Department of Physiology and Pharmacology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
Department of Obstetrics and Gynecology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
PLoS One. 2022 Apr 4;17(4):e0265853. doi: 10.1371/journal.pone.0265853. eCollection 2022.
The ability to predict spontaneous preterm birth (sPTB) prior to labour onset is a challenge, and it is currently unclear which biomarker(s), may be potentially predictive of sPTB, and whether their predictive power has any utility. A systematic review was conducted to identify maternal blood biomarkers of sPTB.
This study was conducted according to PRISMA protocol for systematic reviews. Four databases (MEDLINE, EMBASE, CINAHL, Scopus) were searched up to September 2021 using search terms: "preterm labor", "biomarker" and "blood OR serum OR plasma". Studies assessing blood biomarkers prior to labour onset against the outcome sPTB were eligible for inclusion. Risk of bias was assessed based on the Newcastle Ottawa scale. Increased odds of sPTB associated with maternal blood biomarkers, as reported by odds ratios (OR), or predictive scores were synthesized. This review was not prospectively registered.
Seventy-seven primary research articles met the inclusion criteria, reporting 278 unique markers significantly associated with and/or predictive of sPTB in at least one study. The most frequently investigated biomarkers were those measured during maternal serum screen tests for aneuploidy, or inflammatory cytokines, though no single biomarker was clearly predictive of sPTB based on the synthesized evidence. Immune and signaling pathways were enriched within the set of biomarkers and both at the level of protein and gene expression.
There is currently no known predictive biomarker for sPTB. Inflammatory and immune biomarkers show promise, but positive reporting bias limits the utility of results. The biomarkers identified may be more predictive in multi-marker models instead of as single predictors. Omics-style studies provide promising avenues for the identification of novel (and multiple) biomarkers. This will require larger studies with adequate power, with consideration of gestational age and the heterogeneity of sPTB to identify a set of biomarkers predictive of sPTB.
预测分娩前自发性早产（sPTB）的能力是一个挑战，目前尚不清楚哪种生物标志物可能具有预测早产的潜力，以及它们的预测能力是否具有任何实用性。本文进行了一项系统综述，以确定与 sPTB 相关的母体血液生物标志物。
本研究按照 PRISMA 系统评价协议进行。使用“早产劳动”、“生物标志物”和“血液或血清或血浆”等检索词，检索了 MEDLINE、EMBASE、CINAHL 和 Scopus 这四个数据库，检索时间截至 2021 年 9 月。评估了在分娩前评估血液生物标志物与 sPTB 结局的研究，以确定其是否符合纳入标准。基于纽卡斯尔-渥太华量表评估了偏倚风险。根据报道的比值比（OR）或预测评分，综合了与 sPTB 相关的母体血液生物标志物的优势比。本综述未进行前瞻性注册。
77 篇主要研究文章符合纳入标准，报告了 278 个独特的标志物，这些标志物在至少一项研究中与 sPTB 显著相关和/或具有预测性。研究最多的生物标志物是在母体血清筛查非整倍体或炎症细胞因子时测量的标志物，但根据综合证据，没有单一的生物标志物可明确预测 sPTB。免疫和信号通路在生物标志物中富集，并且在蛋白质和基因表达水平上均有富集。
目前没有已知的 sPTB 预测性生物标志物。炎症和免疫生物标志物显示出一定的前景，但阳性报告偏倚限制了结果的实用性。确定的生物标志物在多标志物模型中可能更具预测性，而不是作为单一预测因子。基于组学的研究为识别新的（和多个）生物标志物提供了有前景的途径。这将需要具有足够效力的更大规模的研究，同时需要考虑到 sPTB 的妊娠年龄和异质性，以确定一组可预测 sPTB 的生物标志物。
