri, T., Falck-Hansen, M., Goddard, M. E., Seneviratne, A. N., Green, P. A., Park, I., Shami, A., Pattarabanjird, T., et al. (2021) · Circulation Research · doi:10.1161/circresaha.119.316062 · Cited by 37 · see citing works
Cordero, P., Parikh, V. N., Chin, E. T., Erbilgin, A., Gloudemans, M. J., Shang, C., Huang, Y., Chang, A. C. Y., Smith, K. S., Dewey, F. E., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-10591-5 · Cited by 36 · see citing works
Network analysis: a new approach to study endocrine disorders
Stevens, A., Leonibus, C. D., Hanson, D., Dowsey, A. W., Whatmore, A. J., Meyer, S., Donn, R. P., Chatelain, P., Banerjee, I., Cosgrove, K. E., et al. (2013) · Journal of Molecular Endocrinology · doi:10.1530/jme-13-0112 · Cited by 37 · see citing works
Network Modeling Approaches and Applications to Unravelling Non-Alcoholic Fatty Liver Disease
Blencowe, M., Karunanayake, T., Wier, J. R., Hsu, N., & Yang, X. (2019) · Genes · doi:10.3390/genes10120966 · Cited by 35 · see citing works
Self-citationYang, H., Arif, M., Yuan, M., Li, X., Shong, K. E., Türkez, H., Nielsen, J., Uhlén, M., Borén, J., Zhang, C., et al. (2021) · iScience · doi:10.1016/j.isci.2021.103222 · Cited by 33 · see citing works
Multidimensional Integrative Genomics Approaches to Dissecting Cardiovascular Disease
Arneson, D. V., Shu, L., Tsai, B. L., Barrere‐Cain, R., Sun, C., & Yang, X. (2017) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2017.00008 · Cited by 34 · see citing works
Self-citationKurowski, B. G., Treble‐Barna, A., Pitzer, A. J., Wade, S. L., Martin, L. J., Chima, R. S., & Jegga, A. G. (2017) · Journal of Neurotrauma · doi:10.1089/neu.2016.4856 · Cited by 32 · see citing works
Mangge, H., Prüller, F., Schnedl, W. J., Renner, W., & Almer, G. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21114082 · Cited by 33 · see citing works
Biswas, M., Suvarna, R., Vimal Krishnan, S., Devasia, T., Belle, V. S., & Prabhu, K. (2022) · F1000Research · doi:10.12688/f1000research.123245.1 · Cited by 31 · see citing works
Das, S. K., Sharma, N., & Zhang, B. (2015) · BMC Medical Genomics · doi:10.1186/s12920-015-0078-0 · Cited by 31 · see citing works
Self-citationRNA sequencing of blood in coronary artery disease: involvement of regulatory T cell imbalance
McCaffrey, T. A., Toma, I., Yang, Z., Katz, R. J., Reiner, J. S., Mazhari, R., Shah, P. M., Tackett, M., Jones, D. R., Jepson, T., et al. (2021) · BMC Medical Genomics · doi:10.1186/s12920-021-01062-2 · Cited by 29 · see citing works
Opportunities for an atherosclerosis vaccine: From mice to humans
Roy, P., Ali, A. J., Kobiyama, K., Ghosheh, Y., & Ley, K. F. (2020) · Vaccine · doi:10.1016/j.vaccine.2019.12.039 · Cited by 29 · see citing works
Understanding the Role of B cells in Atherosclerosis: Potential Clinical Implications
Morris-Rosenfeld, S., Lipinski, M., & McNamara, C. (2013) · Expert Review of Clinical Immunology · doi:10.1586/1744666x.2014.857602 · Cited by 26 · see citing works
Towards a Molecular Systems Model of Coronary Artery Disease
Abraham, G., Bhalala, O. G., de Bakker, P. I. W., Ripatti, S., & Inouye, M. (2014) · Current Cardiology Reports · doi:10.1007/s11886-014-0488-1 · Cited by 27 · see citing works
B-cells in pulmonary arterial hypertension: friend, foe or bystander?
