# Chronology, Maternal Determinants, and Impact of Feeding Mode on Human Milk: A Systems Biology and Ecological Approach

> **NIH NIH R56** · UNIVERSITY OF ROCHESTER · 2022 · $77,000

## Abstract

Human milk (HM) is a “live tissue”: its composition changes over time including diurnal fluctuations,
answering the evolving needs of the infant and programming infants' “biological clock” and physiology. Despite
its extraordinary importance, little is known about the chronobiology and system biology of HM, the maternal
factors that impact this biology, and the mechanisms that underlie its contribution to normal infant development.
It is also unknown how infant input (via suckling) influences HM biology, a crucial question given the almost
universal practice of feeding expressed (ie: pumped) HM. As such, our over-arching hypothesis is that HM is an
ecological system that harbors distinct diurnal and longitudinal variation that is impacted by both maternal fixed
and modifiable factors, and by infant input, resulting in different HM biological dynamics depending on if the
infant is primarily fed at-the-breast vs expressed HM. Our interdisciplinary team of HM researchers and
computational biologists will collect daily longitudinal and diurnal HM samples, and extensive metadata from 120
mothers exclusively feeding HM to their healthy infants between 1-4 months postpartum: 60 mothers primarily
feeding ATB (ATB group) and 60 mothers exclusively expressing HM (Express group). Multi-omics analytical
platforms will be used to characterize HM hormones (insulin, leptin, cortisol), macronutrients, microbiota,
oligosaccharides, cytokines, and immunoglobulins to study HM as an ecological system. This novel high-
resolution sampling combined with cutting-edge analytical and modeling techniques power these aims:
 1) Detect temporal changes in HM composition diurnally and longitudinally and compare these
 trajectories between ATB vs express groups. Time-series models and state-of-the-art analytic
 approaches will be utilized to infer latent HM dynamics and identify temporal trajectories, for the first time,
 identifying longitudinal and 24-hour temporal patterns in HM composition. We will then determine how these
 trajectories differ when infant “biofeedback” into the HM system is lacking by comparing trajectories between
 ATB vs Express Groups.
 2) Identify maternal determinants of HM composition and temporal patterns. In addition to
 sociodemographic and health factors, mobile phone apps and wearable devices will be utilized to capture
 granular data on HM expression patterns, maternal diet, stress, physical activity and sleep patterns. These
 will be linked with “clades” of HM components that co-vary together over time via Bayesian supervised
 machine learning algorithms. The algorithm will distinguish if relationships between maternal factors and
 HM composition and dynamics differs between ATB vs Express groups.
This work will elucidate mechanisms underlying HM contribution to infant health and development, allowing for
optimized feeding practices for infants fed ATB or expressed HM, and premature infants dependent on
expressed HM. This study also represents...

## Key facts

- **NIH application ID:** 10531705
- **Project number:** 1R56HD109837-01
- **Recipient organization:** UNIVERSITY OF ROCHESTER
- **Principal Investigator:** Bridget E Young
- **Activity code:** R56 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $77,000
- **Award type:** 1
- **Project period:** 2022-09-08 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10531705

## Citation

> US National Institutes of Health, RePORTER application 10531705, Chronology, Maternal Determinants, and Impact of Feeding Mode on Human Milk: A Systems Biology and Ecological Approach (1R56HD109837-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10531705. Licensed CC0.

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