Introduction and Objective: Human milk (HM) fatty acids (FA), which are critical for infant development, show wide inter-individual variability, but the impact of maternal metabolic health on HM FA profiles remain unclear. Our objective was to evaluate differences in HM FA between lactating mothers who had been diagnosed with gestational diabetes mellitus (GDM) and those without GDM. Methods: HM samples were collected at 3 months post-partum from participants in two centers, Minnesota and Oklahoma, in the MILk Study (NIHR01HD080444). MILk included women aged 21-45 years; pre-pregnancy BMI 18.5-45.0 kg/m2; singleton full-term pregnancy; intention to breastfeed. Cohort selection for this analysis ensured one third of participants had GDM, although data on GDM treatment was not available. HM was stored at -80°C until FA analysis by GC-MS to measure relative concentrations of 24 FA, reported as the percent of total FA measured (FA%). The primary FA of interest was docosahexaenoic acid (DHA; 22:6n3). Linear regression models evaluated the associations between GDM status and HM FA. Adjustments included maternal BMI, parity, maternal use of omega(n)3 FA supplements and study center. Results: Of the 100 participants (n=32 with GDM), maternal age was 32.4±4.2 years, pre-pregnancy BMI 27.7±5.7 kg/m2 and 38% were nulliparous. Most participants (80%) used n3 FA supplements. Mean dietary n3 FA intake was 1.59±0.83 g/d with no difference by GDM. Milk from mothers with GDM had lower DHA (ß=-0.07, 95% CI (-0.14,-0.01) FA%; p=0.029) which was attenuated in fully adjusted models (ß=-0.035 (-0.10,0.03). Milk oleic acid (18:1n9) was lower in GDM in adjusted models (ß=-2.28 (-4.44,-0.12); p=0.039). GDM was associated with higher FA 15:0, 17:1, 20:1n9, 20:4n6, and lower FA 12:0, 18:3n6, 22:4n6, 22:5n6, 24:0 in adjusted models. The n6:n3 FA ratio did not differ by GDM status. Conclusion: Maternal GDM is associated with altered HM FA profiles. These findings suggest implications of GDM extend beyond gestation well into the lactation period. Disclosure J. Josefson: None. B. Gregg: Consultant; Current; CVS Health. D. Robinson: Research Support; Current; Abbott. Speaker's Bureau; Ended; Baxter. S. Dong: None. A.C. Andrei: None. S. Dhavamani: None. P.V. Subbaiah: None. M. Crimmins: None. D.A. Fields: None. E. Demerath: None. Funding NIH/NICHD (R01HD109260)

The assessment of body composition has long been a fundamental component of research and is gaining increasing adoption in clinical practice. This growing interest has drawn new professionals to the field and increased emphasis on its clinical relevance and applications. However, the diversity of assessment techniques and inconsistent terminology create challenges, highlighting the urgent need for harmonized approaches across research and healthcare settings. Commonly employed methods include bioelectrical impedance approaches, dual-energy X-ray absorptiometry, and computerized tomography, with ultrasound emerging as an increasingly prominent tool. These methods are featured in guidelines for diagnosing conditions such as low muscle mass, malnutrition, sarcopenia, and sarcopenic obesity, among others. This second narrative review in a series, developed by an international panel of experts, focuses on these widely accessible assessment tools that align with clinical recommendations. It presents foundational knowledge, discusses validity and reliability considerations, and offers practical advice on terminology, measurement protocols, data interpretation, and longitudinal monitoring. The report also addresses current limitations and identifies areas needing further research. Our goal is to provide clear, evidence-based guidance that is useful for both experienced practitioners and those newly engaging with body composition assessment. We urge organizations, journals, and stakeholders across the body composition field to adopt the proposed principles and standards to support consistency, transparency, and scientific rigor in both research and clinical care.

