Small Sample-Big Data: Integrative Indexed Systems Biology Reveals Dramatic Molecular Ontogeny over the First Week of Human Life

Systems biology provides a powerful approach to unravel complex biological processes yet it has not been applied systematically to samples from newborns, a group highly vulnerable to a wide range of diseases. Published methods rely on blood volumes that are not feasible to obtain from newborns. We optimized methods to extract transcriptomic, proteomic, metabolomic, cytokine/chemokine, and single cell immune phenotyping data from <1ml of blood, a volume readily obtained from newborns. Furthermore, indexing to baseline and applying innovative integrative computational methods that address the challenge of few data points with many features enabled identification of robust findings within a readily achievable sample size. This approach uncovered dramatic changes along a stable developmental trajectory over the first week of life. The ability to extract information from 'big data' and draw key insights from such small sample volumes will enable and accelerate characterization of the molecular ontogeny driving this crucial developmental period. Overall design: This study examines the global transcriptomic profiles in peripheral blood of newborns at birth (D0) comparing with follow up at day 1 (D1), day 3 (D3), or day 7 (D7) post birth. Contributor: Expanded Program on Immunization Consortium (EPIC)