Sperm epigenetics and sperm RNAs as drivers of male infertility: truth or myth?

Male infertility represents a complex clinical condition that often challenges the ability of reproductive specialists to find its etiology and then propose an adequate treatment. The unexplained decline in sperm count, as well as the association between male infertility and mortality, morbidity, and cancer, has prompted researchers toward an urgent need to better understand the causes of male infertility. Therefore, molecular biologists are increasingly trying to study whether sperm epigenetic alterations may be involved in male infertility and embryo developmental abnormalities. In this context, research is also trying to uncover the hidden role of sperm RNAs, both coding and non-coding. This narrative review aims to thoroughly and comprehensively present the relationship between sperm epigenetics, sperm RNAs, and human fertility. We first focused on the technological aspects of studying sperm epigenetics and RNAs, relating to the complex role(s) played in sperm maturation, fertilization, and embryo development. Then, we examined the intricate connections between epigenetics and RNAs with fertility measures, namely sperm concentration, embryo growth and development, and live birth rate, in both animal and human studies. A better understanding of the molecular mechanisms involved in sperm epigenetic regulation, as well as the impact of RNA players, will help to tackle infertility.

Effects of pesticide exposure on the expression of selected genes in normal and cancer samples: Identification of predictive biomarkers for risk assessment.

Pesticides pivotal in controlling pests, can represent a threat for human health. Regulatory agencies constantly monitor their harmful effects, regulating their use. Several studies support a positive association between long-term exposure to pesticides and chronic pathologies, such as cancer. Geno-toxicological biomonitoring has proven to be valuable to assess genetic risks associated with exposure to pesticides, representing a promising tool to improve preventive measures and identify workers at higher risk. In this study, a differential gene expression analysis of 70 candidate genes deregulated upon pesticide exposure, was performed in 10 GEO human gene expression DataSets. It was found that six genes (PMAIP1, GCLM, CD36, SQSTM1, ABCC3, NR4A2) had significant AUC predictive values. Also, CD36 was upregulated in non-transformed cell samples and healthy workers, but downregulated in cancer cells. Further validation in larger groups of workers will corroborate the importance of the identified candidates as biomarkers of exposure/effect.