Sungsam Gong, Carlo Randise-Hinchliff, Suzanne Rohrback, Jing Yin Weng, Komal Singh, Sarah Shultzaberger, Ulla Sovio, Emma Cook, Fiona Kaper, Gordon C. S. Smith, D. Stephen Charnock-Jones
{"title":"瘦素和Pappalysin2无细胞rna升高是妊娠合并子痫前期胎儿生长受限的标志","authors":"Sungsam Gong, Carlo Randise-Hinchliff, Suzanne Rohrback, Jing Yin Weng, Komal Singh, Sarah Shultzaberger, Ulla Sovio, Emma Cook, Fiona Kaper, Gordon C. S. Smith, D. Stephen Charnock-Jones","doi":"10.1038/s41467-025-61931-7","DOIUrl":null,"url":null,"abstract":"<p>Preeclampsia (PE) and fetal growth restriction (FGR) complicate 5-10% of pregnancies and are major causes of maternal and fetal morbidity and mortality. Here we demonstrate that measuring circulating cell-free RNAs (cfRNAs) from maternal plasma can accurately predict pregnancies complicated by the combination of PE and FGR. We investigated 751 maternal plasma samples from 195 pregnant women (39 cases; 156 non-cases). We developed machine learning models from our discovery cohort (15 cases; 60 non-cases) and evaluated their predictive performances internally (24 cases; 96 controls) and externally (40 cases; 73 non-cases). We found circulating leptin (<i>LEP</i>) and pappalysin2 (<i>PAPPA2</i>) cfRNAs are the strongest cfRNA predictors of complicated pregnancies, each with an area under the receiver operating characteristic curve (AUC) of ~0.82. Using an external validation dataset of women with established PE, the combination of <i>LEP</i> and <i>PAPPA2</i> had an AUC ~0.951. Our findings show that cfRNAs can predict complications of human pregnancy.</p>","PeriodicalId":19066,"journal":{"name":"Nature Communications","volume":"24 1","pages":""},"PeriodicalIF":15.7000,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Raised Leptin and Pappalysin2 cell-free RNAs are the hallmarks of pregnancies complicated by preeclampsia with fetal growth restriction\",\"authors\":\"Sungsam Gong, Carlo Randise-Hinchliff, Suzanne Rohrback, Jing Yin Weng, Komal Singh, Sarah Shultzaberger, Ulla Sovio, Emma Cook, Fiona Kaper, Gordon C. S. Smith, D. Stephen Charnock-Jones\",\"doi\":\"10.1038/s41467-025-61931-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Preeclampsia (PE) and fetal growth restriction (FGR) complicate 5-10% of pregnancies and are major causes of maternal and fetal morbidity and mortality. Here we demonstrate that measuring circulating cell-free RNAs (cfRNAs) from maternal plasma can accurately predict pregnancies complicated by the combination of PE and FGR. We investigated 751 maternal plasma samples from 195 pregnant women (39 cases; 156 non-cases). We developed machine learning models from our discovery cohort (15 cases; 60 non-cases) and evaluated their predictive performances internally (24 cases; 96 controls) and externally (40 cases; 73 non-cases). We found circulating leptin (<i>LEP</i>) and pappalysin2 (<i>PAPPA2</i>) cfRNAs are the strongest cfRNA predictors of complicated pregnancies, each with an area under the receiver operating characteristic curve (AUC) of ~0.82. Using an external validation dataset of women with established PE, the combination of <i>LEP</i> and <i>PAPPA2</i> had an AUC ~0.951. Our findings show that cfRNAs can predict complications of human pregnancy.</p>\",\"PeriodicalId\":19066,\"journal\":{\"name\":\"Nature Communications\",\"volume\":\"24 1\",\"pages\":\"\"},\"PeriodicalIF\":15.7000,\"publicationDate\":\"2025-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature Communications\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1038/s41467-025-61931-7\",\"RegionNum\":1,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Communications","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41467-025-61931-7","RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
Raised Leptin and Pappalysin2 cell-free RNAs are the hallmarks of pregnancies complicated by preeclampsia with fetal growth restriction
Preeclampsia (PE) and fetal growth restriction (FGR) complicate 5-10% of pregnancies and are major causes of maternal and fetal morbidity and mortality. Here we demonstrate that measuring circulating cell-free RNAs (cfRNAs) from maternal plasma can accurately predict pregnancies complicated by the combination of PE and FGR. We investigated 751 maternal plasma samples from 195 pregnant women (39 cases; 156 non-cases). We developed machine learning models from our discovery cohort (15 cases; 60 non-cases) and evaluated their predictive performances internally (24 cases; 96 controls) and externally (40 cases; 73 non-cases). We found circulating leptin (LEP) and pappalysin2 (PAPPA2) cfRNAs are the strongest cfRNA predictors of complicated pregnancies, each with an area under the receiver operating characteristic curve (AUC) of ~0.82. Using an external validation dataset of women with established PE, the combination of LEP and PAPPA2 had an AUC ~0.951. Our findings show that cfRNAs can predict complications of human pregnancy.
期刊介绍:
Nature Communications, an open-access journal, publishes high-quality research spanning all areas of the natural sciences. Papers featured in the journal showcase significant advances relevant to specialists in each respective field. With a 2-year impact factor of 16.6 (2022) and a median time of 8 days from submission to the first editorial decision, Nature Communications is committed to rapid dissemination of research findings. As a multidisciplinary journal, it welcomes contributions from biological, health, physical, chemical, Earth, social, mathematical, applied, and engineering sciences, aiming to highlight important breakthroughs within each domain.