Characterization of Omics Components in Human Milk: A Systematic Review
Department of Pediatrics, School of Medicine, Universidad de La Sabana, Chía, Cundinamarca, Colombia
Deparment of Pediatrics, School of Medicine, Universidad de La Sabana. Campus Puente del Común, Km 7, Autopista Norte de Bogotá, Chía, Cundinamarca, Colombia
Abstract
Background/Aims
The proteome, lipidome, glycome, and metabolome of human milk are critical for newborn nutrition and health, and offer personalised, non-pharmacological interventions. This systematic review aims to characterise the omics components of human milk according to maternal health and lactation phases, summarising current knowledge based on high-resolution analytical techniques.
Methods
We conducted a systematic review according to the PRISMA 2020 guidelines. The search was performed between August and September 2022 using Medline, EMBASE, Scopus, LILACS, and Web of Science. Observational studies that analysed human milk at any lactation stage using mass spectrometry or nuclear magnetic resonance to characterise nutrients, biomolecules, or bioactive compounds were included. In total, 55 full-text articles were included in this study.
Results
Glycomics is the most frequently studied omics, followed by proteomics, metabolomics, and lipidomics. Analyses revealed that maternal comorbidities and lactation phases influence the composition of human milk. Fucosylated HMOs showed a protective role against infectious diseases, while elevated levels of protease inhibitors were found in milk from allergic mothers and elevated immunoglobulins were present in milk from mothers with COVID-19. Endocannabinoid profile is associated with improved neonatal sucking ability, while fatty acid-derived metabolites are correlated with infant growth. Distinct omics patterns have also been identified in mothers with diabetes, hypothyroidism, and obesity.
Conclusion
Understanding the omics profile of human milk can guide precise nutrition and improve human milk substitutes. Further research integrating omics data with maternal and infant outcomes will be essential to advance knowledge and support infant health.
Introduction
Breast milk is the optimal source of nutrition for infants, recommended exclusively during the first six months of life, and continued alongside complementary feeding until at least two years of age [1]. It confers critical benefits in nutrition, metabolism, neurodevelopment, and immune protection, both in the short and long terms. These advantages are derived from breast milk’s intricate composition of macronutrients, micronutrients, and bioactive molecules, which interact dynamically with infants to support essential biological processes and adapt to individual needs and conditions [2]. Notably, the composition of breast milk varies among individuals and is adjusted in response to maternal health status and environmental factors [3,4,5,6,7].
Recent advancements in high-resolution analytical technologies, such as mass spectrometry (MS), nuclear magnetic resonance (NMR), and chromatographic techniques (GC and LC), along with advances in bioinformatics and statistical approaches, have markedly enhanced the ability to analyse complex biological matrices. These innovations have given rise to the field of omics and enabled comprehensive characterization of the proteome, lipidome, glycome, and metabolome in biological fluids, including human milk [8, 9]. Omics technologies have elucidated the metabolic profile of human milk, its temporal variations, and its remarkable capacity to adapt to diverse maternal and neonatal conditions [10]. This growing body of knowledge highlights the central role of human milk in newborn nutrition and health, offering personalised non-pharmacological interventions for both healthy and critically ill infants [1, 7].
In this context, we conducted a systematic review of the literature to characterise human milk from an omics perspective, integrating evidence from high-resolution analytical technologies across different lactation phases with clinical and biological observations of the mother-infant dyad.
Methodology
We conducted a systematic review of the literature following the PRISMA 2020 (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines [11].
Literature search strategy
A literature search was performed between August and September 2022 across the electronic databases MEDLINE (via PubMed); EMBASE; Scopus; Latin American and Caribbean Health Sciences Literature (LILACS); and Web of Science. Additionally, a snowball sampling approach was employed to screen the reference lists of eligible full-text articles and identify further relevant studies. The search was limited to publications in English and Spanish, and observational studies (cohort, case-control, and cross-sectional) were eligible for inclusion.
