Evidence mapPaperPMID 39389019Full record

ArticleCell genomics2024

A genome-wide association study of neonatal metabolites.

Quanze He, Hankui Liu, Lu Lu, Qin Zhang, Qi Wang, Benjing Wang, Xiaojuan Wu, Liping Guan, Jun Mao, Ying Xue and 11 more

Abstract read
In one paragraph

Article in Cell genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors.

Quanze HeThe Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China; Suzhou Municipal Hospital, Suzhou Jiangsu 215000, China.
Hankui LiuHebei Industrial Technology Research Institute of Genomics in Maternal & Child Health, Clin Lab, BGI Genomics, Shijiazhuang 050035, China; BGI Genomics, Shenzhen 518083, China.
Lu LuThe Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China.
Qin ZhangThe Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China.
Qi WangThe Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China.
Benjing WangThe Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China.
Xiaojuan WuThe Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China.
Liping GuanHebei Industrial Technology Research Institute of Genomics in Maternal & Child Health, Clin Lab, BGI Genomics, Shijiazhuang 050035, China; BGI Genomics, Shenzhen 518083, China.
Jun MaoThe Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China.
Ying XueThe Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China.
Chunhua ZhangThe Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China.
Xinye CaoClinical Medicine Department, Xinjiang Medical University, Urumqi, Xinjiang Province 830054, China.
Yuxing HeClinical Medicine Department, Xinjiang Medical University, Urumqi, Xinjiang Province 830054, China.
Xiangwen PengChangsha Hospital for Maternal and Child Health Care of Hunan Normal University, Changsha, Hunan Province 431005, China.
Huanhuan PengBGI Genomics, Shenzhen 518083, China.
Kangrong ZhaoThe Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China.
Hong LiThe Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China.
Xin JinBGI Research, Shenzhen 518083, China; The Innovation Centre of Ministry of Education for Development and Diseases, School of Medicine, South China University of Technology, Guangzhou 510006, China; Shanxi Medical University-BGI Collaborative Center for Future Medicine, Shanxi Medical University, Taiyuan 030001, China; Shenzhen Key Laboratory of Transomics Biotechnologies, BGI Research, Shenzhen 518083, China. Electronic address: jinxin@genomics.cn.
Lijian ZhaoHebei Industrial Technology Research Institute of Genomics in Maternal & Child Health, Clin Lab, BGI Genomics, Shijiazhuang 050035, China; BGI Genomics, Shenzhen 518083, China; Medical Technology College, Hebei Medical University, Shijiazhuang 050000, China. Electronic address: zhaolijian@genomics.cn.
Jianguo ZhangHebei Industrial Technology Research Institute of Genomics in Maternal & Child Health, Clin Lab, BGI Genomics, Shijiazhuang 050035, China; BGI Research, Shenzhen 518083, China; School of Public Health, Hebei Medical University, Shijiazhuang 050000, China. Electronic address: zhangjg@genomics.cn.
Ting WangThe Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province 215000, China; Suzhou Municipal Hospital, Suzhou Jiangsu 215000, China. Electronic address: biowt@njmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Genome-Wide Association StudyPolymorphism, Single NucleotideCohort StudiesFemaleGenotypeHumansInfant, NewbornMaleMetabolomegenome-wide association studygenotype imputationheritabilitylow-pass whole-genome sequencingneonatal metabolismnon-invasive prenatal testing

Identifiers

PMID39389019
PMCPMC11602626

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.