Meta-analysis of mitochondrial T16189C polymorphism for cancer and Type 2 diabetes risk.

AIM

Whereas many previous studies have revealed that mitochondrial DNA (mtDNA) polymorphism T16189C is associated with the risk of cancer and Type 2 diabetes mellitus (T2DM), there are others that have disputed the same. As a result, clarity on the role of mitochondrial T16189C in these disorders is missing. The aim of this study is to evaluate the association of T16189C polymorphism with the risk of cancer and T2DM development by pooling all case-control studies available.

METHODS

Published studies till November 2017 were searched from PubMed, Google scholar, Google and EMBASE and isolated a total of 36 studies having 44,203 subjects (20,439 cases and 23,764 controls) based on strict inclusion and exclusion criteria. We used the statistical software "R" to calculate the Pooled Odds Ratios and 95% confidence intervals to evaluate the association of T16189C polymorphism with a possible risk towards cancer and T2DM development.

RESULT

From the meta-analysis, we obtained Pooled Odds Ratios using Random effect model for cancer (OR: 1.20, 95% CI: 0.96-1.49, P = 0.104) and for T2DM (OR: 1.22, 95% CI: 1.09-1.36, P = 0.0004). In the subgroup analysis with Random effect model, we found that both Asians and Caucasians were at a statistically significant risk (OR: 1.25, P < 0.0001 and OR: 1.20, P < 0.0001, respectively) for the development of T2DM, whereas, a statistically non-significant risk (OR: 1.28 P = 0.1965 and OR: 1.16, P = 0.1148) emerged for the development of cancer. There was no evidence of a significant publication bias (Egger's and Begg's test) in this meta-analysis. Further sensitivity analysis also demonstrated that our meta-analysis was relatively stable and credible.

CONCLUSION

Individuals with 'C' allele at position 16,189 within the mitochondrial D-loop are seemingly at a higher risk of developing T2DM and cancer. However, before arriving at generalizations, it would be pertinent to conduct similar studies in different populations with larger numbers to corroborate these results, especially in cancer.