The search strategy applied in MEDLINE was as follows, and was adapted accordingly for the other databases: ((“Milk, Human” OR “Breast Milk Expression” OR “Lactation” OR “Breast Feeding” OR “Colostrum”) AND (“Mass Spectrometry” OR “Proton Magnetic Resonance Spectroscopy”)) AND (“Bioinformatics” OR “Proteomics” OR “Metabolomics” OR “Lipidomics” OR “Oligosaccharides” OR “Glycomics”).
Study eligibility criteria
- Analysed human milk at any stage of lactation (colostrum, transitional, or mature milk).
- Employed mass spectrometry (MS) and/or nuclear magnetic resonance (NMR) as analytical platforms, and
- Characterised nutrients, biomolecules, and/or bioactive compounds using omics approaches.
The following exclusion criteria were applied:
- Literature reviews (narrative, systematic, scoping, etc.), conference proceedings, poster abstracts, correspondence to the editor, and unpublished data.
- In vitro studies, and
- Studies characterising the omics profile of donor milk in milk banks and/or pasteurised human milk.
Screening and inclusion of studies
All retrieved records were independently screened and assessed for eligibility by two reviewers in a blinded manner. Disagreements were resolved through consensus. The Bioinformatics Systematic Literature Review (BiSLR) instrument was used to guide decision-making regarding study inclusion [12]. The initial screening of titles and abstracts was performed using the Rayyan® web application, which also allowed for the identification and removal of duplicate records across databases. The full texts of potentially relevant articles were retrieved and independently reviewed in detail by both reviewers.
Data extraction and synthesis
For each included study, we extracted data on the journal name; first author; publication year; country; clinical characteristics of the mothers; omics domain (proteomics, metabolomics, glycomics, lipidomics); analytical technology employed; and bioinformatics database used.
The extracted data were qualitatively synthesized and organised into tables, categorising the findings by omics domain, maternal health status, and lactation phase to facilitate comparisons and highlight patterns across studies.
Results
The study selection process (Figure 1) began with 1,612 records, which were reduced to 823 after removing duplicates. Following title and abstract screening, 96 full-text articles were reviewed, and 55 met the inclusion criteria, including 21 on glycomics, 17 on proteomics, 10 on metabolomics, 5 on lipidomics, and 2 on multi-omics. Bibliometric details and findings are presented in Supplementary Table 1, while Table 1 summarizes the key results by omics component, maternal health status, and lactation phase. Healthy mothers were the subject of 82% of the studies; the rest included those with gestational diabetes (n = 4), allergies (n = 2), obesity (n = 1), iodine deficiency (n = 1), hypothyroidism (n = 1), or COVID-19 (n = 1). Regarding lactation phase, 44% analysed colostrum, 42% analysed transitional, 82% analysed mature, and 25% analysed all phases.
| Omics | Maternal health: healthy | Maternal health: with comorbidities | Lactation phase: colostrum | Lactation phase: transitional | Lactation phase: mature |
|---|---|---|---|---|---|
| Glycomics | High diversity of HMOs; ↑ fucosylation early; ↓ over time; neutral and sialylated HMOs decrease progressively | ↑ DFpLNnH in allergic mothers; differences in secretor/non-secretor patterns; ethnic variation | High HMO concentrations, fucosylated and sialylated; immune protection | HMOs decrease, shifting patterns (e.g., LNT, LNFP) | 3′-FL increases over time; ↓ total HMOs |
| Proteomics | High levels of immune proteins (lactoferrin, IgA, etc.); proteins supporting development and metabolism | ↑ protease inhibitors in allergic mothers; ↑ apolipoproteins in diabetes; ↓ IgA in diabetes; ↑ immune proteins in COVID-19 | High diversity of low-molecular-weight and immune proteins | Decline of early proteins; stabilization | Predominance of growth and metabolism-related proteins |
| Metabolomics | Amino acids, essential fatty acids, endocannabinoids support growth and development | ↑ lipids in obesity; alterations in diabetes, hypothyroidism, and iodine deficiency | ↑ carbohydrates, amino acids, essential fatty acids | Gradual decline of initial lipids and metabolites | ↑ vitamins D3, D2, biotin; ↓ cholesterol, tocopherols |
| Lipidomics | High lipid diversity: very long-chain fatty acids identified; ↑ saturated and unsaturated fatty acids | Minor variations reported | High in phosphatidylcholine, triglycerides, ether-phospholipids | Decrease in plasmalogens and polyunsaturated lipids | Stabilized lipid profile; predominance of lipids supporting microbiota and development |
Glycomics
Oligosaccharides (HMO) profile of the milk of healthy mothers
The composition of HMOs in milk from healthy mothers is influenced by maternal and neonatal factors, including age, allergic history, BMI during pregnancy, parity, delivery mode, gestational age, and infant sex [13,14]. Genetic determinants, such as the Se and Le genes on chromosome 19, play key roles, with Se associated with higher 2′-fucosyllactose (2′FL) levels and Le with higher lacto-N-tetraose (LNT) and lacto-N-fucopentaose II (LNFP II) [15, 16].
