丹麦哥本哈根大学Mads Melbye、美国斯坦福大学Michael Snyder等研究人员合作揭示了人类怀孕过程中的代谢动态变化。该研究于2020年6月25日发表于《细胞》。
Title: Metabolic Dynamics and Prediction of Gestational Age and Time to Delivery in Pregnant Women
Author: Liang Liang, Marie-Louise Hee Rasmussen, Brian Piening, Xiaotao Shen, Songjie Chen, Hannes Rst, John K. Snyder, Robert Tibshirani, Line Skotte, Norman CY. Lee, Kévin Contrepois, Bjarke Feenstra, Hanyah Zackriah, Michael Snyder, Mads Melbye
Abstract: Metabolism during pregnancy is a dynamic and precisely programmed process, the failure of which can bring devastating consequences to the mother and fetus. To define a high-resolution temporal profile of metabolites during healthy pregnancy, we analyzed the untargeted metabolome of 784 weekly blood samples from 30 pregnant women. Broad changes and a highly choreographed profile were revealed: 4,995 metabolic features (of 9,651 total), 460 annotated compounds (of 687 total), and 34 human metabolic pathways (of 48 total) were significantly changed during pregnancy. Using linear models, we built a metabolic clock with five metabolites that time gestational age in high accordance with ultrasound (R = 0.92). Furthermore, two to three metabolites can identify when labor occurs (time to delivery within two, four, and eight weeks, AUROC ≥ 0.85). Our study represents a weekly characterization of the human pregnancy metabolome, providing a high-resolution landscape for understanding pregnancy with potential clinical utilities.
本期文章：《细胞》：Volume 181 Issue 7