Division of Endocrinology, Central Drug Research Institute, Lucknow, India.
Department of Zoology, Lucknow University, Lucknow, India.
Reprod Biol Endocrinol. 2022 Aug 15;20(1):122. doi: 10.1186/s12958-022-00990-7.
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.
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).
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)].
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.
与生殖细胞的前几个阶段相比,精子中的小非编码 RNA 特别丰富,而编码 RNA 则相对较少。这些小 RNA 可能在精子发生过程中具有重要作用,或者在受精后发育过程中具有关键作用。尽管已经进行了零星的努力来鉴定不育个体中差异表达的 miRNAs,但这些 miRNA 在其他研究中并未得到复制。
为了鉴定不育或精子质量差的 miRNA 特征,我们比较了九个数据集的 miRNA 差异表达数据,然后在病例对照研究中通过实时 PCR 对其进行了分析。随后,在另一组病例和对照中验证了潜在的生物标志物。为此,我们从 161 个精子样本中分离出总 RNA。使用 TaqMan 实时 PCR 测量不育病例和正常生育对照的 miRNA 表达水平。使用 Comprehensive Meta-Analysis Software(版本 2)对两个 miRNA(hsa-miR-9-3p 和 hsa-miR-122-5p)进行了荟萃分析。使用 GraphPad Prism Software(版本 8)进行了所有统计分析。
文献检索确定了七个 miRNA(hsa-let-7a-5p、hsa-miR-9-3p、hsa-miR-22-5p、has-miR-30b-5p、hsa-miR-103-3p、hsa-miR-122-5p 和 hsa-miR-335-5p)在至少四个研究中一致失调与不育有关。在发现阶段,有六个 miRNA 与不育有很强的关联,其中四个(hsa-miR-9-3p、hsa-miR-30b-5p、hsa-miR-103-3p 和 hsa-miR-122-5p)在所有亚组中均表现出一致的差异调节。受试者工作特征(ROC)曲线分析表明,三个 miRNA(hsa-mir-9-3p、hsa-miR-30b-5p 和 hsa-miR-122-5p)的曲线下面积 > 0.75。在验证阶段,这三个 miRNA 与不育一致相关(hsa-mir-9-3p、hsa-miR-30b-5p 和 hsa-miR-122-5p)。对 hsa-miR-122-5p 的荟萃分析表明,其与不育具有显著的定量关联[Hedge's g = -2.428,p = 0.001(随机效应)]。
三个 miRNA(hsa-miR-9-3p、hsa-miR-30b-5p 和 hsa-miR-122-5p)与不育密切相关,具有成为精子质量生物标志物的高潜力。