High-resolution analyses have detected elevated levels of 2′-FL, α1, 2-fucosylated HMOs, and bifidobacteria-associated oligosaccharides [13, 17, 18]. HMO concentrations were not significantly related to growth in the first four months but were lower in infants with excessive weight gain [14, 19]. Geographic differences were observed, with Latino mothers exhibiting a higher prevalence of secretory HMO patterns [16].
HMO profile of the milk of mothers with comorbidities
HMO profile of human milk in the lactation phases
The HMO concentrations and composition evolve markedly across lactation stages [18, 20,21,22,23,24]. Chaturvedi et al. documented a decline in the total HMO concentration from approximately 9 g/L in colostrum to approximately 4 g/L at one year postpartum, with a specific decrease in α1,2-fucosylated HMOs [18, 20,21,22,23,24]. On the other hand, 3′-fucosyllactose (3′-FL) increased significantly during this period, reaching up to four times its initial concentration in one year [13, 18, 20].
This transition is characterised by a shift from neutral, non-fucosylated HMOs to a higher proportion of fucosylated species, while neutral HMOs declined more rapidly, particularly during the transition to mature milk [22]. In colostrum, high levels of fucosylated HMOs persist during the first four weeks to support the infant’s immature immune system and intestinal barrier [13, 20, 25]. Transitional milk was enriched in lacto-N-fucopentaose III, lacto-N-hexaose, monofucosyllacto-N-hexaose I and III, and acidic HMOs [13, 26]. Wang et al. further observed that mature milk in the first month of lactation contains higher concentrations of the isomer 1-fucosyl-paralacto-N-hexaose III and difucosyllacto-N-hexane-b, whereas 3′-peaks around six months postpartum [13].
Proteomics
Proteomic profile in the milk of healthy nursing mothers
Human milk has a complex protein composition; its key components include serum albumin, lactalbumin, caseins, lysozyme, lactotransferrin, bile salt-activated lipase, and glycoproteins such as polymeric Ig receptor, lactoferrin, and mannose receptor 1 [27,28,29]. Other proteins detected included bovine caseins and β-lactoglobulin, which may have been derived from maternal diet [30]. Furthermore, specific amino acids and metabolites, such as arginine, tyrosine, hydroxybutyrate, niacinamide, choline, and lacto-N-fucopentaose, have been identified as potential predictors of weight gain in preterm infants during hospitalization [19].
Human milk is rich in immune-related proteins and calcium-regulating proteins. Lactoadherin provides protection against rotavirus, while lactoferrin, adipophilin, and butyrophilin exert antibacterial effects through iron sequestration [31]. Peptides derived from lactoferrin promote growth and antimicrobial properties [32]. Novel proteins, including polymeric immunoglobulin receptors and human leukocyte antigens (HLA), facilitate IgA antibody transport [33]. FAM20A and other calcium-associated proteins play critical roles in regulating calcium homeostasis and preventing pathological calcification of mammary epithelial cells during lactation [29].
