Male reproductive health is critically worsening around the world. It has been reported that the mycotoxin ZEA causes reproductive toxicity to domestic animals and affects spermatogenesis, thereby inhibiting male reproductive function. Ferroptosis is a newly identified type of programmed cell death that is different from apoptosis and it depends on iron accumulation and lipid peroxidation. Whether ferroptosis is linked to ZEA’s detrimental effect on spermatogenesis needs to be further explored. This study clarifies ferroptosis’s involvement in ZEA-induced damage on spermatogenesis. The reproductive injury model used in this study was induced by gavaging male mice in the ZEA treatment group with 30 μg/kg of ZEA for five weeks. Results show that ZEA treatment reduced mouse sperm motility and concentration, destroyed the structure of the seminiferous tubules of the testis, damaged the antioxidant defense system, and blocked spermatogenesis. Ferrostatin-1 (Fer-1) inhibition of ferroptosis partially alleviated ZEA-induced oligozoospermia in mice. In addition, ZEA treatment was found to activate a signaling pathway associated with ferroptosis in mouse testis. ZEA also downregulated the expression of Nrf2, SLC7A11, and GPX4, and decreased the protein expression of SLC7A11 and GPX4, resulting in the accumulation of lipid peroxides and an increase in the level of 4-HNE protein in the testis. Importantly, these changes were accompanied by an increase in the relative contents of Fe2+ and Fe3+. Iron accumulation and lipid peroxidation are the causes of ferroptosis in spermatogenic cells, leading to a decrease in sperm motility and concentration. While the administration of Fer-1 at 0.5 and 1 mg/kg also increased the expression of SLC7A11 and GPX4 proteins by upregulating Nrf2 expression, reducing iron accumulation, and reversing ZEA-induced ferroptosis, Fer-1 at 1.5 mg/kg had the best repairing effect for all parameters. In conclusion, ZEA-induced ferroptosis may be mediated by a notable reduction in Nrf2, SLC7A11 and GPX4 expression levels. Overall, ferroptosis is a novel therapeutic target for mitigating ZEA-induced reproductive toxicity.

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Long-term exposures to low-dose radiation (LDR) may trigger several specific biological responses, including dysregulation of the immune and inflammatory systems. Here, we examined whether biodosimetry of LDR can be used to protect tissues from radiation or assess cancer risk. Mice were subjected to gamma-irradiation with repeated or single-dose LDR, and then the organ indices, peripheral hemogram, and blood biochemistry were analyzed. An antibody array was applied followed by enzyme-linked immunosorbent assay to evaluate the utility of multiple plasma proteins as biomarkers of repeated LDR in a murine model. LDR induced inapparent symptoms but slight variations in peripheral blood cell counts and alterations in blood biochemical indicator levels. Specific plasma proteins in the LDR groups were altered in response to a higher dose of irradiation at the same time points or a single-dose equivalent to the same total dose. Plasma levels of interleukin (IL)-5, IL-12p40, P-selectin, and serum amyloid A1 were associated with the LDR dose and thus may be useful as dosimetric predictors of LDR in mice. Estimating the levels of certain plasma proteins may yield promising biodosimetry parameters to accurately identify individuals exposed to LDR, facilitating risk assessment of long-term LDR exposure in individuals.

Background Coronary heart disease (CHD) and type 2 diabetes (T2D) are two complex diseases with complex interrelationships. However, the genetic architecture of the two diseases is often studied independently by the individual single-nucleotide polymorphism (SNP) approach. Here, we presented a genotypic-phenotypic framework for deciphering the genetic architecture underlying the disease patterns of CHD and T2D. Method A data-driven SNP-set approach was performed in a genome-wide association study consisting of subpopulations with different disease patterns of CHD and T2D (comorbidity, CHD without T2D, T2D without CHD and all none). We applied nonsmooth nonnegative matrix factorization (nsNMF) clustering to generate SNP sets interacting the information of SNP and subject. Relationships between SNP sets and phenotype sets harboring different disease patterns were then assessed, and we further co-clustered the SNP sets into a genetic network to topologically elucidate the genetic architecture composed of SNP sets. Results We identified 23 non-identical SNP sets with significant association with CHD or T2D (SNP-set based association test, P < 3.70 × $${10}^{-4}$$ 10 - 4 ). Among them, disease patterns involving CHD and T2D were related to distinct SNP sets (Hypergeometric test, P < 2.17 × $${10}^{-3}$$ 10 - 3 ). Accordingly, numerous genes (e.g., KLKs, GRM8, SHANK2) and pathways (e.g., fatty acid metabolism) were diversely implicated in different subtypes and related pathophysiological processes. Finally, we showed that the genetic architecture for disease patterns of CHD and T2D was composed of disjoint genetic networks (heterogeneity), with common genes contributing to it (pleiotropy). Conclusion The SNP-set approach deciphered the complexity of both genotype and phenotype as well as their complex relationships. Different disease patterns of CHD and T2D share distinct genetic architectures, for which lipid metabolism related to fibrosis may be an atherogenic pathway that is specifically activated by diabetes. Our findings provide new insights for exploring new biological pathways.

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