BACKGROUND:Gestational diabetes mellitus (GDM) increases offspring obesity risk, but whether this occurs via changes in human milk composition, including alterations in human milk oligosaccharides (HMOs), is unknown. OBJECTIVES:This study aimed to identify differences in HMO concentrations in mothers with and without GDM and test whether GDM-associated HMOs are associated with infant growth, body composition, and fecal microbiome characteristics over the first 6-mo of life. METHODS:Human milk was collected at 1-mo postpartum from 337 females (49 with GDM) who fed their infants breastmilk exclusively. HMOs were quantified by high-performance liquid chromatography and multivariate regression models were used to test differences in HMO concentrations by GDM status (false discovery rate adjustment for multiple testing set at q < 0.05). HMOs associated with GDM were then tested for associations with infant growth, body composition, and 1 and 6-mo infant fecal microbial abundances measured by metagenomic whole-genome sequencing. RESULTS:Participants with GDM had ∼1 SD higher milk 6'sialyllactose (6'SL) {[β (95% confidence interval): 0.58 (0.20, 0.96)] and lacto-N-fucopentaose III (LNFP III) III [95% CI: 0.55 (0.16, 0.94)]} compared with those without GDM and 6'SL concentration was also positively associated with weight and length gain. Although infants of mothers with GDM had lower 1-mo fecal α-diversity and altered abundances of 6 of 56 microbial species detected compared with those without GDM, microbial features were not associated with the concentration of either 6'SL or LNFP III and evidence for mediation of GDM-growth and GDM-microbiome by HMOs was not found. CONCLUSIONS:Mothers with a GDM diagnosis had higher milk concentrations of LNFP III and 6'SL, and 6'SL was in turn associated with increased infant growth rate, but neither HMO was associated with differential infant gut microbial abundances. The results suggest that the link between 6'SL and faster infant growth, if causal, occurs via mechanisms independent of the infant gut microbiome. This study was registered at clinicaltrials.gov as NCT03301753.

Maternal obesity alters breast milk composition in ways that may predispose infants to excess adiposity. Although maternal exercise during lactation has been associated with favorable shifts in milk metabolites in humans, the mechanisms by which exercise remodels the mammary gland and milk lipid profile to influence offspring metabolism remain unclear. We developed a mouse model incorporating daily moderate treadmill exercise only during lactation, using lean (LN) and diet-induced obese (OB) dams, and leveraged indirect calorimetry, stable isotope tracer respirometry, and mammary epithelial cell (MEC) proteomics assays. Maternal obesity broadly remodeled the MEC proteome, decreasing enzymes of de novo fatty acid synthesis and altering lipid transport and oxidative pathways. These molecular adaptations in OB dams corresponded to higher milk triglyceride content and shifts in fatty acid composition, including suppressed medium-chain fatty acids (MCFAs). The exercise (EX) intervention during lactation reset MEC protein networks, enhancing protein translation and vesicle transport pathways, whereas decreasing fatty acid desaturation, relative to the sedentary (SED) group. In OB dams, the exercise intervention increased milk MCFA levels and partially corrected the proinflammatory omega-6 fatty acid bias. Offspring suckling OB-EX dams exhibited enhanced in vivo fatty acid oxidation, partially rescuing obesity-associated impairments in metabolic fuel preference. Together, maternal exercise during lactation remodels mammary metabolism and milk fatty acid composition in obese dams, which in turn, enhances postnatal lipid oxidation. These findings highlight lactation as a modifiable window, wherein maternal activity influences milk composition and early life metabolism. NEW & NOTEWORTHY Maternal obesity alters milk fatty acid composition, with consequences for postnatal metabolism. Maternal exercise during lactation in obese dams remodeled the mammary epithelial cell proteome, increasing medium-chain fatty acids in milk and enhancing offspring lipid oxidation.