Proteomic profile in human milk according to maternal comorbidities
The protein composition of human milk is influenced by maternal health status. In mothers with allergic diseases, the levels of protease inhibitors, cystatin C, and apolipoproteins are elevated — potentially limiting allergen penetration through the epithelium — while transthyretin and calcium-binding protein A1 are reduced [34]. In those with gestational diabetes mellitus, higher levels of Apolipoprotein A1 and lactoferrin-related proteins have been reported, along with reduced IgA concentrations [35, 36]. In mothers with hypothyroidism, immune-related proteins increased, but proteins associated with energy metabolism and cytoskeletal integrity, such as actin, tubulin, and GAPDH, decreased [37].
During the COVID-19 pandemic, colostrum from infected mothers exhibited increased levels of immune proteins, including SIgA1 and complement factors, along with a marked reduction in casein [38].
Proteome profile of human milk according to the stages of lactation
High-resolution analyses have revealed substantial changes in the proteome during lactation. Colostrum is characterised by an abundance of low-molecular-weight proteins and peptides, which decline rapidly within the first month postpartum and stabilize in mature milk approximately 60 d after birth [39]. Early lactation also features elevated levels of essential and branched-chain amino acids such as leucine, isoleucine, and valine [40]. Proteins such as R-1-antitrypsin, carbonic anhydrase, and E-cadherin predominate in the early stages, whereas fatty acid-binding proteins and lysozyme C become more prevalent after six months [41]. Additionally, tryptophan, histidine, and peptides associated with purine and pyrimidine nucleotide metabolism increase throughout lactation, reflecting the increasing requirements for DNA synthesis and cell proliferation [42].
Lipidomics
Lipidomic profile of milk from healthy nursing mothers
Studies on the lipid composition of human milk from both full-term and preterm mothers, have identified up to 235 distinct lipids belonging to 16 subclasses, with significant differences in colostrum lipids depending on gestational age [51, 52]. Previously unreported very-long-chain fatty acids (C26:0 and C26:1) were also detected [53]. In preterm infants, the lipid profile shows elevated levels of phosphatidylethanolamine and phosphatidylcholine compared to term milk, while diacylglycerol and ceramide levels are reduced [51]. These lipidomic differences are associated with metabolic pathways, neurodevelopment, and LXR/RXR signalling in neonates [51].
Fatty acid-derived metabolites have also been linked to growth outcome. Faster infant growth correlates with higher levels of tyrosine, arginine, medium-chain saturated fatty acids (e.g., pentadecanoic and myristic acid), triglycerides, phosphatidylcholine, and sphingomyelin [19]. Conversely, slower growth is associated with higher concentrations of plasmalogen-derived oleic acid, arachidonic acid, ceramide, and very-long-chain fatty acids [19].
Lipidomic profile in human milk during the lactation phases
The lipid profile of human milk undergoes significant changes during lactation [54]. Early lactation is characterised by elevated concentrations of odd-chain fatty acids, triglycerides, ether glycerophospholipids, and long-chain polyunsaturated fatty acids (LC-PUFAs). As lactation progresses, plasmalogens and polyunsaturated phospholipids decrease. During the first 15 d postpartum, phosphatidylcholines and phosphatidylglycerols decrease, while lysophosphatidylethanolamines and lysophosphatidylcholines increase [52, 54, 55].
In addition, cholesterol and cholesterol ester levels decline between day 2 and day 84 post-partum [50]. Mature milk is characterised by higher levels of saturated and unsaturated fatty acids, which play a crucial role in supporting infant development and establishing early gut microbiota [40].
