The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Toll-Like Receptor-2 Mediates Inflammation and Matrix Degradation in Human Atherosclerosis
Open accessAbstract
Background— Inflammation and matrix degradation are the hallmarks of high-risk atherosclerosis that leads to myocardial infarction and stroke. Toll-like receptors (TLRs), key players in innate immunity, are upregulated in atherosclerotic lesions, but their functional role in human atherosclerosis is unknown. We explored the effects of blocking TLR-2, TLR-4, and myeloid differentiation primary response gene 88 (MyD88), a signaling adaptor shared by most TLRs and interleukin-1 receptor (IL-1R), in an in vitro model of human atherosclerosis. Methods and Results— Carotid endarterectomies were obtained from patients with symptomatic carotid disease. Cells were isolated via enzymatic tissue dissociation and cultured in the presence or absence of TLR signaling blockers. A dominant-negative form of MyD88 (MyD88 DN ) decreased the production of monocyte chemotactic protein-1/CCL2 ( P =0.000), IL-8/CXCL8 ( P =0.006), IL-6 ( P =0.002), matrix metalloproteinase-1 (MMP-1; P =0.002), and MMP-3 ( P =0.000), as well as nuclear factor-κB activation ( P <0.05) in atheroma cell cultures. IL-1R antagonist, TLR-4 blocking antibodies, or overexpression of a dominant-negative form of the TLR-4 signaling adaptor TRIF-related adaptor molecule reduced nuclear factor-κB activity but did not have a broad impact on the production of the mediators studied. In contrast, TLR-2 neutralizing antibodies inhibited nuclear factor-κB activation ( P <0.05) and significantly reduced monocyte chemotactic protein-1/CCL2 ( P =0.000), IL-8/CXCL8 ( P =0.009), IL-6 ( P =0.000), and MMP-1 ( P =0.000), MMP-2 ( P =0.004), MMP-3 ( P =0.000), and MMP-9 ( P =0.006) production. Conclusions— Our data indicate that TLR-2 signaling through MyD88 plays a predominant role in inflammation and matrix degradation in human atherosclerosis. TLR-2 blockade may represent a therapeutic strategy for atherosclerosis and its complications.
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Cites
Inflammation, Atherosclerosis, and Coronary Artery Disease
Hansson, G. K. (2005) · New England Journal of Medicine · doi:10.1056/nejmra043430 · Cited by 8,773
The family of five: TIR-domain-containing adaptors in Toll-like receptor signalling
O'Neill, L. A. J., & Bowie, A. G. (2007) · Nature Reviews Immunology · doi:10.1038/nri2079 · Cited by 2,667
Regulation of lung injury and repair by Toll-like receptors and hyaluronan
Jiang, D., Liang, J., Fan, J., Yu, S., Chen, S., Luo, Y., Prestwich, G. D., Mascarenhas, M. M., Garg, H. G., Quinn, D. A., et al. (2005) · Nature Medicine · doi:10.1038/nm1315 · Cited by 1,401
Michelsen, K. S., Wong, M. H., Shah, P. K., Zhang, W., Yano, J., Doherty, T. M., Akira, S., Rajavashisth, T. B., & Arditi, M. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0403249101 · Cited by 1,019
Schaefer, L., Babelova, A., Kiss, E., Hausser, H.-J., Baliova, M., Krzyzankova, M., Marsche, G., Young, M. F., Mihalik, D., Götte, M., et al. (2005) · Journal of Clinical Investigation · doi:10.1172/jci23755 · Cited by 850
Björkbacka, H., Kunjathoor, V. V., Moore, K. J., Koehn, S., Ordija, C. M., Lee, M. A., Means, T., Halmen, K., Luster, A. D., Golenbock, D. T., et al. (2004) · Nature Medicine · doi:10.1038/nm1008 · Cited by 634
Modulation of atherosclerosis in mice by Toll-like receptor 2
Mullick, A. E. (2005) · Journal of Clinical Investigation · doi:10.1172/jci25482 · Cited by 549
Translating molecular discoveries into new therapies for atherosclerosis
Rader, D. J., & Daugherty, A. (2008) · Nature · doi:10.1038/nature06796 · Cited by 515
Cutting Edge: TLR2 Is a Functional Receptor for Acute-Phase Serum Amyloid A
Cheng, N., He, R., Tian, J., Ye, P. P., & Ye, R. D. (2008) · The Journal of Immunology · doi:10.4049/jimmunol.181.1.22 · Cited by 284
Cited by
Cholesterol, inflammation and innate immunity.
Tall, A. R., & Yvan-Charvet, L. (2015) · Nature Reviews Immunology · doi:10.1038/nri3793 · Cited by 1,479
Inflammation and atherosclerosis: signaling pathways and therapeutic intervention
Kong, P., Cui, Z.-Y., Huang, X.-F., Zhang, D.-D., Guo, R.-J., & Han, M. (2022) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-022-00955-7 · Cited by 1,183
Microanatomy of the Human Atherosclerotic Plaque by Single-Cell Transcriptomics
Depuydt, M. A. C., Prange, K. H. M., Slenders, L., Örd, T., Elbersen, D., Boltjes, A., de Jager, S. C. A., Asselbergs, F. W., de Borst, G. J., Aavik, E., et al. (2020) · Circulation Research · doi:10.1161/circresaha.120.316770 · Cited by 594
Stroke and the immune system: from pathophysiology to new therapeutic strategies
Macrez, R., Ali, C., Toutirais, O., Le Mauff, B., Defer, G., Dirnagl, U., & Vivien, D. (2011) · The Lancet Neurology · doi:10.1016/s1474-4422(11)70066-7 · Cited by 560
Seimon, T. A., Nadolski, M. J., Liao, X., Magallon, J., Nguyen, M., Feric, N. T., Koschinsky, M. L., Harkewicz, R., Witztum, J. L., Tsimikas, S., et al. (2010) · Cell Metabolism · doi:10.1016/j.cmet.2010.09.010 · Cited by 457
Metadata
- Authors
- Monaco, C., Gregan, S. M., Navin, T. J., Foxwell, B. M. J., Davies, A. H., & Feldmann, M.
- Venue
- Circulation
- Published
- 2009-12-15
- Volume
- 120
- Issue
- 24
- Pages
- 2462-2469
- ISSN
- 0009-7322 (ISSN-L)
- 1524-4539
- OpenAlex
- W2120272302
- Cited by
- 162
- References
- 9
- FWCI
- 6.49
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Monaco, C., Gregan, S. M., Navin, T. J., Foxwell, B. M. J., Davies, A. H., & Feldmann, M. (2009). Toll-Like Receptor-2 Mediates Inflammation and Matrix Degradation in Human Atherosclerosis. Circulation. https://doi.org/10.1161/circulationaha.109.851881
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