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Insulin-resistance (IR) is one of the most important precursors of type 2 diabetes (T2D). Recent evidence suggests an association of depression with the onset of T2D. Accumulating evidence shows that depression and T2D share common biological origins, and DNA methylation examination might reveal the link between lifestyle, disease risk, and potential therapeutic targets for T2D. Here we hypothesize that integrative mining of IR and depression cohort data will facilitate predictive biomarkers identification for T2D. We utilized a newly proposed method to extract gene-level information from probe level data on genome-wide DNA methylation array. We identified a set of genes associated with IR and depression in clinical cohorts. By overlapping the IR-related nutraceutical-gene network with depression networks, we identified a common subnetwork centered with Vitamin D Receptor (VDR) gene. Preliminary clinical validation of gene methylation set in a small cohort of T2D patients and controls was established using the Sequenome matrix-assisted laser desorption ionization-time flight mass spectrometry. A set of sites in the promoter regions of VDR showed a significant difference between T2D patients and controls. Using a logistic regression model, the optimal prediction performance of these sites was AUC = 0.902，and an odds ratio = 19.76. Thus, monitoring the methylation status of specific VDR promoter region might help stratify the high-risk individuals who could potentially benefit from vitamin D dietary supplementation. Our results highlight the link between IR and depression, and the DNA methylation analysis might facilitate the search for their shared mechanisms in the etiology of T2D.

Epigenetics is an essential biological frontier linking genetics to the environment, where DNA methylation is one of the most studied epigenetic events. In recent years, through the epigenome-wide association study (EWAS), researchers have identified thousands of phenotype-related methylation sites. However, the overlaps of identified phenotype-related DNA methylation sites between various studies are often quite small, and it might be due to the fact that methylation remodeling has a certain degree of randomness within the genome. Thus, the identification of robust gene-phenotype associations is crucial to interpreting pathogenesis. How to integrate the methylation values of different sites on the same gene and to mine the DNA methylation at the gene level remains a challenge. A recent study found that the DNA methylation difference of the gene body and promoter region has a strong correlation with gene expression. In this study, we proposed a Statistical difference of DNA Methylation between Promoter and Other Body Region (SIMPO) algorithm to extract DNA methylation values at the gene level. First, by choosing to smoke as an environmental exposure factor, our method led to significant improvements in gene overlaps (from 5 to 17%) between different datasets. In addition, the biological significance of phenotype-related genes identified by SIMPO algorithm is comparable to that of the traditional probe-based methods. Then, we selected two disease contents (e.g., insulin resistance and Parkinson’s disease) to show that the biological efficiency of disease-related gene identification increased from 15.43 to 44.44% (p-value = 1.20e–28). In summary, our results declare that mining the selective remodeling of DNA methylation in promoter regions can identify robust gene-level associations with phenotype, and the characteristic remodeling of a given gene’s promoter region can reflect the essence of disease.

Tetramethylpyrazine (TMP), extracted from the Chinese herbal medicine Ligusticum wallichii franchat (chuan xiong in Chinese), is a potent anti-free radical and calcium antagonist. Correspondingly, two important hypotheses in the causation of cataracts are free radical toxicity and calcium ion overload. In this study we investigated the effect of TMP on lens opacification induced by sodium selenite in rats, addressing the potential of TMP eye drops to prevent and treat cataracts. Results showed that the extent of lens opacification in the untreated Normal Control group (NC group) was significantly less than that of selenite-injected untreated rats (MC group) on days 3, 5, 7 and 10 (p 0.001), while TMP treated selenite-injected rats (TMP group) had less lens opacification than the MC group on days 3, 5, 7 and 10 (p 0.05). Compared with the NC group, the MC group had significantly decreased activity of super-oxide dismutase (SOD), glutathione peroxidase (GSH-PX) and catalase (CAT) and significantly elevated malondialdehyde (MDA) and calcium ion content (p 0.001). Compared with the MC group, the activity of (SOD), (GSH-PX) and (CAT) were significantly higher while (MDA) and calcium ion levels were significantly lower in the TMP group at all time points (p 0.01). The findings demonstrate that the selenite-induced cataract rat models were successfully built and the TMP eye drops can delay lens opacification induced by sodium selenite in rats. The mechanism by which TMP preserves lens transparency from selenite treated animals is associated with the lenses' ability to maintain normal levels of activity of SOD, GSH-PX and CAT and normal concentrations of MDA and calcium ion.