Abstract Human milk contains a diverse array of metabolites that contribute to infant nutrition, immune development, and microbial colonization. The maternal factors shaping the milk metabolome, and the relative contribution of genetics or diet vs. other factors, remain poorly understood. Here, we profiled 458 milk metabolites in 349 one-month postpartum human milk samples and integrated metabolomic data with maternal diet, clinical, transcriptomic, and genomic measurements. Maternal diet was broadly associated with milk metabolite composition, with significant correlations identified between dietary features and 323 metabolites. Coffee consumption strongly predicted milk quinic acid and 1,3-dimethyluric acid abundance, while high-fiber dietary patterns were associated with metabolites including proline-betaine and N-acetylornithine. Integration of milk transcriptomic and metabolomic data via machine learning identified biologically plausible gene-metabolite pairs, including associations between QPRT expression and quinolinic acid, and DPEP1 and cysteine-glycine dipeptide. Genome-wide association analyses identified nine study-wide significant metabolite quantitative trait loci, including novel milk-specific associations near PDE6A affecting purine metabolites and near GNE affecting free sialic acid. Comparison with plasma metabolite studies demonstrated both shared and milk-specific genetic regulation of metabolites. Finally, we found that of all tested maternal features, diet explained the largest proportion of variation in the milk metabolome. Together, these findings demonstrate that the human milk metabolome reflects both maternal exposures and mammary gland-specific biology. This work establishes a framework for understanding how genetic and environmental factors shape milk composition.

Introduction and Objective: Breast milk is a dynamic substance rich in both nutritive and nonnutritive compounds that may influence infant growth, development, and obesity risk. We aimed to identify metabolites in human milk that are associated with infant growth and body composition. Methods: We analyzed breast milk metabolomics from 350 mother-infant pairs at 1 month postpartum using high-sensitivity LC/GC-MS and assessed infant anthropometrics (BMI percentile) and body composition [percent body fat (%BF), Fat Free Mass Index (FFMI)] using air displacement plethysmography (at 1-month) and DXA (at 6-months). We tested associations between milk metabolites and infant anthropometric and body composition measures using linear regressions adjusting for covariates including maternal age, parity, delivery mode, gestational age, infant sex, birth weight, race, ethnicity, and enrollment site. We used Benjamini-Hochberg procedure to adjust for multiple comparisons (FDR <0.05). Results: Semi-quantitative concentrations were obtained for 458 metabolites. A greater number of milk metabolites were associated with %BF (9 with FDR<0.05) and BMI percentile (4 with FDR <0.05) than with FFMI (0 with FDR <0.05). Highest ranking metabolites associated with %BF included gamma-glutamylglutamine (beta=0.056, FDR=0.004) and 7-methylguanine (beta=0.061, FDR=0.03) while docosahexaenoate (beta = -0.020, FDR= 0.02) and p-hydroxybenzoate (beta = -0.012, FDR= 0.02) were the highest ranking metabolites associated with BMI percentile. The purine metabolite 7-methylguanine has been implicated previously in adipogenesis. Conclusion: Infant adiposity measures, but not measures of fat free mass, are associated with differences in the human milk metabolome. Further studies are needed to determine whether differences in human milk metabolites play a mechanistic role in infant growth and obesity risk. A. Uniyal: None. C. Lu: None. J.M. Dreyfuss: None. E.M. Nagel: None. A. Pena: None. M. Rudolph: None. D.A. Fields: None. E.W. Demerath: None. E.M. Isganaitis: None. NIH/NICHD (R01HD080444, R01HD109830)

Context: Exercise is recommended for postpartum health, but its effects on breast milk composition and offspring are understudied. Objective: This work aimed to test whether the breast milk metabolome is altered with (i) acute exercise and/or (ii) habitual physical activity, and (iii) whether exercise-altered metabolites are associated with infant adiposity. Methods: Milk metabolites were assessed before and after acute exercise and in association with habitual activity score in 2 independent cohorts at 2 academic medical centers. The acute exercise cohort had 15 mother-infant dyads. The habitual activity nested case-control analysis had 84 physically active "cases" and 35 inactive "controls," and was conducted in a subset of the Mothers and Infants Linked for Healthy Growth (MILk)/4M study (N = 348). The acute exercise exposure was a 30-minute moderate-intensity treadmill session. The habitual activity exposure was based on Physical Activity Recall questionnaire scores. Main outcome measures included milk metabolite relative abundance at 1-month post partum by liquid chromatography-gas chromatography mass spectrometry, and infant anthropometric and body composition measures at 1, 3, and 6 months. Results: An acute exercise bout altered milk concentrations in 28 of 511 detectable metabolites (false discovery rate [FDR] < .05). In the habitual activity analysis, 4 of 454 detectable metabolites differed between active cases vs inactive controls (FDR < .05). Ten metabolites were altered (P < .05) by both exercise exposures. Of these, 4 were positively associated with fat mass index at 1 month, and 2 were associated with greater increase in body mass index z score between 1 and 3 months. Conclusion: Maternal exercise was associated with differences in the breast milk metabolome. Metabolites that were associated both with acute exercise and habitual activity correlated with infant adiposity measures.

