DescriptionIntroduction: Early life is a major determinant for the development of the immune system and the overall health for the entire human lifespan. However, our knowledge of the development of the neonatal immune system is incomplete. This limits the success of preventative, diagnostic, and therapeutic interventions, especially in newborns where death caused by infections are most common due to an immature immune system.
Methods: Blood-plasma samples were collected from 30 newborns in Gambia at the day of birth (Day 0) and at a follow-up visit on Day 1, 3 or 7. A similar cohort was collected in Papua New Guinea (PNG) for validation. We characterized the plasma proteome using only 1 μL of plasma. In brief, the samples were prepared in a 96-well format, and the generated peptides were analyzed by LC-MS using a Q Exactive high resolution/high accuracy mass spectrometer. To identify significantly changed proteins and biological schemes in this detailed analysis of the data, we established an advanced bioinformatic analysis pipeline in R. In silico analysis, employing a workflow beyond that commonly applied to proteomics, included linear mixed modelling and Fisher’s exact testing.
Conclusion: A cutting edge sample-sparing plasma proteomics platform using only 1 μL of plasma reveals significant and consistent changes to the plasma proteome across the first week of human life. Several of the changing proteins demonstrate development of the innate- and adaptive immune system, which can be detected as early as 24 hours after birth. Characterization of the plasma proteome may provide fresh insight into immune ontogeny and inform new approaches to prevent, detect and treat infectious diseases.
|Period||18 Oct 2019|
|Event title||International Precision Vaccines Conference|
|Location||Boston, United States, Massachusetts|
|Degree of Recognition||International|
- big data
- machine learning
- immune system
Dynamic molecular changes during the first week of human life follow a robust developmental trajectory
Research output: Contribution to journal › Journal article › Research › peer-review