Significance: Infants born of very low birth weight (VLBW) account for 50% of all long-term neurological
morbidity among North American children; they commonly have sub-optimal growth and life threatening
morbidities such as necrotising enterocolitis and sepsis. It is now widely recognized that human milk (HM)
feeding is the best strategy to prevent serious morbidity in VLBW infants, yet growth and neurodevelopment
often remain sub-optimal with current one-size-fits-all feeding regimes. There is increasing interest in
“precision nutrition” approaches, but it is unclear which HM components require personalized titration.
Previous efforts have focused on macronutrients, but HM also contains essential micronutrients as well as non-
nutrient bioactive components that shape the gut microbiome. Further, it is unclear if or how parental factors
(e.g. stress, body mass index, diet) and infant factors (e.g. genetics, gut microbiota, sex, acuity) influence
relationships between early nutrition and growth, neurodevelopment and morbidity. Understanding these
complex relationships is paramount to developing effective personalized HM feeding strategies for VLBW
infants. This is the overarching goal of the proposed Optimizing Nutrition and Milk (Opti-NuM) Project.
Approach: We will leverage two established research platforms led by PIs of this grant: 1) the Maximizing
Mother’s Milk (MaxiMoM) Program with its neonatal feeding trial network and 2) the International
Milk Composition (IMiC) Consortium. This partnership unites the comprehensive nutrition and clinical
data (daily feed volumes and composition) and pristinely collected biospecimens from MaxiMoM (n=1105)
with the systems biology and machine learning pipelines from IMiC Consortium. We aim to define optimal
nutrient intake ranges (Aim 1) and microbially-relevant non-nutrient intake profiles (Aim 2) associated with
optimal growth and neurodevelopment and low risk of serious morbidity in different clinical sub-populations
of HM-fed VLBW infants. Additionally, we will explore the role of infant gut microbiota, infant genetics and
parent stress in associations between early nutrition and growth, neurodevelopment and morbidity (Aim 3).
Innovation: The MaxiMoM platform is unique in the world in terms of size, scope of nutritional data,
biobanked samples and longitudinal follow up data. The IMiC Consortium approach to studying HM as a
biological system using sophisticated modelling and machine learning approaches is pushing the boundaries of
HM research. Combined, these platforms offer an unparalleled opportunity to decipher how HM supports the
growth and development of VLBW infants, and to accelerate the development of novel precision nutrition
approaches for this vulnerable population.