Maternal Metals/Metalloid Blood Levels Are Associated With Lipidomic Profiles Among Pregnant Women in Puerto Rico

FRONTIERS IN PUBLIC HEALTH(2022)

引用 4|浏览17
暂无评分
摘要
Background/Aim: The association between heavy metal exposure and adverse birth outcomes is well-established. However, there is a paucity of research identifying biomarker profiles that may improve the early detection of heavy metal-induced adverse birth outcomes. Because lipids are abundant in our body and associated with important signaling pathways, we assessed associations between maternal metals/metalloid blood levels with lipidomic profiles among 83 pregnant women in the Puerto Rico PROTECT birth cohort.Methods: We measured 10 metals/metalloid blood levels during 24-28 weeks of pregnancy. Prenatal plasma lipidomic profiles were identified by liquid chromatography-mass spectrometry-based shotgun lipidomics. We derived sums for each lipid class and sums for each lipid sub-class (saturated, monounsaturated, polyunsaturated), which were then regressed on metals/metalloid. False discovery rate (FDR) adjusted p-values (q-values) were used to account for multiple comparisons.Results: A total of 587 unique lipids from 19 lipid classes were profiled. When controlling for multiple comparisons, we observed that maternal exposure to manganese and zinc were negatively associated with plasmenyl-phosphatidylethanolamine (PLPE), particularly those containing polyunsaturated fatty acid (PUFA) chains. In contrast to manganese and zinc, arsenic and mercury were positively associated with PLPE and plasmenyl-phosphatidylcholine (PLPC).Conclusion: Certain metals were significantly associated with lipids that are responsible for the biophysical properties of the cell membrane and antioxidant defense in lipid peroxidation. This study highlighted lipid-metal associations and we anticipate that this study will open up new avenues for developing diagnostic tools.
更多
查看译文
关键词
metals, metalloid, lipidomics, pregnancy, Puerto Rico
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要