Research found genetic factors linked to baby's metabolism and long-term health | BGI Insight
2024-10-14
A series of large cohort studies revealed genetic factors affecting maternal and neonatal metabolite levels, potentially guiding personalized approaches in managing pregnancy and newborn health.
The research was led by BGI Genomics, in collaboration with multiple research institutes such as the Affiliated Suzhou Hospital of Nanjing Medical University, Wuhan Maternal and Child Health Care Hospital, and more. It was published in Cell Genomics Journal in October 2024.
One of the key findings of this research series emphasizes the intricate relationship between a mother’s health and her newborn’s metabolic profile. The researchers employed advanced genotype imputation techniques on large-scale low-pass genome data obtained from non-invasive prenatal testing (NIPT).
This allowed them to gain a detailed understanding of how genetic variants can influence the metabolism of newborns. In simpler terms, they could predict certain aspects of a baby's health using genetic data collected from expectant mothers during routine prenatal tests.
Genetic Discoveries Linked to Newborn Metabolism
Figure 1. Graphical abstract of the neonatal metabolism study
A significant aspect of the study was a genome-wide association study (GWAS) that revealed how genetic factors, as well as maternal characteristics like age, height, and body mass index (BMI), neonatal traits like weight and sex, play crucial roles in shaping a newborn’s metabolic health. This study, encompassing over 27,000 participants across discovery and replication cohorts, identified 30 genetic associations related to neonatal metabolism. These included 19 previously known associations and 11 new discoveries.
Among these, 16 genes such as ACADM, CPT2, CRAT, and PTPA have known roles in metabolism, while nine new genes—like BCL7A, MSH4, and CYP4A11—were found to be associated with various metabolic components. Two novel genetic associations, involving the genes TM9SF4 and LRP8, add to the growing understanding of how genetic factors influence newborn health. These associations' discovery underscores the potential of maternal genetic data in predicting neonatal health outcomes.
Personalized Nutrition for Expecting Mothers
Figure 2. Overview of the 104 pregnancy metabolism phenotypes
The implications of these findings go beyond identifying genetic markers—they pave the way for more customized approaches to pregnancy nutrition. While many pregnant women take multivitamins, this series of studies revealed that expectant mothers’ nutritional needs can vary significantly based on their genetic makeup. The researchers identified 84 metabolic indicators during pregnancy, such as amino acids and vitamins, and found genetic links to 53 of these, including 23 newly discovered genes.
Interestingly, the study showed that the genetic influences on certain metabolites differed between younger and older pregnant women, as well as between pregnant and non-pregnant individuals. This suggests that a more tailored approach to nutritional supplementation could benefit mothers, helping to optimize their health during pregnancy and beyond. By aligning dietary recommendations with genetic insights, doctors can help mothers reduce the risk of complications and promote better outcomes for both mother and baby.
Pregnancy-Specific Genetic Associations
Figure 3. Graphical abstract of the pregnancy phenotype paper
The studies further explored genetic associations with over 100 pregnancy traits in more than 20,000 Chinese women, identifying 410 trait-locus associations. Of these, 31 associations were found to be potentially pregnancy-specific, revealing unique genetic influences that may only be active during pregnancy. For example, associations between creatine levels and specific genes like ESR1 highlight the complex interplay between a mother’s body and the developing fetus.
This deeper understanding of genetic markers in pregnancy provides a scientific basis for interpreting how different genetic factors influence pregnancy-related changes. The research also found that these genetic associations were particularly enriched in pathways related to estrogen and female reproductive tissues, further emphasizing their importance in pregnancy health.
Prof. Zhang Jianguo and researcher Dr. Liu Hankui from the Institute of Intelligent Medical Research (IIMR) of BGI Genomics, co-authors of the neonatal metabolites study (A genome-wide association study of neonatal metabolites) shared their views on maternal and child health genetics research. Dr. Liu stated, “NIPT genetic data have been successfully utilized in genetic studies of maternal height, BMI, and pregnancy traits; we now extend this to neonatal traits.”
Prof. Zhang looked into the future and suggested, “We predict that once these datasets are linked, neonatal weights at different developmental times and neonatal growth, long-term health, and genetic-environmental interaction will also be investigated using the NIPT array.”
As science advances, the vision of personalized maternal and neonatal care becomes increasingly attainable, offering new hope for mothers and children. By leveraging genetic information, healthcare providers can develop more targeted strategies for preventing birth defects and managing pregnancy complications. The research also provides a foundation for future studies that could explore how these genetic factors interact with environmental factors like diet, stress, and lifestyle.
The series of studies include:
1. Genome-wide association study of maternal plasma metabolites during pregnancy
2. A genome-wide association study of neonatal metabolites
5. Utilizing non-invasive prenatal test sequencing data for human genetic investigation
About BGI Genomics
BGI Genomics, headquartered in Shenzhen, China, is the world's leading integrated solutions provider of precision medicine. Its services cover more than 100 countries and regions, involving more than 2,300 medical institutions and 10,000 employees worldwide. In July 2017, as a subsidiary of BGI Group, BGI Genomics (300676.SZ) officially began trading on the Shenzhen Stock Exchange.