title: The translation of lipid profiles to nutritional biomarkers in the study of infant metabolism.
abstract: BACKGROUND
  Links between early life exposures and later health outcomes may, in part, be due tonutritional programmingin infancy. This hypothesis is supported by observed long-term benefits associated with breastfeeding, such as better cognitive development in childhood, and lower risks of obesity and high blood pressure in later life. However, the possible underlying mechanisms are expected to be complex and may be difficult to disentangle due to the lack of understanding of the metabolic processes that differentiate breastfed infants compared to those receiving just formula feed.
  
  
  OBJECTIVE
  Our aim was to investigate the relationships between infant feeding and the lipid profiles and to validate specific lipids in separate datasets so that a small set of lipids can be used as nutritional biomarkers.
  
  
  METHODS
  We utilized a direct infusion high-resolution mass spectrometry method to analyse the lipid profiles of 3.2 mm dried blood spot samples collected at age 3 months from the Cambridge Baby Growth Study (CBGS-1), which formed the discovery cohort. For validation two sample sets were profiled: Cambridge Baby Growth Study (CBGS-2) and Pregnancy Outcome Prediction Study (POPS). Lipidomic profiles were compared between infant groups who were either exclusively breastfed, exclusively formula-fed or mixed-fed at various levels. Data analysis included supervised Random Forest method with combined classification and regression mode. Selection of lipids was based on an iterative backward elimination procedure without compromising the class error in the classification mode.
  
  
  CONCLUSIONS
  From this study, we were able to identify and validate three lipids: PC(35:2), SM(36:2) and SM(39:1) that can be used collectively as biomarkers for infant nutrition during early development. These biomarkers can be used to determine whether young infants (3-6 months) are breast-fed or receive formula milk.
authors.affiliation: MRC Elsie Widdowson Laboratory, Cambridge, UK.|Department of Biochemistry, University of Cambridge, Cambridge, UK.
authors.forename: Animesh
authors.initials: A
authors.lastname: Acharjee
authors.affiliation: Department of Paediatrics, University of Cambridge, Cambridge, UK.
authors.forename: Philippa
authors.initials: P
authors.lastname: Prentice
authors.affiliation: Department of Paediatrics, University of Cambridge, Cambridge, UK.
authors.forename: Carlo
authors.initials: C
authors.lastname: Acerini
authors.affiliation: MRC Elsie Widdowson Laboratory, Cambridge, UK.|School of Food Science and Nutrition, University of Leeds, Leeds, UK.
authors.forename: James
authors.initials: J
authors.lastname: Smith
authors.affiliation: Department of Paediatrics, University of Cambridge, Cambridge, UK.
authors.forename: Ieuan A
authors.initials: IA
authors.lastname: Hughes
authors.affiliation: Department of Paediatrics, University of Cambridge, Cambridge, UK.|MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.
authors.forename: Ken
authors.initials: K
authors.lastname: Ong
authors.affiliation: MRC Elsie Widdowson Laboratory, Cambridge, UK.|Department of Biochemistry, University of Cambridge, Cambridge, UK.
authors.forename: Julian L
authors.initials: JL
authors.lastname: Griffin
authors.affiliation: Department of Paediatrics, University of Cambridge, Cambridge, UK.
authors.forename: David
authors.initials: D
authors.lastname: Dunger
authors.affiliation: MRC Elsie Widdowson Laboratory, Cambridge, UK.|NIHR BRC Clinical Metabolomics and Lipidomics Laboratory, Level 4, Laboratory Block, Cambridge University Hospitals, University of Cambridge, Hills Road, Cambridge, CB2 0QQ UK.
authors.forename: Albert
authors.identifier: 0000-0001-9998-051X
authors.initials: A
authors.lastname: Koulman
keywords: Biomarker discovery; Infant nutrition; Lipidomics; Random Forest