Influence of tobacco cigarette heavy smoking on DNA methylation patterns and transcription levels of MAPK8IP3, GAA, ANXA2, PRRC2A, and PDE11A genes in human spermatozoa

Influence of Seminal Metals on Assisted Reproduction Outcome

Increased levels of metal ions in human seminal fluid have a significant correlation with male fertility. Few publications explain the effect of metals in semen and their influence on assisted reproductive treatments. Semen parameters and the levels of twenty-two metals were measured in the seminal fluid of 102 men attended in a Reproductive Unit. Metals were determined by optical emission spectrophotometry. A statistical relationship was found between spermiogram and iron, which was lower than expected in pathological spermiograms (p = 0.032); zinc (p = 0.066), calcium (p = 0.047), and magnesium (p = 0.048) mean levels were higher in normozoospermics. More days of sexual abstinence correlates with higher seminal zinc (p = 0.001) and magnesium levels (p = 0.002). Lower vanadium values were found to be associated with higher fertilization rates (p = 0.039). Higher values of lead (p = 0.052) and vanadium (p = 0.032) were obtained in patients who did not reach 100% embryo cleavage rate. Aluminium (p = 0.042) and sodium (p = 0.002) were found in lower amounts associated with better blastocyst rates. The implantation rate shows an inverse association with women's age and iron and calcium content, compared to magnesium and sodium which presented a significant direct association with this percentage. A significant direct relationship was found between the positive evolution of pregnancy and the values of zinc (p = 0.004), calcium (p = 0.013), potassium (p = 0.002), and magnesium (p = 0.009). The study confirms that zinc, iron, calcium, sodium, aluminium, magnesium, vanadium, and lead have positive-negative effects on reproduction and support the analysis of metals in semen as a new line of study on male fertility with implications for reproductive outcomes.

Statistical Bioinformatics to Uncover the Underlying Biological Mechanisms That Linked Smoking with Type 2 Diabetes Patients Using Transcritpomic and GWAS Analysis

Type 2 diabetes (T2D) is a chronic metabolic disease defined by insulin insensitivity corresponding to impaired insulin sensitivity, decreased insulin production, and eventually failure of beta cells in the pancreas. There is a 30–40 percent higher risk of developing T2D in active smokers. Moreover, T2D patients with active smoking may gradually develop many complications. However, there is still no significant research conducted to solve the issue. Hence, we have proposed a highthroughput network-based quantitative pipeline employing statistical methods. Transcriptomic and GWAS data were analysed and obtained from type 2 diabetes patients and active smokers. Differentially Expressed Genes (DEGs) resulted by comparing T2D patients’ and smokers’ tissue samples to those of healthy controls of gene expression transcriptomic datasets. We have found 55 dysregulated genes shared in people with type 2 diabetes and those who smoked, 27 of which were upregulated and 28 of which were downregulated. These identified DEGs were functionally annotated to reveal the involvement of cell-associated molecular pathways and GO terms. Moreover, protein–protein interaction analysis was conducted to discover hub proteins in the pathways. We have also identified transcriptional and post-transcriptional regulators associated with T2D and smoking. Moreover, we have analysed GWAS data and found 57 common biomarker genes between T2D and smokers. Then, Transcriptomic and GWAS analyses are compared for more robust outcomes and identified 1 significant common gene, 19 shared significant pathways and 12 shared significant GOs. Finally, we have discovered protein–drug interactions for our identified biomarkers.

Cigarette heavy smoking alters DNA methylation patterns and gene transcription levels in humans spermatozoa

Tobacco smoking is considered the most common reason of death and infertility around the world. This study was designed to assess the impact of tobacco heavy smoking on sperm DNA methylation patterns and to determine whether the transcription level of ALDH3B2, PTGIR, PRICKLE2, and ALS2CR12 genes is different in heavy smokers compared to non-smokers. As a screening study, the 450 K array was used to assess the alteration in DNA methylation patterns between heavy smokers (n = 15) and non-smokers (n = 15). Then, four CpGs that have the highest difference in methylation level (cg16338278, cg08408433, cg05799088, and cg07227024) were selected for validation using deep bisulfite sequencing in an independent cohort of heavy smokers (n = 200) and non-smokers (n = 100). A significant variation was found between heavy smokers and non-smokers in the methylation level at all CpGs within the PRICKLE2 and ALS2CR12 gene amplicon (P < 0.001). Similarly, a significant variation was found in the methylation level at nine out of thirteen CpGs within the ALDH3B2 gene amplicon (P < 0.01). Additionally, eighteen CpGs out of the twenty-six within the PTGIR gene amplicon have a significant difference in the methylation level between heavy smokers and non-smokers (P < 0.01). The study showed a significant difference in sperm global DNA methylation, chromatin non-condensation, and DNA fragmentation (P < 0.001) between heavy smokers and non-smokers. A significant decline was shown in the transcription level of ALDH3B2, PTGIR, PRICKLE2, and ALS2CR12 genes (P < 0.001) in heavy smokers. In conclusion, heavy smoking influences DNA methylation at several CpGs, sperm global DNA methylation, and transcription level of the PRICKLE2, ALS2CR12, ALDH3B2, and PTGIR genes, which affects negatively the semen parameters of heavy smokers.