Dingle Kamaludin, Kassem Osama M, Azizieh Fawaz, AbdulHussain Ghadeer, Raghupathy Raj
Centre for Applied Mathematics and Bioinformatics, Department of Mathematics and Natural Sciences, Gulf University for Science and Technology, Hawally, Kuwait; Department of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, CA, USA.
Centre for Applied Mathematics and Bioinformatics, Department of Mathematics and Natural Sciences, Gulf University for Science and Technology, Hawally, Kuwait.
Cytokine. 2023 Apr;164:156160. doi: 10.1016/j.cyto.2023.156160. Epub 2023 Feb 18.
Cytokines play important roles in pregnancy complications. Some hormones such as estrogen, progesterone, and dydrogesterone have been shown to alter cytokine profiles. Understanding how cytokine profiles are affected by these hormones is therefore an important step towards immunomodulatory therapies for pregnancy complications. We analyse previously published data on the effects of estrogen, progesterone, and dydrogesterone on cytokine balances in women having recurrent spontaneous miscarriages.
Levels of eight cytokines (IFN-γ, IL-2, IL-6, IL-10, IL-13, IL-17, IL-23, TNF-α) from n = 22 women presenting unexplained recurrent spontaneous miscarriages were studied. Cytokine values were recorded after in vitro exposure of peripheral blood cells to estrogen, progesterone, and dydrogesterone. We expand on earlier analysis of the dataset by employing different statistical techniques including effect sizes for individual cytokine values, a more powerful statistical test, and adjusting p-values for multiple comparisons. We employ multivariate analysis methods, including to determine the relative magnitude of the effects of the hormone therapies on cytokines. A new statistical method is introduced based on pairwise distances able to accommodate complex relations in cytokine profiles.
We report several statistically significant differences in individual cytokine values between the control group and each hormone treated group, with estrogen affecting the fewest cytokines, and progesterone and dydrogesterone both affecting seven out of eight cytokines. Exposure to estrogen produces no large effects sizes however, while IFN-γ and IL-17 show large effect sizes for both progesterone and dydrogesterone, among other cytokines. Our new method for identifying which collections (i.e. subsets) of cytokines best distinguish contrasting groups identifies IFN-γ, IL-10 and IL-23 as especially noteworthy for both progesterone and dydrogesterone treatments.
While some statistically significant differences in cytokine levels after exposure to estrogen are found, these have small effect sizes and are unlikely to be clinically relevant. Progesterone and dydrogesterone both induce statistically significant and large effect-size differences in cytokine levels, hence therapy with these two progestogens is more likely to be clinically relevant. Univariate and multivariate methods for identifying cytokine importances provide insight into which groups of cytokines are most affected and in what ways by therapies.
细胞因子在妊娠并发症中起重要作用。一些激素，如雌激素、孕酮和地屈孕酮，已被证明会改变细胞因子谱。因此，了解这些激素如何影响细胞因子谱是朝着妊娠并发症免疫调节疗法迈出的重要一步。我们分析了先前发表的关于雌激素、孕酮和地屈孕酮对复发性自然流产女性细胞因子平衡影响的数据。
研究了n = 22例不明原因复发性自然流产女性的8种细胞因子（IFN-γ、IL-2、IL-6、IL-10、IL-13、IL-17、IL-23、TNF-α）水平。在体外将外周血细胞暴露于雌激素, 孕酮和地屈孕酮后记录细胞因子值。我们通过采用不同的统计技术，包括单个细胞因子值的效应大小、更强大的统计检验以及对多重比较的p值进行调整, 对数据集进行了扩展分析。我们采用多变量分析方法，包括确定激素疗法对细胞因子影响的相对大小。引入了一种基于成对距离的新统计方法，能够适应细胞因子谱中的复杂关系。
我们报告了对照组与各激素治疗组之间在单个细胞因子值上的几个统计学显著差异，雌激素影响的细胞因子最少，而孕酮和地屈孕酮均影响8种细胞因子中的7种。然而，暴露于雌激素不会产生较大的效应大小，而IFN-γ和IL-17在孕酮和地屈孕酮以及其他细胞因子中均显示出较大的效应大小。我们用于识别哪些细胞因子集合（即子集）最能区分对比组的新方法确定，IFN-γ、IL-10和IL-23在孕酮和地屈孕酮治疗中特别值得关注。
虽然在暴露于雌激素后发现细胞因子水平存在一些统计学显著差异，但这些差异的效应大小较小，不太可能具有临床相关性。孕酮和地屈孕酮均在细胞因子水平上诱导出统计学显著且效应大小较大的差异，因此这两种孕激素疗法更有可能具有临床相关性。用于识别细胞因子重要性的单变量和多变量方法提供了关于哪些细胞因子组受治疗影响最大以及以何种方式受影响的见解。
