Investigating the Metabolic Model in Preterm Neonates by Tandem Mass Spectrometry: A Cohort Study

Author:

Wang Benjing1,Zhang Qin1,Wang Qi1,Ma Jun1,Cao Xiaoju1,Chen Yaping1,Pan Yuhong1,Li Hong1,Xiang Jingjing1,Wang Ting1

Affiliation:

1. Center for Reproduction and Genetic, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China

Abstract

AbstractThe changes of metabolite profiles in preterm birth have been demonstrated using newborn screening data. However, little is known about the holistic metabolic model in preterm neonates. The aim was to investigate the holistic metabolic model in preterm neonates. All metabolite values were obtained from a cohort data of routine newborn screening. A total of 261 758 newborns were recruited and randomly divided into a training subset and a testing subset. Using the training subset, 949 variates were considered to establish a logistic regression model for identifying preterm birth (<37 weeks) from term birth (≥37 weeks). Sventy-two variates (age at collection, TSH, 17α-OHP, proline, tyrosine, C16:1-OH, C18:2, and 65 ratios) entered into the final metabolic model for identifying preterm birth from term birth. Among the variates entering into the final model of PTB [Leucine+Isoleucine+Proline-OH)/Valine (OR=38.36], (C3DC+C4-OH)/C12 (OR=15.58), Valine/C5 (OR=6.32), [Leucine+isoleucine+Proline-OH)/Ornithine (OR=2.509)], and Proline/C18:1 (OR=2.465) have the top five OR values, and [Leucine+Isoleucine+Proline-OH)/C5 (OR=0.05)], [Leucine+Isoleucine+Proline-OH)/Phenylalanine (OR=0.214)], proline/valine (OR=0.230), C16/C18 (OR=0.259), and Alanine/free carnitine (OR=0.279) have the five lowest OR values. The final metabolic model had a capacity of identifying preterm infants with >80% accuracy in both the training and testing subsets. When identifying neonates ≤32 weeks from those >32 weeks, it had a robust performance with nearly 95% accuracy in both subsets. In summary, we have established an excellent metabolic model in preterm neonates. These findings could provide new insights for more efficient nutrient supplements and etiology of preterm birth.

Funder

Suzhou Key Medical Center

Jiangsu Maternal and Children health care research project

Jiangsu Provincial Medical Innovation Team

Suzhou Clinical Medical Expert Team

Jiangsu Maternal and Children health care key discipline

Suzhou Science and Technology Support Program

Publisher

Georg Thieme Verlag KG

Subject

Biochemistry, medical,Clinical Biochemistry,Endocrinology,Biochemistry,General Medicine,Endocrinology, Diabetes and Metabolism

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3