Abstract

Analysis of gene expression (e.g. Ferredoxin Reductase: FDXR) changes in the blood samples have shown potential as predictive markers of disease, prognosis for therapy as well as triage and dose estimation in radiation-exposed populations. Similarly, quantification of micronuclei (MN) formation has been presented as a rapid cytogenetic marker for those applications. It was cautioned that the reliable utilization of these markers for prediction of disease, therapy prognosis, and dose estimation depends upon the information on known variables that affect these markers. Literature suggests that advanced glycation end products/oxidative stress in diabetic conditions can alter the levels of DNA damage and gene expression, and impact the segregation of the exposed from unexposed during nuclear disasters. Therefore, we investigated the influence of Type 2 diabetes mellitus (T2DM) on baseline expression of the FDXR and frequency of MN. Peripheral blood samples were collected from healthy volunteers (HV) (n = 60; 43 males and 17 females) and T2DM patients (n = 60; 32 males and 28 females), and performed real-time quantification of FDXR gene expression and analysis of MN frequency using microscopy. The basal level of FDXR gene expression (2.55 folds) (p < 0.01) and the frequency of MN is significantly (p < 0.01) higher (4 folds) in T2DM patients when compared to HV. Further, subgroup analysis found that gender, alcohol, smoking, duration of T2DM, complications, and medications increased both the expression of the FDXR gene and frequency of MN in T2DM; nevertheless, the increase was not significant, except for gender (p < 0.05) and medication (p < 0.05) on the frequency of MN. Overall results indicate that the T2DM patients showed a higher basal level expression of the FDXR gene and MN frequency when compared to HV and suggest an altered metabolic condition in T2DM is a confounding factor that impacts the levels of those markers. The increased levels of these markers might need to be considered to monitor medical radiation exposures and reliable biodosimetry during large-scale radiological accidents.

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