Body composition assessment is widely used in both research and clinical practice, yet confusion over basic concepts and terminology persists, leading to inaccurate assessments, comparisons, and interpretations. To address this concern, an international working group was formed to clarify basic concepts, standardize terminology, and provide guidance on the use and interpretation of body composition assessment. This initial publication addresses methodological standards, focusing on summarizing body composition levels and models, and introducing standardized terms and definitions. Body composition is organized into 5 distinct levels, ranging from atomic to whole-body, with each higher level encompassing the components of the preceding less complex levels. As a result, terms that describe components at different levels should not be used interchangeably. For example, the use of the molecular-level term “lean body mass” is discouraged because it inaccurately refers to fat-free mass (FFM), lean mass, or lean soft tissue (LST). FFM includes all compartments at the molecular level except fat (nonpolar lipids; mainly triglycerides), and FFM also contains nonfat (or polar) lipids. The term “lean mass” is equivalent to FFM, but not to LST, as FFM includes bone mineral content. Additionally, skeletal muscle is classified at the tissue-organ level and should not be confused with the molecular-level components FFM and LST. Likewise, fat mass and adipose tissue are different components: fat mass, mainly triglycerides, is assessed at the molecular level, whereas adipose tissue is measured at the tissue-organ level. Models are also specific to each level. It is crucial for researchers and clinicians to have a clear understanding of what each body component entails and to use accurate terminology to ensure precise assessment, reporting, and interpretation of body composition data.

Background: Human milk hyaluronan (HA), a glycosaminoglycan with barrier-protective and immunomodulatory functions, may be influenced by maternal characteristics. The effects of maternal obesity and acute dietary intake on milk HA concentrations remain unclear. Methods: This secondary analysis included 35 lactating mothers (n = 19 normal weight [NW], n = 16 obese [OB]) at 6 weeks postpartum who participated in two separate, but standardized, protocols: (1) Study One, which consisted of hourly milk collections for six hours following a standardized high-fat meal with a sugar-sweetened beverage beginning at 6:00 am, and (2) Study Two, which consisted of daily morning milk collections for seven consecutive days to assess temporal stability (Monday-Sunday). HA concentrations were quantified by an ELISA and analyzed using a mixed-effects and repeated-measures ANOVA. Results: In Study One, postprandial HA concentrations remained stable with no effect of time, BMI, or time × BMI interaction (p > 0.05). In Study Two, HA did not vary significantly by day (p = 0.082) but was higher in OB versus NW mothers (151.9 ± 18.7 vs. 96.5 ± 12.4 ng/mL; p = 0.0396), with the largest difference observed on Day 1 (p = 0.0117). Mean HA values trended upward later in the week (Day 6 and 7), suggesting potential influences of habitual dietary intake or weekend energy patterns. Conclusions: Milk HA concentrations were not altered by acute dietary intake but were consistently higher across multiple days in mothers with obesity. These results indicate that milk HA varies with maternal metabolic status and may also be influenced by habitual dietary patterns, including fluctuations between weekday and weekend intake.