Discussion
This systematic review describes the omics components of human milk by integrating evidence from healthy mothers, as well as mothers with comorbidities, at different lactation stages. The findings were systematically categorised by maternal health status and lactation phase, underscoring the dynamic and adaptive nature of milk composition. By combining glycomics, proteomics, metabolomics, and lipidomics, this review highlights how high-resolution analytical platforms have advanced our understanding of human milk as a complex bioactive fluid. The observed variations in bioactive molecules and macronutrients across maternal and lactation stages reveal the potential mechanisms by which milk may provide personalised support for infant nutrition, immune protection, microbiome development, and growth.
Carbohydrates in human milk
The data revealed substantial variability in the types and amounts of HMOs, with by maternal genetic factors (e.g., FUT2 and FUT3 gene status), health, environmental and geographic context, and lactation phase all having effects [56]. Over time, there is a consistent increase in 3′-fucosyllactose (3′-FL) and overall fucosylation, while sialylation and non-fucosylated neutral oligosaccharides progressively decrease. This dynamic adaptation reflects the evolving needs of the infant’s immune system and microbiota maturation during lactation. Functionally, 3′-FL inhibits pathogen adhesion to epithelial cells, contributing to mucosal protection [14]. Sialylated HMOs, including 3′-sialyllactose (3′-SL) and 6′-sialyllactose (6′-SL), show antiviral activity against influenza and possibly other respiratory viruses [57]. Milk rich in 1,2-fucosylated oligosaccharides also reduces the risk of gastrointestinal infections by pathogens, such as Escherichia coli, Campylobacter jejuni, and noroviruses, by competitively inhibiting their gut receptor binding [58]. Lower levels of lacto-N-difucohexaose I (LDFH-I), which is closely associated with 2′-fucosyllactose (2′-FL), correlate with higher rates of calicivirus-associated diarrhoea, underscoring the protective role of 2′-FL in blocking mucosal pathogen-host interactions [58]. Beyond their antimicrobial and antiviral properties, HMOs act as prebiotics, promoting colonization by beneficial Bifidobacterium species and enhancing gut barrier function and immune modulation. These findings illustrate the critical contribution of milk oligosaccharides to infant health beyond nutrition, positioning HMOs as key components of personalised protection in early life.
Proteomics in human milk
Colostrum from SARS-CoV-2-infected mothers contains higher levels of immunological proteins, such as IgA and complement components, and lower levels of ribosomal proteins [38]. Secretory IgA (SIgA) not only neutralizes viral particles, but also modulates mucosal immune responses by transporting antigens to dendritic cells, thus fostering immune education in infants [59]. The observed reduction in ribosomal proteins in colostrum may represent an adaptive response to inhibit viral replication, as ribosomal machinery is essential for viral protein synthesis [60]. These findings underscore the dynamic immune adaptation of breast milk during maternal infections, providing tailored protection for neonates.
In addition to infections, proteomic analyses of human milk have revealed associations with neonatal growth and development. Alexandre-Gouabau et al. identified specific proteins and metabolites in milk that could serve as biomarkers to predict weight gain in preterm infants during hospitalization [19, 61]. This supports the growing concept of precision nutrition, in which milk composition is leveraged to optimize individualized nutritional support for vulnerable neonates.
Additionally, evidence suggests that human milk may contribute to allergy prevention and immune regulation in the offspring. Studies have shown that milk from mothers with allergic conditions (e.g., asthma, rhinitis, and eczema) contains elevated levels of protease inhibitors, as well as immunomodulatory proteins such as cystatin C and apolipoproteins [34]. These molecules may help maintain epithelial barrier integrity, regulate protease-mediated inflammation, and modulate immune sensitivity, thereby potentially conferring on children protection against allergic diseases.
Lipidomics in breast milk
Recent studies have revealed a distinctive endocannabinoid profile in human milk that appears to contribute to improved motor function and coordination of sucking and swallowing in neonates [44]. Given that early weaning is often attributed to sucking difficulties and perceived insufficient milk supply, it would be valuable to further investigate whether this endocannabinoid profile could serve as a biomarker for the risk of early weaning or feeding difficulties [64, 65].
