Anna Fedyukova

Human milk contains a variety of biologically active molecules that are essential for infant growth and development, as well as indicators of maternal health. However, understanding the full potential of these molecules is challenging due to variations in their concentrations among mothers, potential degradation during sample handling and storage, and the limited accessibility of specific human milk analyses. This study aimed to evaluate the effectiveness of a freeze-dried preservative cocktail in maintaining the stability of key milk molecules during collection, transport, and storage. GenV participants (n = 96) were given a sample collection kit and followed the instructions to collect approximately 5 mL of breast milk, which was placed in a collection tube containing the preservative. The samples were mailed at ambient temperature to the GenV laboratory (Murdoch Children’s Research Institute, Melbourne, Victoria, Australia), where they were aliquoted into 1 mL tubes using a liquid handling system (Janus) and stored at −80 °C. These samples were randomly selected and sent to The University of Western Australia (Perth, Western Australia, Australia) on dry ice for biochemical analysis. The average collection day postpartum was 16 ± 14 (range 1–91 days), while the average postal receipt time was 5 ± 3 days (range 1–16 days), and samples were processed within 6 days of receipt (average 3 ± 2 days). The mean concentrations of key molecules—fat (48.6 ± 17.1 g/L), protein (15.5 ± 4.3 g/L), lactose (78.9 ± 13.9 g/L), glucose (0.17 ± 0.17 g/L), lysozyme (0.16 ± 0.16 g/L), and insulin (6.1 ± 4.9 μIU/mL)—were consistent with reported literature values. There were no statistically significant differences in molecular concentrations based on postal transit time, receipt, or processing delays (p > 0.05). These results demonstrate that the preservative cocktail effectively preserved the integrity of key molecules in human milk during handling, postal transport, and storage at ambient temperature. The findings support its use as a valuable tool for human milk research, enabling more flexible sample collection and handling without compromising the quality of the milk or the biochemical analysis. Future research should explore its application in broader contexts to further enhance the accuracy and reliability of milk composition studies across diverse research settings.

Linking very large, consented birth cohorts to birthing hospitals clinical data could elucidate the lifecourse outcomes of health care and exposures during the pregnancy, birth and newborn periods. Unfortunately, cohort personally identifiable information (PII) often does not include unique identifier numbers, presenting matching challenges. To develop optimized cohort matching to birthing hospital clinical records, this pilot drew on a one-year (December 2020–December 2021) cohort for a single Australian birthing hospital participating in the whole-of-state Generation Victoria (GenV) study. For 1819 consented mother-baby pairs and 58 additional babies (whose mothers were not themselves participating), we tested the accuracy and effort of various approaches to matching. We selected demographic variables drawn from names, DOB, sex, telephone, address (and birth order for multiple births). After variable standardization and validation, accuracy rose from 10% to 99% using a deterministic-rule-based approach in 10 steps. Using cohort-specific modifications of the Australian Statistical Linkage Key (SLK-581), it took only 3 steps to reach 97% (SLK-5881) and 98% (SLK-5881.1) accuracy. We conclude that our SLK-5881 process could safely and efficiently achieve high accuracy at the population level for future birth cohort-birth hospital matching in the absence of unique identifier numbers.