The establishment of the gut microbiome in early life is critical for healthy infant development. Although human milk is recommended as sole nutrition for the infant, little is known about how variation in the milk microbiome shapes the microbial communities in the infant gut. Here, we quantified the similarity between the maternal milk and the infant gut microbiomes using 507 metagenomic samples collected from 195 mother-infant pairs at one, three, and six months postpartum. Microbial taxonomic overlap between milk and the infant gut was driven by Bifidobacterium longum, and infant microbiomes dominated by B. longum showed greater temporal stability than those dominated by other species. We identified numerous instances of strain sharing between milk and the infant gut, involving both commensal (e.g. B. longum) and pathobiont species (e.g. K. pneumoniae). Shared strains also included typically oral species such as S. salivarius and V. parvula, suggesting possible transmission from the infant's oral cavity to the mother's milk. At one month, the infant gut microbiome was enriched in biosynthetic pathways, suggesting that early colonisers might be more metabolically independent than those present at six months. Lastly, we observed significant overlap in antimicrobial resistance gene carriage within mother-infant pairs. Together, our results suggest that the human milk microbiome has an important role in the assembly, composition, and stability of the infant gut microbiome.

Maternal obesity alters breast milk composition in ways that may predispose infants to excess adiposity. While maternal exercise during lactation has been associated with favorable shifts in milk metabolites in humans, the mechanisms by which exercise remodels the mammary gland and milk lipid profile to influence offspring metabolism remain unclear. We developed a mouse model incorporating daily moderate treadmill exercise during lactation, indirect calorimetry, stable isotope tracer respirometry, and mammary epithelial cell (MEC) proteomics in lean (LN) and diet-induced obese (OB) dams. Maternal obesity broadly remodeled the MEC proteome, reducing enzymes of de novo fatty acid synthesis and altering lipid transport and oxidative pathways. These molecular adaptations corresponded to higher milk triglyceride content and shifts in fatty acid composition, including an elevated omega-6 to omega-3 fatty acid ratio. The exercise (EX) intervention during lactation reset MEC protein networks, enhancing translational and vesicle transport pathways while reducing fatty acid desaturation, relative to the sedentary (SED) group. In OB dams, exercise increased milk medium-chain fatty acid (MCFA) levels and partially corrected the n6/n3 FA ratio. Offspring nursed by OB-EX dams exhibited higher whole-body energy expenditure, increased fatty acid oxidation, and improved metabolic flexibility compared to litters consuming OB-SED milk. Together, maternal exercise during lactation remodels mammary metabolism and milk fatty acid composition in obese dams, enhancing neonatal lipid oxidation and energy expenditure. These findings highlight lactation as a modifiable window, wherein maternal activity influences milk composition and infant metabolic health. New and noteworthy:Maternal obesity alters milk fatty acid composition, with consequences for infant metabolism. Exercise during lactation in obese dams remodeled the mammary epithelial cell proteome, increasing medium-chain fatty acids in milk and enhancing lipid oxidation and energy expenditure in offspring.

Disclosure: A. Uniyal: None. C. Lu: None. D. Jonathan: None. E.M. Nagel: None. A. Peña: None. M.C. Rudolph: None. D.A. Fields: None. E. Demerath: None. E. Isganaitis: None. Introduction and Objectives Breast milk is a dynamic fluid rich in both nutritive and nonnutritive compounds that support infant development and growth. The lipidome of human milk may reflect both maternal diet and metabolic health, which may impact infant metabolic, endocrine, and inflammatory phenotypes. Higher breast milk levels of 12,13-diHOME, a signaling lipokine, have been linked to lower 1-month infant fat mass and reduced BMI Z-score gain. We aimed to study the relationship between the human milk lipidome and adiposity measures during infancy. Hypothesis: The milk lipidome is associated with changes in infant growth and body composition in the first 6-months postpartum. Methods: We analyzed breast milk from 117 mother-infant pairs at 1-month using high-sensitivity LC/GC-MS lipidomics (BPGbio, Inc.), and assessed infant growth (weight for age-z-scores: waz, length-age-z score: laz) and body composition (fat mass, fat free mass, % body fat) from birth to 6 months (0, 1, 3, 6 months) using air-displacement plethysmography (ADP) and Dual Energy Xray Absorptiometry (DXA). We calculated Pearson correlation coefficients (unadjusted) between individual signaling and structural lipids (exposure) with infant growth measures and body composition measures (outcome). We used FDR<0.05 to denote statistical significance after adjustment for multiple comparisons. Results: We included 117 mother infant dyads with maternal age of 32.2 ±3.5 (mean ±SD) years and gestational age of 39 ±1 weeks, with 71 male and 46 female infants. Lipidomic analysis identified 51 signaling lipids and 516 structural lipids. Abundance in several structural lipids at 1-month postpartum was associated with infant growth measures at 3-months and with infant fat mass at 6-months. For infant growth measures at 3- months with FDR<0.05, 9 lipids were associated with infant weight for age z scores, and 23 lipids were associated with infant length for age z scores; highest ranking lipids included Triglycerides (TG) (14:0_16:0_20:4) (waz : r = -0.35, FDR 0.04, laz r =-0.39, FDR=0.02) and TG (16:0_18:0_20:4) (r =-0.38, waz FDR =0.03, laz: r =-0.40, FDR=0.02). Abundance of 91 lipids in milk at 1-month predicted reduced infant fat mass at 6 months with the highest-ranking lipids being TG (10:0_18:1_18:2) (r = -0.39, FDR= 0.038) and TG (10:0_16:0_18:2) (r = -0.37, FDR=0.038). Conclusion: Plasmenyl-PE, diacylglycerol (DG), and triglyceride (TG) derivatives were among the top lipid classes linked to weight and adiposity measures, with the majority of associations showing an inverse relationship between lipid abundance and infant adiposity. Additional research is needed to clarify the mechanistic relationship between breast milk lipids and infant health. Presentation: Saturday, July 12, 2025