In mothers of pre-term infants, human milk shows significantly elevated levels of phosphatidylcholine [66]. This lipid is a critical precursor of choline, which is essential for the structural and functional development of the central nervous system. Preterm infants have increased choline requirements and insufficient choline intake, which can adversely affect neurocognitive development and pulmonary maturation [67]. Furthermore, alterations in bioactive lipids like plasmalogens has been linked to neonatal complications, including bronchopulmonary dysplasia [68], as well as to long-term conditions, including chronic obstructive pulmonary disease [69]; Alzheimer’s disease [70]; Parkinson’s disease; and Down syndrome [71]. These associations underscore the potential of lipidomics as a tool for identifying at-risk infants and for informing targeted nutritional interventions.
These findings underscore the complexity and adaptability of human milk, which transcends nutrition to act as a dynamic bioactive fluid tailored to the infant’s stage, health, and maternal condition. Multi-omics approaches—glycomics, proteomics, metabolomics, and lipidomics—have revealed molecular networks that nourish, modulate immunity, shape microbiota, support neurodevelopment, and protect against disease. This system-level perspective positions human milk as a model for personaliszed medicine, offering insights into preventive and therapeutic strategies beyond infant nutrition. Future research combining omics, metagenomics, and longitudinal outcomes will be essential to fully elucidate these mechanisms and inform interventions to improve maternal and infant health globally.
This review had several limitations. Studies on the metagenomic profile of human milk—a key component for understanding the milk microbiota and its impact on infant health—were not included. Heterogeneity in study designs, analytical platforms, and reporting limits quantitative synthesis and comparability. Most of the studies were observational and cross-sectional, restricting causal inferences. Finally, restricting English and Spanish may have excluded relevant studies.
Among its strengths, this is the first study to integrate findings from four major omics disciplines, systematically summarizing the molecular components of human milk as they fluctuate with maternal health and lactation stage. A rigorous search strategy, adherence to PRISMA guidelines, and clinically relevant categorization of findings provide robust synthesis and highlight knowledge gaps, making it a valuable resource for clinicians, researchers, and policymakers.
Conclusion
Advances in high-resolution omics and bioinformatics have revealed the dynamic and individualised composition of human milk, shaped by maternal genetics, health, and lactation stages. Beyond HMOs, which are key for immunity, microbiota, and disease prevention, proteomics, metabolomics, and lipidomic studies highlight bioactive molecules that support growth, neurodevelopment, and immune regulation. Future research should clarify causal links with infant outcomes and how maternal factors influence the “nutriome.” Deciphering this network reinforces the unique role of milk and provides information for precision nutrition, neonatal care, and improved human milk substitutes.
Key Points
- Carbohydrates in breast milk, particularly HMOs, contribute to the protection against infectious and allergic diseases through microbiota modulation and pathogen inhibition.
- Omic-derived components of human milk vary significantly depending on maternal comorbidities and lactation phases, reflecting personalised adaptation.
- An endocannabinoid profile unique to breast milk may play a role in infant motor function, sucking, and swallowing skills, with implications for early weaning risk.
- Specific metabolite profiles in human milk are associated with infant growth trajectories and may serve as biomarkers to guide nutritional intervention.
- Distinct omics patterns have been observed in the milk of mothers with diabetes mellitus, hypothyroidism, and obesity, potentially influencing infant development and health outcomes.
