The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Cytokine and Cytokine-Like Inflammation Markers, Endothelial Dysfunction, and Imbalanced Coagulation in Development of Diabetes and Its Complications
Abstract
CONTEXT: Recent developments indicate that pathophysiological mechanisms leading to beta-cell damage, insulin resistance, and the vascular complications of diabetes include an activation of the inflammation cascade, endothelial dysfunction, and procoagulant imbalance. Their circulating biomarkers may therefore provide opportunities for early diagnosis and targets for novel treatments. EVIDENCE: Circulating biomarkers of these pathways such as TNFalpha, IL-6, C-reactive protein (CRP) (inflammation), vascular cellular adhesion molecule-1, interstitial cellular adhesion molecule-1, E-selectin, von Willebrand factor (endothelial dysfunction), plasminogen activator inhibitor-1, fibrinogen, P-selectin (procoagulant state), and adiponectin (antiinflammation) may be associated with development of both type 1 and type 2 diabetes and some studies, particularly in type 2 diabetes, have demonstrated that certain biomarkers may have independent predictive value. Similarly studies have shown that these biomarkers may be associated with development of diabetic nephropathy and retinopathy, and again, particularly in type 2 diabetes, with cardiovascular events as well. Finally, the comorbidities of diabetes, namely obesity, insulin resistance, hyperglycemia, hypertension and dyslipidemia collectively aggravate these processes while antihyperglycemic interventions tend to ameliorate them. CONCLUSIONS: Increased CRP, IL-6, and TNFalpha, and especially interstitial cellular adhesion molecule-1, vascular cellular adhesion molecule-1, and E-selectin are associated with nephropathy, retinopathy, and cardiovascular disease in both type 1 and type 2 diabetes. Whereas further work is needed, it seems clear that these biomarkers are predictors of increasing morbidity in prediabetic and diabetic subjects and should be the focus of work testing their clinical utility to identify high-risk individuals as well as perhaps to target interventions.
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Citations
Cites
Inflammation in atherosclerosis
Libby, P. (2002) · Nature · doi:10.1038/nature01323 · Cited by 8,315
Inflammation and insulin resistance
Shoelson, S. E. (2006) · Journal of Clinical Investigation · doi:10.1172/jci29069 · Cited by 4,769
The adipocyte-secreted protein Acrp30 enhances hepatic insulin action
Berg, A. H., Combs, T. P., Du, X., Brownlee, M., & Scherer, P. E. (2001) · Nature Medicine · doi:10.1038/90992 · Cited by 2,526
Yudkin, J. S., Stehouwer, C. D. A., Emeis, J. J., & Coppack, S. W. (1999) · Arteriosclerosis, Thrombosis, and Vascular Biology · doi:10.1161/01.atv.19.4.972 · Cited by 2,465
Inflammation: the link between insulin resistance, obesity and diabetes
Dandona, P. (2004) · Trends in Immunology · doi:10.1016/j.it.2003.10.013 · Cited by 2,170
The Finnish Diabetes Prevention Study (DPS)
Lindström, J., Louheranta, A., Mannelin, M., Rastas, M., Salminen, V., Eriksson, J., Uusitupa, M., Tuomilehto, J., & for the Finnish Diabetes Prevention Study Group (2003) · Diabetes Care · doi:10.2337/diacare.26.12.3230 · Cited by 1,848
Ceriello, A., & Motz, E. (2004) · Arteriosclerosis, Thrombosis, and Vascular Biology · doi:10.1161/01.atv.0000122852.22604.78 · Cited by 1,378
Retinol-Binding Protein 4 and Insulin Resistance in Lean, Obese, and Diabetic Subjects
Graham, T. E., Yang, Q., Blüher, M., Hammarstedt, A., Ciaraldi, T. P., Henry, R. R., Wason, C. J., Oberbach, A., Jansson, P.-A., Smith, U., et al. (2006) · New England Journal of Medicine · doi:10.1056/nejmoa054862 · Cited by 1,319
Suganami, T., Nishida, J., & Ogawa, Y. (2005) · Arteriosclerosis, Thrombosis, and Vascular Biology · doi:10.1161/01.atv.0000183883.72263.13 · Cited by 1,056 · cited 1×
“Adipose tissue from obese individuals contains activated macrophages that together with adipocytes produce inflammatory adipokines such as MCP-1, MIF, TNF , IL-6, procoagulant substances such as PAI-1, vasculoactive substances such as angiotensinogen and endothelin, and molecules that may contribute to insulin resista…”
BackgroundZiccardi, P., Nappo, F., Giugliano, G., Esposito, K., Marfella, R., Cioffi, M., D’Andrea, F., Molinari, A. M., & Giugliano, D. (2002) · Circulation · doi:10.1161/hc0702.104279 · Cited by 994
Cited by
Pathophysiology of type 2 diabetes mellitus
Galicia-Garcia, U., Benito-Vicente, A., Jebari, S., Larrea-Sebal, A., Siddiqi, H., Uribe, K. B., Ostolaza, H., & Martín, C. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21176275 · Cited by 3,360
“This balance is altered in T2DM leading to alteration of the physicochemical properties of the vascular wall via endothelial dysfunction, oxidative stress, platelet hyperreactivity, and inflammation [240,241].”
BackgroundOxidative stress, insulin signaling, and diabetes
Rains, J. L., & Jain, S. K. (2011) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2010.12.006 · Cited by 1,435
Molecular Mechanisms Linking Oxidative Stress and Diabetes Mellitus
Yaribeygi, H., Sathyapalan, T., Atkin, S. L., & Sahebkar, A. (2020) · Oxidative Medicine and Cellular Longevity · doi:10.1155/2020/8609213 · Cited by 685
Obesity, Inflammation, and Cardiovascular Risk
Mathieu, P., Lemieux, I., & Després, J.-P. (2010) · Clinical Pharmacology & Therapeutics · doi:10.1038/clpt.2009.311 · Cited by 419
Hasselbalch, H. C. (2012) · Blood · doi:10.1182/blood-2011-11-394775 · Cited by 300
Metadata
- Authors
- Goldberg, R. B.
- Venue
- The Journal of Clinical Endocrinology & Metabolism
- Publisher
- The Endocrine Society
- Published
- 2009-09-01
- Volume
- 94
- Issue
- 9
- Pages
- 3171-3182
- ISSN
- 0021-972X (ISSN-L)
- 1945-7197
- OpenAlex
- W2052882363
- Cited by
- 644
- References
- 20
- FWCI
- 33.52
- Type
- journal article
- Language
- en
- Open access
- closed
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- Goldberg, R. B. (2009). Cytokine and Cytokine-Like Inflammation Markers, Endothelial Dysfunction, and Imbalanced Coagulation in Development of Diabetes and Its Complications. The Journal of Clinical Endocrinology & Metabolism. https://doi.org/10.1210/jc.2008-2534
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