Human milk is a complex mix of nutritional and bioactive components that provide complete nourishment for the infant. However, we lack a systematic knowledge of the factors shaping milk composition and how milk variation influences infant health. Here, we characterize relationships between maternal genetics, milk gene expression, milk composition, and the infant fecal microbiome in up to 310 exclusively breastfeeding mother-infant pairs. We identified 482 genetic loci associated with milk gene expression unique to the lactating mammary gland and link these loci to breast cancer risk and human milk oligosaccharide concentration. Integrative analyses uncovered connections between milk gene expression and infant gut microbiome, including an association between the expression of inflammation-related genes with milk interleukin-6 (IL-6) concentration and the abundance of Bifidobacterium and Escherichia in the infant gut. Our results show how an improved understanding of the genetics and genomics of human milk connects lactation biology with maternal and infant health.

Breastfeeding reduces childhood obesity risk, though the mechanisms remain unclear. We recently reported that maternal exercise significantly increases breastmilk levels of lipids and metabolites involved in brown adipocyte thermogenesis. It is unclear whether differences in these milk constituents may play a functional role in infant adipose tissue metabolism. Thus, we tested whether consumption of human milk after an acute bout of maternal exercise alters infant thermogenesis, a surrogate for brown adipose tissue function. Exclusively breastfeeding mothers (n=31, 1-mo postpartum) completed a supervised exercise session (45 minutes, heart-rate reserve 65-75%) and, on a separate day, a control period of rest, each followed by an infant feeding session 1h afterwards. We analyzed human milk (metabolomics, lipidomics) before and after exercise. We compared infant anterior neck surface temperature (infrared thermography, IRT) following feeding of either “exercise milk” or “control milk”. We analyzed resting metabolic rate (RMR) and body composition (DXA) in all infants; a subset (n=10) also underwent fat-fraction MRI to assess sub-clavicular beige fat depot volume. Infant temperature trended higher (+0.245°C, P=0.1) after consumption of “exercise milk” vs. “control milk”; higher delta temperature was associated with higher infant trunk fat free mass (P<0.05). Of 213 metabolites detected in breastmilk; 37 were nominally changed (P<0.05) and 3 significantly changed (FDR<0.05) by exercise. For 16 metabolites, the change in abundance with maternal exercise correlated with change in infant temperature after "exercise-" vs. "control-milk" consumption. Top-ranking positively correlated metabolites included signaling lipids, lactate, guanine, and spermine (P<0.05). Our findings indicate that exercise-induced changes in human milk are associated with activation of infant metabolism via thermogenesis. Disclosure E.M. Isganaitis: Research Support; Dexcom, Inc., Tandem Diabetes Care, Inc., Insulet Corporation, MannKind Corporation. C. Lu: None. J. Dreyfuss: None. G. Kyere-Davies: None. K.R. Short: None. D.A. Fields: None. M. Rudolph: None. Funding Harold Hamm Pilot and Feasibility Grant; NIDDK P30 Pilot and Feasibility Grant

