The objective of the study was to determine whether weight loss in obese men improves their fertility with respect to DNA fragmentation index and morphology. Collected fertility parameters included DFI and morphology. Body mass index (BMI) was calculated for all patients with comparisons to their fertility parameters before and after weight loss using paired t test and chi-square tests. The mean BMI was significantly higher in group 1, before weight loss (33.18 kg/m ), than in group 2, after weight loss (30.43 kg/m ). Overall, 53.3% of men had DFI <20% while 43.8% had a DFI between 20% and 40%, and 2.9% of men had DFI >40%. The mean DFI of participants was higher before weight loss (20.2%) and had improved significantly after weight loss (17.5%) (p = <.001). The weight loss had significant positive correlation with percentage of DFI. There was a significant improvement in morphology after weight loss (p = <.05). In one of the largest cohorts of male fertility and obesity, DFI and morphology demonstrated significant relationship with adiposity, possibly contributing to subfertility in this population.
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) widely known as COVID-19 was first reported in late December 2019, in China. Since then this novel coronavirus has spread throughout the world. Our return to normal life will not take long, for we are in a phase where the COVID-19 curve is stabilizing. ART services must return to operation, since infertility is also a disease and treatment has to start. Before resuming ART treatments, it is very important to consider local and national regulations. Change is mandatory, to set us back to successful ART treatment without compromising on quality, and to minimize the spread of COVID-19 among staff and patients; and for this we need to take measured and vigilant steps.
Purpose To identify the frequency of Y chromosome microdeletions in Indian populations and to quantitatively estimate the significance of association between these deletions and male infertility. Methods A total of 379 infertile males (302 azoospermic and 77 oligozoospermic infertile males) and 265 normozoospermic fertile males were evaluated for Y chromosome microdeletions (YCD) using PCR amplification and gel electrophoresis. Metaanalyses were performed on AZFa (2079 cases and 1217 controls), AZFb (2212 cases and 1267 controls), AZFc (4131 cases and 2008 controls), and AZFb+c (1573 cases and 942 controls) deletions data to quantitatively estimate the significance of association between these deletions and male infertility in Indian populations. ResultsThe results revealed that out of 379 infertile azoospermic and oligozoospermic males, 38 (10.02%) had AZF deletions. No deletion was found in control samples. The highest percentage of deletions was observed in the AZFc region, followed by AZFa and AZFb. Qualitative analysis showed that AZF deletions were present in 0.59 to 32.62% (average 13.48%) of infertile cases in Indian populations. Meta-analysis revealed a significant association of AZFa (OR = 6.74, p value = 0.001), AZFb (OR = 4.694, p value = 0.004), AZFc (OR = 13.575, p value = 0.000), and AZFb+c (OR = 5.946, p value = 0.018) deletions with male infertility. Conclusion AZF deletions were seen in 10.02% of azoospermic and oligozoospermic cases with the highest frequency of AZFc deletions. Pooled analysis for all studies showed deletion frequency from 0.59 to 32.62% (average = 13.48%). Meta-analysis showed significant association of AZFa, AZFb, and AZFb+c deletions with male infertility. Analysis of Y chromosome microdeletions should be reckoned as an essential testing for diagnostic and therapeutic purposes.
Background In contrast with the preceding stages of the germ cells, spermatozoa are unusually rich in small non-coding RNAs in comparison to the coding RNAs. These small RNAs may have had an essential role in the process of spermatogenesis or may have critical roles in the post-fertilization development. Sporadic efforts have identified a few differentially expressed miRNAs in infertile individuals, which do not replicate in other studies. Methods In order to identify miRNAs signatures of infertility or poor sperm quality, we compared miRNA differential expression data across nine datasets, followed by their analysis by real-time PCR in a case–control study. This was followed by the validation of potential biomarkers in yet another set of cases and controls. For this, total RNA was isolated from 161 sperm samples. miRNA expression levels in infertile cases and fertile controls were measured using TaqMan real-time PCR. Meta-analyses of two miRNAs (hsa-miR-9-3p and hsa-miR-122-5p) were performed using Comprehensive Meta‐Analysis Software (version 2). All statistical analyses were performed with the help of GraphPad Prism Software (version 8). Results Literature search identified seven miRNAs (hsa-let-7a-5p, hsa-miR-9-3p, hsa-miR-22-5p, has-miR-30b-5p, hsa-miR-103-3p, hsa-miR-122-5p and hsa-miR-335-5p) showing consistent dysregulation in infertility across a minimum of four studies. In the discovery phase, six miRNAs showed strong association with infertility with four (hsa-miR-9-3p, hsa-miR-30b-5p, hsa-miR-103-3p and hsa-miR-122-5p) showing consistent differential regulation across all sub-groups. Receiver operating characteristic (ROC) curve analysis showed that the area under curve of > 0.75 was achieved by three (hsa-mir-9-3p, hsa-miR-30b-5p and hsa-miR-122-5p) miRNAs. In the validation phase, these three miRNAs showed consistent association with infertility (hsa-mir-9-3p, hsa-miR-30b-5p, and hsa-miR-122-5p). Meta-analysis on hsa-miR-122-5p showed its significant quantitative association with infertility [Hedge’s g = -2.428, p = 0.001 (Random effects)]. Conclusions Three miRNAs (hsa-miR-9-3p, hsa-miR-30b-5p and hsa-miR-122-5p) have strong linkage with infertility and a high potential as sperm quality biomarkers.
The aim of the present study was to identify RNA‐based signatures of male infertility by sperm transcriptome analysis. In this study, deep sequencing analyses of coding (mRNA) and regulatory (miRNA) transcriptomes were performed by pooling 15 oligo/oligoasthenozoospermic infertile sperm and 9 normozoospermic fertile sperm samples. Furthermore, interesting candidates were selected for validation by real‐time PCR. The comparison of miRNAs between cases and controls identified 94 differentially expressed miRNAs, of which at least 38 have known functions in spermatogenesis. In transcriptome (mRNA) data, a total of 60,505 transcripts were obtained. The comparison of coding RNAs between cases and controls revealed 11,688 differentially expressed genes. miRNA–mRNA paired analysis revealed that 94 differentially expressed miRNAs could potentially target 13,573 genes, of which 6419 transcripts were actually differentially expressed in our data. Out of these, 3303 transcripts showed inverse correlation with their corresponding regulatory miRNAs. Moreover, we found that most of the genes of miRNA–mRNA pairs were involved in male germ cell differentiation, apoptosis, meiosis, spermiogenesis and male infertility. In conclusion, we found that a number of sperm transcripts (miRNAs and mRNAs) have a very high potential of serving as infertility/sperm quality markers.
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