Sanges, S., Tian, W., Dubucquoi, S., Chang, J., Collet, A., Launay, D., & Nicolls, M. R. (2024) · European Respiratory Journal · doi:10.1183/13993003.01949-2023 · Cited by 26 · see citing works
Veras, P. S. T., Ramos, P. I. P., & de Menezes, J. P. B. (2018) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2018.00326 · Cited by 26 · see citing works
Intimal pericytes as the second line of immune defence in atherosclerosis
Ivanova, E. A. (2015) · World Journal of Cardiology · doi:10.4330/wjc.v7.i10.583 · Cited by 26 · see citing works
Gupta, A., Slater, J., Boyne, D. J., Mitsakakis, N., Béliveau, A., Drużdżel, M. J., Brenner, D. R., Hussain, S., & Arora, P. (2019) · Medical Decision Making · doi:10.1177/0272989x19879095 · Cited by 25 · see citing works
Serum proteomics reveals disorder of lipoprotein metabolism in sepsis
Liang, X., Wu, T., Chen, Q., Jiang, J., Jiang, Y., Ruan, Y., Zhang, H., Zhang, S., Zhang, C., Chen, P., et al. (2021) · Life Science Alliance · doi:10.26508/lsa.202101091 · Cited by 25 · see citing works
Readapting the adaptive immune response – therapeutic strategies for atherosclerosis
Sage, A. P., & Mallat, Z. (2017) · British Journal of Pharmacology · doi:10.1111/bph.13700 · Cited by 24 · see citing works
Adaptive Immune Responses in Human Atherosclerosis
Lee, S., Bartlett, B., & Dwivedi, G. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21239322 · Cited by 25 · see citing works
A systematic heritability analysis of the human whole blood transcriptome
Huan, T., Liu, C., Joehanes, R., Zhang, X., Chen, B. H., Johnson, A. D., Yao, C., Courchesne, P. L., O’Donnell, C. J., Munson, P. J., et al. (2015) · Human Genetics · doi:10.1007/s00439-014-1524-3 · Cited by 24 · see citing works
Self-citationSystems pharmacology modeling: an approach to improving drug safety
Bai, J. P. F., Fontana, R. J., Price, N. D., & Sangar, V. (2013) · Biopharmaceutics & Drug Disposition · doi:10.1002/bdd.1871 · Cited by 24 · see citing works
Whole blood microRNA expression associated with stroke: Results from the Framingham Heart Study
Salinas, J., Lin, H., Aparicio, H. J., Huan, T., Liu, C., Rong, J., Beiser, A., Himali, J. J., Freedman, J. E., Larson, M. G., et al. (2019) · PLoS ONE · doi:10.1371/journal.pone.0219261 · Cited by 23 · see citing works
Self-citationAnti-inflammatory and Immunomodulatory Therapies in Atherosclerosis
Deroissart, J., Porsch, F., Köller, T., & Binder, C. J. (2021) · Handbook of experimental pharmacology · doi:10.1007/164_2021_505 · Cited by 22 · see citing works
Precision Medicine Approaches to Vascular Disease
Miller, C. L., Kontorovich, A., Hao, K., Ma, L., Iyegbe, C. O., Björkegren, J., & Kovacic, J. C. (2021) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2021.04.001 · Cited by 22 · see citing works
2019 Russell Ross Memorial Lecture in Vascular Biology
Upadhye, A., Sturek, J. M., & McNamara, C. A. (2019) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.119.313064 · Cited by 21 · see citing works
Multiomics on Mental Stress-Induced Myocardial Ischemia: A Narrative Review
Jin, N., Cheng, L., & Geng, Q. (2024) · Heart and Mind · doi:10.4103/hm.hm-d-23-00021 · Cited by 19 · see citing works
Plan B (-cell) in atherosclerosis
Nus, M., Tsiantoulas, D., & Mallat, Z. (2017) · European Journal of Pharmacology · doi:10.1016/j.ejphar.2017.09.002 · Cited by 19 · see citing works
Network-based association of hypoxia-responsive genes with cardiovascular diseases
Wang, R., Oldham, W. M., & Loscalzo, J. (2014) · New Journal of Physics · doi:10.1088/1367-2630/16/10/105014 · Cited by 19 · see citing works
Self-citationBartoloni, E., Cacciapaglia, F., Erre, G. L., Gremese, E., Manfredi, A., Piga, M., Sakellariou, G., Spinelli, F. R., Viapiana, O., & Atzeni, F. (2025) · Autoimmunity Reviews · doi:10.1016/j.autrev.2025.103760 · Cited by 18 · see citing works