Notes
Supplementary materials
| Bibliometric data (author, year, country and reference) | Omics | Method of technology | Bioinformatics base | Clinical characteristics. (lactation phase, healthy or sick). | Results |
|---|---|---|---|---|---|
| Wieruszeski J et al., 1985, France | Glycomics | FAB-MS and LC-MS. | Not reported | Not reported | Identified two novel oligosaccharides (lacto-N-sialylated fucopentaose I and II), likely reflecting mammary glycosyltransferase activity during lactation. |
| Grönberg G et al., 1990, Sweden | Glycomics | SEC-IEC-HPLC-NMR. | Not reported | Not reported | Identified three novel disialylated oligosaccharides in human milk. |
| Finke B et al., 1999, Germany | Glycomics | MALDI-MS. | Not reported | Not reported | Detected acidic and neutral oligosaccharides, including complex neutral structures of up to 35 monosaccharide units. |
| Chaturvedi P et al., 2001, USA | Glycomics | rpHPLC. | Not reported | Transitional and mature milk from healthy mothers | Oligosaccharides varied in quality and quantity during lactation, with higher fucosylated and sialylated forms early on, decreasing after 26 weeks postpartum; low concentrations may inhibit pathogen binding. |
| Niñonuevo M et al., 2008, USA | Glycomics | HPLC-Chip/TOF-MS. | Not reported | Colostrum, transitional and mature milk from healthy mothers | LNT, LNnT and LNFP I/V were most abundant and stable throughout lactation, with higher fucosylated vs. sialylated HMOs from day 1 to 71, potentially influenced by maternal or infant factors. |
| Albrecht S et al., 2010, Netherlands | Glycomics | Off-line CE-LIF, Online CE-LIF-ESI-MS. | Not reported | Not reported | Detected major peaks of SL, DS-LNT, S-LNT, FL, LNDFH, LNT, LNFP I/III, LNFP II, and DF-L. |
| Dallas D et al., 2011, USA | Glycomics | HPLC-Chip/TOF-MS | In-house Postgres relational database | Mature milk in healthy mothers. | Identified 52 N-linked glycans (84% fucosylated, 47% sialylated); breast milk provides Neu5Ac, important for neonatal brain development. |
| Xu G et al., 2017, USA | Glycomics | HPLC y UPLC/QqQ-MS. | Not reported | Transitional and mature milk from healthy mothers | Most oligosaccharides decreased over lactation, while fucosylation increased; secretor mothers had higher total and fucosylated HMOs. |
| Ma L et al., 2018, China | Glycomics | LC−MRM−MS | Not reported | Mature milk from healthy mothers. | Observed high variability in BMH concentrations, influenced by genetic and ethnic factors and secretor/blood group status |
| Nijman et al., 2018, USA | Glycomics | nano-LC-chip/Q-TOF MS | In-house HMOS database | Colostrum and mature milk from healthy mothers | Identified key health-related oligosaccharides (sialylated, α1,2-fucosylated, LNT), which declined from day 3 to 42. |
| Zhang W et al., 2019, China | Glycomics | LC–MS/MS MRM | Not reported | Mature milk from healthy mothers | Identified 12 oligosaccharides (including isomeric pairs); variations linked to donor ethnicity and timing of collection. |
| Yan J et al., 2019, China | Glycomics | ERLIC−MS/MS | Not reported | Transitional and mature milk from healthy mothers | Oligosaccharides declined during lactation, with neutral forms decreasing faster than sialylated ones. |
| Gao X et al., 2019, China | Glycomics | MALDI-TOF-MS | Not reported | Mature milk from healthy mothers | Sialylated HMOs (SHMO) reduced leukocyte adhesion; 3′-SL had antiviral effects; 2′-FL and 3′-SL improved memory and learning in infants. |
| Tonon M, 2019, Brazil | Glycomics | LC-MS | Not reported | Transitional and mature milk from healthy mothers and mothers with allergic disease | Higher 2′-FL in mothers of girls, higher LNH in mothers of boys; allergic mothers had higher DFpLNnH; secretor phenotype linked to allergy incidence. |
