Wednesday, July 8, 2009

A protein with a higher level of risk for type 2 diabetes

People with higher adiponectin, a protein from fat cells and anti-inflammatory and insulin sensitizing, reducing risks for type 2 diabetes, the analysis of previous studies in the July 8th edition of JAMA.

Several studies have suggested several mechanisms by which adiponectin reduce the risk of type 2 diabetes, although the strength and the relationship between plasma adiponectin and risk for type 2 diabetes is unclear, according to background information background in the article.

Shanshan Li, MD, M.Sc., Harvard School of Public Health, Boston, and colleagues, testing and meta-analysis to assess the consistency of the Association of adiponectin and risk of type 2 diabetes. The researchers identified thirteen studies with a total of 14,598 participants and 2623 new cases of type 2 diabetes as the criteria for granting such status for inclusion in the meta-analysis.

The authors found that higher levels of adiponectin have been linked with a level of risk for type 2 diabetes. This inverse association was consistently white, East Asian, Asian Indians, African Americans and Native Americans. The results do not differ significantly by the method of determination of diabetes, the size of study, monitoring, time, body mass index and the proportion of men and women.

"Although these epidemiological studies can not causation, consistency of association in different population groups, the dose-effect relationship, and support in the results of mechanistic studies suggest that adiponectin is one of promising targets reduced risk of type 2 diabetes, "write the authors.

The researchers add that recent studies have shown that adiponectin levels may be increased by the pharmacy and lifestyle interventions. "In addition, adiponectin levels may be useful in the identification of people, most interventions for the treatment of" inoperative adipose tissue and its metabolic complications. Future studies should also evaluate whether adiponectin is useful for the prediction of type 2 diabetes, in addition to the established risk factors with the help of statistical methods for prognostic analysis.

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