Clinical Manifestations of Neonatal Hyperbilirubinemia Are Related to Alterations in the Gut Microbiota

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Abstract
Background and purpose: Neonatal hyperbilirubinemia, also known as neonatal jaundice, is a common and frequent clinical condition with a complex etiology that can lead to brain damage in severe cases. Early recognition of hyperbilirubinemia and timely intervention and treatment can help reduce the occurrence of sequelae. This study was conducted to identify whether the gut microbiota composition can distinguish neonates with hyperbilirubinemia. Methods: Meconium samples were collected from 69 neonates with neonatal jaundice (NJ) and 69 age- and sex-matched neonates without clinically significant jaundice (healthy controls; HCs) for 16S rRNA gene sequencing and microbiome analysis. Results: Compared with HCs, the Chao 1 richness index of the gut microbiota was significantly decreased in the NJ group. The relative abundance of the probiotic gut bacterium, Lactobacillus, was significantly lower in the NJ group than in the HC group, whereas the abundances of potentially harmful gut bacteria, such as Escherichia coli and Staphylococcus, were significantly higher in the NJ group than in HCs. Correlation of the gut microbiota and clinical indicators revealed a positive correlation between Escherichia coli/Staphylococcus and serum total bilirubin levels. Finally, the results of a random forest machine-learning method to evaluate the possibility of using NJ-associated gut microbiota compositions as potential NJ biomarkers revealed an area under the curve of 96.88%. Conclusions: The abundances of Escherichia coli and Staphylococcus were positively correlated with serum total bilirubin levels. Hence, the gut microbiota composition is a potential biomarker of NJ.
Funding Information
  • National Natural Science Foundation of China (82071733, HLPM201907020103, 2020115, JCYJ20190807152403624, LGKCYLWS2021000006)
  • High level Project of Medicine of Longhua (82071733, HLPM201907020103, 2020115, JCYJ20190807152403624, LGKCYLWS2021000006)
  • Shanghai Talent Development Funding (82071733, HLPM201907020103, 2020115, JCYJ20190807152403624, LGKCYLWS2021000006)
  • Shenzhen Science Technology and Innovation Commission (82071733, HLPM201907020103, 2020115, JCYJ20190807152403624, LGKCYLWS2021000006)
  • Longgang Science Technology (82071733, HLPM201907020103, 2020115, JCYJ20190807152403624, LGKCYLWS2021000006)

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