Human cytomegalovirus (CMV) is a highly prevalent herpesvirus that is often transmitted to the neonate via breast milk. Postnatal CMV transmission can have negative health consequences for preterm and immunocompromised infants, but any effects on healthy term infants are thought to be benign. Furthermore, the impact of CMV on the composition of the hundreds of bioactive factors in human milk has not been tested. Here, we utilize a cohort of exclusively breastfeeding full term mother-infant pairs to test for differences in the milk transcriptome and metabolome associated with CMV, and the impact of CMV in breast milk on the infant gut microbiome and infant growth. We find upregulation of the indoleamine 2,3-dioxygenase (IDO) tryptophan-to-kynurenine metabolic pathway in CMV+ milk samples, and that CMV+ milk is associated with decreased Bifidobacterium in the infant gut. Our data indicate a complex relationship between milk CMV, milk kynurenine, and infant growth; with kynurenine positively correlated, and CMV viral load negatively correlated, with infant weight-for-length at 1 month of age. These results suggest CMV transmission, CMV-related changes in milk composition, or both may be modulators of full term infant development.

The tutelage of our mentors as scientists included the analogy that writing a good scientific paper was an exercise in storytelling that omitted unessential details that did not move the story forward or that detracted from the overall message. However, the advice to not get lost in the details had an important flaw. In science, it is the many details of the data themselves and the methods used to generate and analyze them that give conclusions their probative meaning. Facts may sometimes slow or distract from the clarity, tidiness, intrigue, or flow of the narrative, but nevertheless they are important for the assessment of what was done, the trustworthiness of the science, and the meaning of the findings. Nevertheless, many critical elements and facts about research studies may be omitted from the narrative and become hidden from scholarly scrutiny. We describe a “baker’s dozen” shortfalls in which such elements that are pertinent to evaluating the validity of scientific studies are sometimes hidden in reports of the work. Such shortfalls may be intentional or unintentional or lie somewhere in between. Additionally, shortfalls may occur at the level of the individual or an institution or of the entire system itself. We conclude by proposing countermeasures to these shortfalls.

BACKGROUND:Breastfeeding information stored within electronic health records (EHR) has recently been used for pharmacoepidemiological research, however the data are primarily collected for clinical care. OBJECTIVES:To characterise breastfeeding information recorded in structured fields in EHR during infant and postpartum health care visits, and to assess the validity of lactation status based on EHR data versus maternal report at research study visits. METHODS:We assessed breastfeeding information recorded in structured fields in EHR from one health system for a subset of 211 patients who were also enrolled in a study on breast milk composition between 2014 and 2017 that required participants to exclusively breastfeed their infants until at least 1 month of age. We assessed the frequency of breastfeeding information in EHR during the first 12 months of age and compared lactation status based on EHR with maternal report at 1 and 6-month study visits (reference standard). RESULTS:The median number of breastfeeding records in the EHR per infant was six (interquartile range 3) with most observations clustering in the first few weeks of life and around well-infant visits. At the 6-month study visit, 93.8% of participants were breastfeeding and 80.1% were exclusively breastfeeding according to maternal report. Sensitivity of EHR data for identifying ever breastfeeding was at or near 100%, and sensitivity for identifying ever exclusive breastfeeding was 98.0% (95% CI: 95.0%, 99.2%). Sensitivities were 97.3% (95% CI: 93.9%, 98.9%) for identifying any breastfeeding and 94.4% (95% CI: 89.7%, 97.0%) for exclusive breastfeeding, and positive predictive values were 99.5% (95% CI: 97.0%, 99.9%) for any breastfeeding and 95.0% (95% CI: 90.4%, 97.4%) for exclusive breastfeeding. CONCLUSIONS:Breastfeeding information in structured EHR fields have the potential to accurately classify lactation status. The validity of these data should be assessed in populations with a lower breastfeeding prevalence.