Genetics of Arterial-Wall-Specific Mechanisms in Atherosclerosis: Focus on Mitochondrial Mutations
Orekhov, A. N., Ivanova, E. A., Markin, A. M., Nikiforov, N. G., & Sobenin, I. A. (2020) · Current Atherosclerosis Reports · doi:10.1007/s11883-020-00873-5 · Cited by 18 · see citing works
Liu, M., Xu, Y., Song, Y. Q., Fan, D., Li, J., Zhang, Z., Wang, L., He, J., Chen, C., & Ma, C. (2025) · Advanced Science · doi:10.1002/advs.202415106 · Cited by 17 · see citing works
The Spectrum of B Cell Functions in Atherosclerotic Cardiovascular Disease
Smeets, D., Gisterå, A., Malin, S., & Tsiantoulas, D. (2022) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2022.864602 · Cited by 17 · see citing works
Connections for Matters of the Heart: Network Medicine in Cardiovascular Diseases
Sonawane, A. R., Aïkawa, E., & Aikawa, M. (2022) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2022.873582 · Cited by 17 · see citing works
Malinowski, D., Bochniak, O., Luterek-Puszyńska, K., Puszyński, M., & Pawlik, A. (2023) · Genes · doi:10.3390/genes14071425 · Cited by 21 · see citing works
Vascular Inflammation in Cardiovascular Disease: Is Immune System Protective or Bystander?
Muhammad, K., Ayoub, M. A., & Iratni, R. (2021) · Current Pharmaceutical Design · doi:10.2174/1381612827666210118121952 · Cited by 16 · see citing works
Rincón-Arévalo, H., Quintero, J. C., Fortich, F., Rojas, M., Vásquez, G. M., Castaño, D., & Yassin, L. M. (2020) · Heliyon · doi:10.1016/j.heliyon.2020.e03441 · Cited by 14 · see citing works
- Authors
- Huan, T., Zhang, B., Wang, Z., Joehanes, R., Zhu, J., Johnson, A. D., Ying, S., Munson, P. J., Raghavachari, N., Wang, R., Liu, P., Courchesne, P., Hwang, S.-J., Assimes, T. L., McPherson, R., Samani, N. J., Schunkert, H., Coronary ARteryDIsease Genome wide Replication and Meta-analysis (CARDIoGRAM) Consortium, I. C. F. B. P. G. (., Meng, Q., Suver, C., O’Donnell, C. J., Derry, J., Yang, X., & Levy, D.
- Affiliations
- National Heart, Lung, and Blood Institute (US)
- ORCID
- Venue
- Arteriosclerosis, Thrombosis, and Vascular Biology
- Published
- 2013-06
- Volume
- 33
- Issue
- 6
- Pages
- 1427-1434
- ISSN
- 1079-5642 (ISSN-L)
- 1524-4636
- PMC
- PMC3752786
- OpenAlex
- W2169785917
- Cited by
- 167
- References
- 52
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 10 · 2023: 10 · 2022: 8 · 2021: 16 · 2020: 14 · 2019: 16 · 2018: 11 · 2017: 24 · 2016: 18 · 2015: 15 · 2014: 14 · 2013: 7
- FWCI
- 8.06
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Arteriosclerosis Thrombosis and Vascular Biology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (submittedVersion)
- Funders
- National Institute for Health and Care Research (NF-SI-0611-10170)
- British Heart Foundation
- National Institutes of Health (n01hc25195-41-0-1)
- National Heart, Lung, and Blood Institute (N01‐HC25195, Z01HL006001, N01-HC-025195, ZIAHL006001)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Immunology and Microbiology › Immunology › Atherosclerosis and Cardiovascular Diseases
- Keywords
- coronary artery disease, gene co-expression network, differential modules, whole blood gene expression, single nucleotide polymorphisms, B cell activation, immune response, ion transport, Spi-B, TNFRSF13C, EBF1, protein-protein interaction network, Bayesian networks
- MeSH terms
- Aged, Bayes Theorem, Coronary Artery Disease, Female, Gene Expression Regulation, Humans, Male, Middle Aged, Reference Values, Genetic Variation, Incidence, Case-Control Studies, Age Distribution, Sex Distribution, Risk Assessment, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Systems Biology, Gene Regulatory Networks, Genome-Wide Association Study
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