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In the published article, there was an error. The data processing was carried out without setting the fixed propionamide modification for cysteines. In the sample preparation carried out in our study, proteins were reduced and alkylated before tryptic digestion and analysis. This resulted in the modification of the cysteine residues within the sequence. After the nontargeted analysis, this modification should have been taken into account in the settings of the data processing in order to correctly identify all tryptic peptides. The error was that this modification was not set in the software, which resulted in false negative identification of peptides with cysteine residues. Consequently, the identification of proteins was only based on tryptic peptides with unmodified cysteines in their sequence, and proteins rich in cysteines were therefore also identified less. After discovering this error, we reprocessed the raw data, setting the fixed modification in the data processing software. Although this reprocessing resulted in increased identification of cysteine-rich proteins and, consequently, in differences in numbers, tables, figures, and supplementary material, the discussion and conclusions of the article remain the same. Corrections have been made to Materials and methods, Statistical methods, Missing data. This sentence previously stated: In practice this resulted in a minimum of 66 and a median of 215 valid values. The corrected sentence appears below: In practice this resulted in a minimum of 49 and a median of 209 valid values. Corrections have been made to Materials and methods, Statistical methods, Principal component analysis. This sentence previously stated: For unsupervised data exploration, Principal Component Analysis (PCA) (40) was applied on the 300 × 647 data matrix (samples × proteins), using the FactoMineR package for R (41). The corrected sentence appears below:.

Human milk is a highly complex liquid food tailor-made to match an infant’s needs. Beyond documented positive effects of breastfeeding on infant and maternal health, there is increasing evidence that milk constituents also impact child neurodevelopment. Non-nutrient milk bioactives would contribute to the (long-term) development of child cognition and behavior, a process termed ‘Lactocrine Programming’. In this review we discuss the current state of the field on human milk composition and its links with child cognitive and behavioral development. To promote state-of-the-art methodologies and designs that facilitate data pooling and meta-analytic endeavors, we present detailed recommendations and best practices for future studies. Finally, we determine important scientific gaps that need to be filled to advance the field, and discuss innovative directions for future research. Unveiling the mechanisms underlying the links between human milk and child cognition and behavior will deepen our understanding of the broad functions of this complex liquid food, as well as provide necessary information for designing future interventions.

Human milk is a highly complex liquid food tailor-made to match an infant's needs. Beyond documented positive effects of breastfeeding on infant and maternal health, there is increasing evidence that milk constituents also impact child neurodevelopment. Non-nutrient milk bioactives would contribute to the (long-term) development of child cognition and behavior, a process termed 'Lactocrine Programming'. In this review we discuss the current state of the field on human milk composition and its links with child cognitive and behavioral development. To promote state-of-the-art methodologies and designs that facilitate data pooling and meta-analytic endeavors, we present detailed recommendations and best practices for future studies. Finally, we determine important scientific gaps that need to be filled to advance the field, and discuss innovative directions for future research. Unveiling the mechanisms underlying the links between human milk and child cognition and behavior will deepen our understanding of the broad functions of this complex liquid food, as well as provide necessary information for designing future interventions.

Myrtha E Reyna-Vargas,1 Arpita Parmar,2 Diana L Lefebvre,3 Meghan B Azad,4– 6 Allan B Becker,4,5 Stuart E Turvey,7 Theo J Moraes,1 Wendy Lou,8 Padmaja Subbarao,1,8 Malcolm R Sears,3 Piushkumar J Mandhane,9 Indra Narang1,10 1Translational Medicine Program, The Hospital for Sick Children, Toronto, ON, Canada; 2Sculich School of Medicine and Dentistry, Western University, London, ON, Canada; 3Department of Medicine, McMaster University, Hamilton, ON, Canada; 4Department of Pediatrics and Child Health, University of Manitoba, Winnipeg, MB, Canada; 5Developmental Origins of Chronic Diseases in Children Network (DEVOTION), Children’s Hospital, Winnipeg, MB, Canada; 6Department of Food and Human Nutritional Sciences, University of Manitoba, Winnipeg, MB, Canada; 7Department of Pediatrics, BC Children’s Hospital, University of British Columbia, Vancouver, BC, Canada; 8Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada; 9Department of Pediatrics, University of Alberta, Edmonton, AB, Canada; 10Faculty of Medicine, University of Toronto, Toronto, ON, CanadaCorrespondence: Indra Narang, The Hospital for Sick Children, 555 University Ave-Hill Wing Room #4534, Toronto, ON, M5G 1X8, Canada, Email indra.narang@sickkids.caIntroduction: Decreased sleep duration and increased screen time as early as preschool age may contribute to overweight and obesity. The effects of bedtime together with nocturnal sleep duration remain unclear with a paucity of data evaluating these associations longitudinally. We aim to evaluate the independent and joint effects of sleep duration, sleep bedtime, and screen time at 3 years of age on BMI status, particularly overweight and obesity by age 5 years.Methods: Data from 2185 participants of the CHILD Cohort Study were analyzed longitudinally using generalized estimating equations (GEE). Models included changes in overweight/obesity status from 3 to 5 years of age as outcome, and nocturnal sleep duration, bedtime, and dail

Background: The human milk proteome comprises a vast number of proteins with immunomodulatory functions, but it is not clear how this relates to allergy of the mother or allergy development in the breastfed infant. This study aimed to explore the relation between the human milk proteome and allergy of both mother and child. Methods: Proteins were analyzed in milk samples from a subset of 300 mother-child dyads from the Canadian CHILD Cohort Study, selected based on maternal and child allergy phenotypes. For this selection, the definition of “allergy” included food allergy, eczema, allergic rhinitis, and asthma. Proteins were analyzed with non-targeted shotgun proteomics using filter-aided sample preparation (FASP) and nanoLC-Orbitrap-MS/MS. Protein abundances, based on label-free quantification, were compared using multiple statistical approaches, including univariate, multivariate, and network analyses. Results: Using univariate analysis, we observed a trend that milk for infants who develop an allergy by 3 years of age contains higher abundances of immunoglobulin chains, irrespective of the allergy status of the mother. This observation suggests a difference in the milk’s immunological potential, which might be related to the development of the infant’s immune system. Furthermore, network analysis showed overall increased connectivity of proteins in the milk of allergic mothers and milk for infants who ultimately develop an allergy. This difference in connectivity was especially noted for proteins involved in the protein translation machinery and may be due to the physiological status of the mother, which is reflected in the interconnectedness of proteins in her milk. In addition, it was shown that network analysis complements the other methods for data analysis by revealing complex associations between the milk proteome and mother-child allergy status. Conclusion: Together, these findings give new insights into how the human milk proteome, through differences in