Mirvie Inc., 820 Dubuque Ave, South San Francisco, CA.
Department of Women and Children's Health, School of Life Course Sciences, Faculty of Life Sciences and Medicine, King's College London; 10th Floor North Wing, St Thomas' Hospital Campus, Westminster Bridge Rd., London SE1 7EH, United Kingdom.
Am J Obstet Gynecol. 2022 Jul;227(1):72.e1-72.e16. doi: 10.1016/j.ajog.2022.04.002. Epub 2022 Apr 6.
Spontaneous preterm birth remains the main driver of childhood morbidity and mortality. Because of an incomplete understanding of the molecular pathways that result in spontaneous preterm birth, accurate predictive markers and target therapeutics remain elusive.
This study sought to determine if a cell-free RNA profile could reveal a molecular signature in maternal blood months before the onset of spontaneous preterm birth.
Maternal samples (n=242) were obtained from a prospective cohort of individuals with a singleton pregnancy across 4 clinical sites at 12-24 weeks (nested case-control; n=46 spontaneous preterm birth <35 weeks and n=194 term controls). Plasma was processed via a next-generation sequencing pipeline for cell-free RNA using the Mirvie RNA platform. Transcripts that were differentially expressed in next-generation sequencing cases and controls were identified. Enriched pathways were identified in the Reactome database using overrepresentation analysis.
Twenty five transcripts associated with an increased risk of spontaneous preterm birth were identified. A logistic regression model was developed using these transcripts to predict spontaneous preterm birth with an area under the curve =0.80 (95% confidence interval, 0.72-0.87) (sensitivity=0.76, specificity=0.72). The gene discovery and model were validated through leave-one-out cross-validation. A unique set of 39 genes was identified from cases of very early spontaneous preterm birth (<25 weeks, n=14 cases with time to delivery of 2.5±1.8 weeks); a logistic regression classifier on the basis of these genes yielded an area under the curve=0.76 (95% confidence interval, 0.63-0.87) in leave-one-out cross validation. Pathway analysis for the transcripts associated with spontaneous preterm birth revealed enrichment of genes related to collagen or the extracellular matrix in those who ultimately had a spontaneous preterm birth at <35 weeks. Enrichment for genes in insulin-like growth factor transport and amino acid metabolism pathways were associated with spontaneous preterm birth at <25 weeks.
Second trimester cell-free RNA profiles in maternal blood provide a noninvasive window to future occurrence of spontaneous preterm birth. The systemic finding of changes in collagen and extracellular matrix pathways may serve to identify individuals at risk for premature cervical remodeling, with growth factor and metabolic pathways implicated more often in very early spontaneous preterm birth. The use of cell-free RNA profiles has the potential to accurately identify those at risk for spontaneous preterm birth by revealing the underlying pathophysiology, creating an opportunity for more targeted therapeutics and effective interventions.
自发性早产仍然是儿童发病率和死亡率的主要驱动因素。由于对导致自发性早产的分子途径认识不完整，因此仍然难以确定准确的预测标志物和靶向治疗药物。
本研究旨在确定游离 RNA 谱是否可以在自发性早产发生前数月揭示母体血液中的分子特征。
从 4 个临床站点的单胎妊娠前瞻性队列中获得了 242 名母体样本（嵌套病例对照研究；<35 周自发性早产病例 46 例，<35 周足月对照组 194 例）。通过 Mirvie RNA 平台对血浆进行下一代测序的游离 RNA 处理。在 Reactome 数据库中使用过表达分析鉴定差异表达的转录本。
确定了 25 个与自发性早产风险增加相关的转录本。使用这些转录本建立了一个逻辑回归模型来预测自发性早产，曲线下面积为 0.80（95%置信区间，0.72-0.87）（敏感性=0.76，特异性=0.72）。通过留一法交叉验证验证了基因发现和模型。从非常早期的自发性早产病例（<25 周，n=14 例，分娩时间为 2.5±1.8 周）中确定了一组独特的 39 个基因；基于这些基因的逻辑回归分类器在留一法交叉验证中产生了 0.76（95%置信区间，0.63-0.87）的曲线下面积。与自发性早产相关的转录本的通路分析显示，最终在<35 周发生自发性早产的患者中，与胶原或细胞外基质相关的基因富集。胰岛素样生长因子转运和氨基酸代谢途径中的基因富集与<25 周的自发性早产有关。
母体血液中妊娠中期游离 RNA 谱提供了一个非侵入性窗口，可以预测自发性早产的未来发生。胶原和细胞外基质途径变化的系统发现可能有助于识别有早产宫颈重塑风险的个体，生长因子和代谢途径更多地与非常早期的自发性早产有关。游离 RNA 谱的使用有可能通过揭示潜在的病理生理学来准确识别自发性早产风险，为更有针对性的治疗和有效干预创造机会。
