新生儿代谢物的全基因组关联研究。

IF 11.1 Q1 CELL BIOLOGY
Quanze He, Hankui Liu, Lu Lu, Qin Zhang, Qi Wang, Benjing Wang, Xiaojuan Wu, Liping Guan, Jun Mao, Ying Xue, Chunhua Zhang, Xinye Cao, Yuxing He, Xiangwen Peng, Huanhuan Peng, Kangrong Zhao, Hong Li, Xin Jin, Lijian Zhao, Jianguo Zhang, Ting Wang
{"title":"新生儿代谢物的全基因组关联研究。","authors":"Quanze He, Hankui Liu, Lu Lu, Qin Zhang, Qi Wang, Benjing Wang, Xiaojuan Wu, Liping Guan, Jun Mao, Ying Xue, Chunhua Zhang, Xinye Cao, Yuxing He, Xiangwen Peng, Huanhuan Peng, Kangrong Zhao, Hong Li, Xin Jin, Lijian Zhao, Jianguo Zhang, Ting Wang","doi":"10.1016/j.xgen.2024.100668","DOIUrl":null,"url":null,"abstract":"<p><p>Genetic factors significantly influence the concentration of metabolites in adults. Nevertheless, the genetic influence on neonatal metabolites remains uncertain. To bridge this gap, we employed genotype imputation techniques on large-scale low-pass genome data obtained from non-invasive prenatal testing. Subsequently, we conducted association studies on a total of 75 metabolic components in neonates. The study identified 19 previously reported associations and 11 novel associations between single-nucleotide polymorphisms and metabolic components. These associations were initially found in the discovery cohort (8,744 participants) and subsequently confirmed in a replication cohort (19,041 participants). The average heritability of metabolic components was estimated to be 76.2%, with a range of 69%-78.8%. These findings offer valuable insights into the genetic architecture of neonatal metabolism.</p>","PeriodicalId":72539,"journal":{"name":"Cell genomics","volume":"4 10","pages":"100668"},"PeriodicalIF":11.1000,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A genome-wide association study of neonatal metabolites.\",\"authors\":\"Quanze He, Hankui Liu, Lu Lu, Qin Zhang, Qi Wang, Benjing Wang, Xiaojuan Wu, Liping Guan, Jun Mao, Ying Xue, Chunhua Zhang, Xinye Cao, Yuxing He, Xiangwen Peng, Huanhuan Peng, Kangrong Zhao, Hong Li, Xin Jin, Lijian Zhao, Jianguo Zhang, Ting Wang\",\"doi\":\"10.1016/j.xgen.2024.100668\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Genetic factors significantly influence the concentration of metabolites in adults. Nevertheless, the genetic influence on neonatal metabolites remains uncertain. To bridge this gap, we employed genotype imputation techniques on large-scale low-pass genome data obtained from non-invasive prenatal testing. Subsequently, we conducted association studies on a total of 75 metabolic components in neonates. The study identified 19 previously reported associations and 11 novel associations between single-nucleotide polymorphisms and metabolic components. These associations were initially found in the discovery cohort (8,744 participants) and subsequently confirmed in a replication cohort (19,041 participants). The average heritability of metabolic components was estimated to be 76.2%, with a range of 69%-78.8%. These findings offer valuable insights into the genetic architecture of neonatal metabolism.</p>\",\"PeriodicalId\":72539,\"journal\":{\"name\":\"Cell genomics\",\"volume\":\"4 10\",\"pages\":\"100668\"},\"PeriodicalIF\":11.1000,\"publicationDate\":\"2024-10-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cell genomics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.xgen.2024.100668\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CELL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cell genomics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.xgen.2024.100668","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

遗传因素对成人代谢物的浓度有很大影响。然而,遗传因素对新生儿代谢物的影响仍不确定。为了弥补这一差距,我们在无创产前检测获得的大规模低通基因组数据上采用了基因型推算技术。随后,我们对新生儿的 75 种代谢成分进行了关联研究。研究在单核苷酸多态性与代谢成分之间发现了 19 种先前报道过的关联和 11 种新的关联。这些关联最初是在发现队列(8,744 名参与者)中发现的,随后在复制队列(19,041 名参与者)中得到证实。代谢成分的平均遗传率估计为 76.2%,范围在 69%-78.8% 之间。这些发现为新生儿代谢的遗传结构提供了宝贵的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A genome-wide association study of neonatal metabolites.

Genetic factors significantly influence the concentration of metabolites in adults. Nevertheless, the genetic influence on neonatal metabolites remains uncertain. To bridge this gap, we employed genotype imputation techniques on large-scale low-pass genome data obtained from non-invasive prenatal testing. Subsequently, we conducted association studies on a total of 75 metabolic components in neonates. The study identified 19 previously reported associations and 11 novel associations between single-nucleotide polymorphisms and metabolic components. These associations were initially found in the discovery cohort (8,744 participants) and subsequently confirmed in a replication cohort (19,041 participants). The average heritability of metabolic components was estimated to be 76.2%, with a range of 69%-78.8%. These findings offer valuable insights into the genetic architecture of neonatal metabolism.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
7.10
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信