The establishment of the gut microbiome in early life is critical for healthy infant development. Although human milk is recommended as the sole source of nutrition for the human infant, little is known about how variation in milk composition, and especially the milk microbiome, shapes the microbial communities in the infant gut. Here, we quantified the similarity between the maternal milk and the infant gut microbiome using 507 metagenomic samples collected from 195 mother-infant pairs at one, three, and six months postpartum. We found that the microbial taxonomic overlap between milk and the infant gut was driven by bifidobacteria, in particular by B. longum. Infant stool samples dominated by B. longum also showed higher temporal stability compared to samples dominated by other species. We identified two instances of strain sharing between maternal milk and the infant gut, one involving a commensal (B. longum) and one a pathobiont (K. pneumoniae). In addition, strain sharing between unrelated infants was higher among infants born at the same hospital compared to infants born in different hospitals, suggesting a potential role of the hospital environment in shaping the infant gut microbiome composition. The infant gut microbiome at one month compared to six months of age was enriched in metabolic pathways associated with de-novo molecule biosynthesis, suggesting that early colonisers might be more versatile and metabolically independent compared to later colonizers. Lastly, we found a significant overlap in antimicrobial resistance genes carriage between the mother's milk and their infant's gut microbiome. Taken together, our results suggest that the human milk microbiome has an important role in the assembly, composition, and stability of the infant gut microbiome.

Importance Gestational diabetes (GD) is linked to health risks for the birthing parent and infant. The outcomes of GD on human milk composition are mostly unknown. Objective To determine associations between GD, the human milk metabolome, and infant growth and body composition. Design, Setting, and Participants Cohort study using data from the Mothers and Infants Linked for Healthy Growth and the Maternal Milk, Metabolism, and the Microbiome studies at the University of Oklahoma and University of Minnesota, large prospective US cohorts with a high proportion of exclusive breastfeeding. Participants were mother-infant dyads recruited between October 2014 and August 2019 who planned to exclusively breastfeed for 3 or more months. Data were analyzed from July 2022 to August 2024. Exposure GD diagnosed via oral glucose tolerance test. Main Outcomes and Measures The milk metabolome was assessed by untargeted liquid chromatography-gas chromatography-mass spectrometry at 1 month post partum. Infant growth (weight for length z score, length for age z score, and rapid weight gain) and body composition (percentage body fat and fat-free mass index) from 0 to 6 months were assessed. Linear regression analyses tested associations between GD and milk metabolites, with adjustment for covariates and potential confounders. Results Among 348 dyads (53 with GD), 27 (51%) of the GD-exposed infants were female and 157 (53%) of nonexposed infants were male; 10 (19%) were Asian, 2 (4%) were Black or African American, and 37 (70%) were White. The mean (SD) age was higher in the GD group (with GD, 34.0 [4.3] years; without GD, 30.7 [4.1] years). In adjusted models, GD was associated with differential levels of 9 metabolites of 458 tested (FDR<0.05); 3 were higher (2-hydroxybutyric acid, 3-methylphenylacetic acid, and pregnanolone sulfate) and 6 were lower in women with GD (4-cresyl sulfate, cresol, glycine, P-cresol sulfate, phenylacetic acid, and stearoylcarnitine). Phenylacetic acid was associated with length for age z score (beta = 0.27; SE, 0.13; 95% CI, 0.02 to 0.16), 2-hydroxybutryic acid with percentage body fat (beta = -1.50; SE, 0.66; 95% CI, -2.79 to -4.82), and stearoylcarnitine with greater odds of rapid weight gain (odds ratio, 1.66; 95% CI, 1.23 to 2.25). GD was associated with greater length for age z scores (beta = 0.48; SE, 0.22; 95% CI, 0.04 to 0.91). Conclusions and Relevance In this observational cohort study, GD was associated with altered concentrations of several human milk metabolites. The associations between these metabolites and infant growth suggest that milk compositional differences in mothers with GD may beneficially moderate the growth and body composition of their infants.