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.
Authors
- Xinye Cao (ORCID: https://orcid.org/0009-0007-0060-6693)
- Xiangwen Peng (ORCID: https://orcid.org/0000-0001-9110-5163)
- Hankui Liu (ORCID: https://orcid.org/0000-0001-7826-0388)
- Huanhuan Peng (ORCID: https://orcid.org/0000-0002-4515-6979)
- Quanze He (ORCID: https://orcid.org/0000-0003-4642-117X)
- Congjun Li (ORCID: https://orcid.org/0000-0003-1389-9820)
- Kangrong Zhao
- Benjing Wang
- Xin Jin (ORCID: https://orcid.org/0000-0001-7554-4975)
- Chunhua Zhang (ORCID: https://orcid.org/0000-0003-0509-4336)
- Ting Wang (ORCID: https://orcid.org/0000-0003-3249-444X)
- Jianguo Zhang (ORCID: https://orcid.org/0000-0003-2315-4822)
- Yuxing He
- Qin Zhang (ORCID: https://orcid.org/0000-0001-5718-526X)
- Ying Xue (ORCID: https://orcid.org/0009-0003-9886-6506)
- Liping Guan
- Qi Wang (ORCID: https://orcid.org/0000-0003-1058-5068)
- Jun Mao
- Xiaojuan Wu (ORCID: https://orcid.org/0000-0002-3803-6661)
- Lijian Zhao (ORCID: https://orcid.org/0009-0002-5472-0639)
- Lu Lu
Institutions
- BGI Group (China) (CN)
- Hebei Medical University (CN)
- Xinjiang Medical University (CN)
- Suzhou Municipal Hospital (CN)
- Changsha Hospital for Maternal and Child Health Care (CN)
- BGI Genomics
Publication Details
- Journal
- Cell Genomics
- Published
- 2024-10-01
- DOI
- https://doi.org/10.1016/j.xgen.2024.100668
- Citations
- 5
- Primary Topic
- Genetic Associations and Epidemiology
- Type
- article
- Field-Weighted Citation Impact
- 2.75
Funders
- Government of Jiangsu Province
- Government of Jiangxi Province
- National Key Research and Development Program of China