The 'vitamin E regeneration system' (VERS) and an algorithm to justify antioxidant supplementation in diabetes--a hypothesis.

In studies of vitamin E effectiveness in diabetes, there are still controversies surrounding negative observational and positive experimental results. However, there is no controversy that antioxidant vitamin E is regenerated from its pro-oxidant tocopheroxyl radical by a network of interacting co-antioxidants. The network of interacting co-antioxidants has only been studied individually. The hypothesis we propose is that a vitamin E regeneration system (VERS) model based on the complex interactions of the co-antioxidants provides a rationale for vitamin E supplementation as a therapeutic adjunct in diabetes. Furthermore, the factors considered prior to the use of Vitamin E as a supplement in diabetes research and therapy, the effectiveness of vitamin E supplementation and the limitations have been identified in the literature. There is no single study of vitamin E supplementation or efficacy that has determined vitamin E levels in combination with all of the co-antioxidants that interact to regenerate oxidised vitamin E. Therefore, there is a lack of good evidence for or against vitamin E being unilaterally depleted in the antioxidant network. There is also lack of rationale for choice of co-antioxidant supplementation. In essence, the normal conditions for effective antioxidant activity of vitamin E supplementation have yet to be fully explored. We propose a coherent model of VERS, and recommend that VERS status needs to be assessed, as part of evidence-based clinical practice to determine whether vitamin E should be recommended for the diabetic patient. We also propose an algorithm, based on the antioxidant activity and confounding factors, to guide the formulation of a credible hypothesis for clinical trials in assessing the function of vitamin E and treatment outcomes. The proposed model hinges on pertinent questions that have to be addressed to avoid organising a clinical trial that has been identified as biased.