Exposure to potentially toxic elements (PTEs) and the risk of male infertility- A Systematic review and meta-analysis.

BACKGROUND: Infertility has been defined as a failure to conceive for at least 12 months of regular unprotected sexual intercourse. The male factors are responsible for about 50 % of cases. Various factors such as endocrine, immunological, genetic, exposure to toxicants, and idiopathic factors are involved in male infertility. Recently, the role of PTEs in reproductive performance has been explored by various studies. OBJECTIVES: Current systematic review and meta-analysis have been carried out to compile and statistically analyze the findings of relevant studies and reach some conclusion. METHODOLOGY: A literature search was done according to the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) guidelines in three scientific literature databases; PubMed, Google Scholar, and Science Direct. Meta-analysis was performed using Review Manager 5.4 software. The study's protocol was registered in PROSPERO (CRD42023465776). RESULTS: Meta-analysis of lead in the blood of infertile cases and healthy controls indicated a significant association with male infertility, observed standard mean difference (SMD) was 0.67 at 95 % confidence interval (CI) (0.07, 1.28), and p = 0.03. In the case of lead analysis in semen, the values are as follows: SMD = 1.19 at 95 % CI (0.42, 1.96) with p = 0.002. Significant association appears for cadmium in semen with SMD 0.92 at 95 % CI (0.54, 1.29) and p < 0.00001. No significant association was observed for arsenic, barium, and mercury in blood. CONCLUSION: Most of the studies focus on the detection of PTE in semen samples followed by blood as sample type. Lead and cadmium exposure is significantly associated with male infertility. However, non-significant results for arsenic, barium, and mercury are observed.

Investigation of the Association of Serum Trace Elements Concentrations and Serum Biochemical Parameters with the Risk of Polycystic Ovary Syndrome: a Case-Control Study.

Polycystic ovary syndrome (PCOS) is a heterogeneous endocrinological syndrome characterized by hyperandrogenism of ovarian origin and is often considered a predisposing factor for metabolic disorders. The objective of the study was to investigate serum levels of (a) trace elements (copper (Cu), zinc (Zn), magnesium (Mg), selenium (Se), iron (Fe), chromium (Cr), and manganese (Mn)); and (b) biochemical parameters (glucose, cholesterol, triglycerides, high-density lipoprotein (HDL-C), low-density lipoprotein (LDL-C), albumin, total protein, creatinine, and C-reactive protein (CRP) with risk of PCOS. Another objective was to explore the relationship between serum trace elements and biochemical variables. Serum trace elements were estimated by inductively coupled plasma mass spectrometry (ICP-MS) and biochemical parameters were estimated by colorimetric methods in 99 PCOS cases and 82 controls. Linear and non-linear associations of serum variables with PCOS risk were studied under logistic, probit, GAM, and BKMR model. Statistical analyses were performed using IBM SPSS 22.0 and R package version 4.2.1. All studied serum trace elements (except Zn) are significantly associated with PCOS. Combined effect analysis revealed Mg-Se and Fe-Cu association with PCOS risk. A significant association of cholesterol, HDL-C, LDL-C, CRP, and albumin was observed. Furthermore, linear regression analysis suggests an association between Mg-Cu and Mg-Fe-Mn with HDL-C; Fe and Cr-Cu with albumin; and Cu-Se with cholesterol and LDL-C both.

A panel of blood-based circulatory miRNAs with diagnostic potential in patients with psoriasis.

Psoriasis is a chronic inflammatory skin disease with keratinocyte hyperproliferation and T cells as key mediators of lesional and systemic inflammatory changes. To date, no suitable differential biomarkers are available for the disease diagnosis. More recently, microRNAs have been identified as critical regulators of lesional and systemic immune changes in psoriasis with diagnostic potential. We have performed expression profiling of T cell-specific miRNAs in 38 plasma samples from psoriasis vulgaris patients and an equal number of age- and gender-matched healthy subjects. Our findings have identified a panel of five blood-based circulatory miRNAs with a significant change in their expression levels, comprising miR-215, miR-148a, miR-125b-5p, miR-223, and miR-142-3p, which can differentiate psoriasis vulgaris patients from healthy individuals. The receiver operating characteristic (ROC) curves for all five miRNAs individually and in combination exhibited a significant disease discriminatory area under the curve with an AUC of 0.762 and a p < 0.0001 for all the miRNAs together. Statistically, all five miRNAs in combination depicted the best-fit model in relation to disease severity (PASI) compared with individual miRNAs, with the highest R2 value of 0.94 and the lowest AIC score of 131.8. Each of the miRNAs also exhibited a significant association with at least one of the other miRNAs in the panel. Importantly, the five miRNAs in the panel regulate one or more immune-inflammation pathways based on target prediction, pathway network analysis, and validated roles in the literature. The miRNA panel provides a rationalized combination of biomarkers that can be tested further on an expanded cohort of patients for their diagnostic value.

A diagnostic and prognostic value of blood-based circulating long non-coding RNAs in thyroid, pancreatic and ovarian cancer.

Several studies have demonstrated the potential of circulating long non-coding RNAs (lncRNAs) as promising cancer biomarkers. Herein, we addressed the regulatory role of circulating lncRNAs and their potential value as diagnostic/prognostic markers for thyroid, pancreatic and ovarian cancers. Furthermore, we analyzed and measured the clinical implications and association of lncRNAs with sensitivity, specificity, and area under the ROC curve (AUC). Based on our meta-analysis, we found that GAS8-AS1 could discriminate thyroid cancer from non-cancer and other cancers with higher accuracy (AUC = 0.746; sensitivity = 61.70 %, and specificity = 90.00 %). Similarly, for ovarian cancer, lncRNA RP5-837J1.2 was found to have ideal diagnostic potential with critical clinical specifications of AUC = 0.996; sensitivity = 97.30 % and specificity = 94.60 %. Whereas we could not find any lncRNA having high diagnostic/prognostic efficiency in pancreatic cancer. We believe that lncRNAs mentioned above may explore clinical settings for the diagnosis and prognosis of cancer patients.