| Mernie E, 2019, Taiwan | Glycomics | TLC MALDI-MS | Not reported | Colostrum, transitional and mature milk from healthy mothers | Identified 25 neutral HMOs; early milk richer in large oligosaccharides; no sialylated HMOs detected. |
| Wang M et al., 2020, China | Glycomics | HPLC-ESI-MS | Not reported | Colostrum, transitional and mature milk from healthy mothers | Secretor phenotype influenced by ethnicity; multiparity associated with higher LNT and LNnT, lower 3′FL. |
| Ferreira A et al., 2020, Brazil | Glycomics | HPLC-FL | In-house HMOS database | Colostrum, transition milk and mature milk from healthy mothers | Secretor pattern more common in Latin women; multiparity linked to higher LNT and LNnT, lower 3′FL; mechanism unclear. |
| Siziba L, 2021, Germany | Glycomics | LC-MS2 | Not reported | Mature milk from healthy mothers | Oligosaccharides decreased at 6–12 months; secretor mothers produced more; early FUT-dependent HMO exposure may be beneficial. |
| Siziba L, 2022, Germany | Glycomics | LC-ESI-MS | Not reported | Mature milk from healthy mothers | No association found between HMOs and atopic dermatitis at 1–2 years; identified several key HMOs. |
| Xun Y et al., 2022, China | Glycomics | UPLC-MS | Not reported | Mature milk from healthy mothers | Multiparous mothers had higher LNT and LNnT, lower 3FL, regardless of secretor status; explained by FUT2/FUT3 gene expression. |
| Vinjamuri A, 2022, USA | Glycomics | nano–HPLC–time of flight (TOF)–MS | Not reported | Mature milk in healthy mothers | HMO abundance decreased in first 6 months; α(1,2)-fucosylated species varied most; secretor mothers had higher 2′FL and LDFT, non-secretors had higher α(1,3)/α(1,4)-fucosylated HMOs. |
| Donatella Fortunato et al., 2003, Italy | Proteomics | MALDI-TOF-MS | PROSITE database | Colostrum from healthy mothers | Identified 107 proteins, mainly lactadherin, butyrophilin, lactoferrin, adipophilin, and carbonic anhydrase. |
| Gianluca Picariello et al., 2008, Italy | Proteomics | MALDI-TOF-MS | Databases from the National Center for Biotechnology Information (nrNCBI) | Colostrum from healthy mothers. | Identified 32 glycoproteins with 63 N-glycosylation sites, mainly polymeric Ig receptor, lactoferrin, IgA2 chain, serum albumin, and caseins. |
| Liao et al., 2011, USA | Proteomics | LC-MS/MS | Uniprot database | Colostrum, transition milk and mature milk from healthy mothers | Identified 115 proteins; early lactation showed higher expression of R-1-antitrypsin, carbonic anhydrase, chordin-like protein 2, and galectin-3 binding protein; later lactation showed higher fatty acid-binding protein, lysozyme C, and monocyte differentiation antigen. |
| Liao et al., 2011, USA | Proteomics | LC-MS/MS | Uniprot database | Colostrum, transition milk and mature milk from healthy mothers. | Identified 191 MFGM proteins: 21.5% involved in energy metabolism, 8.4% in growth, 19.9% in immune functions; novel proteins included polymeric immunoglobulin receptor and HLA antigens. |
| Liao et al., 2011, USA | Proteomics | LC-MS/MS | Not reported | Colostrum, transition milk and mature milk from healthy mothers. | Identified 82 proteins (18 specific to casein fraction) grouped into nine functional categories, highlighting immune response (28%), metabolism (22%), and cell communication (18.3%); casein fraction lacked proteins regulating nucleic acid metabolism. |
| Smilowitz et al., 2013, USA | Proteomics | nanoLC-Chip/TOF MS | Not reported | Mature milk from healthy mothers and mothers with gestational diabetes mellitus (GDM) | Compared to controls, GDM milk had 63.6% less sIgA, 45% more lactoferrin N-glycans, 36–72% more fucosylated and sialylated lactoferrin N-glycans, and 32–43% less sIgA and mannose, fucose, and sialic acid N-glycans. |
| Mandal et al., 2014, India | Proteomics | MALDI-TOF-MS | NCBI and SwissProt databases | Mature milk from healthy mothers | Identified 24 peptides with antimicrobial, antioxidant, and growth-stimulating activities; lactoferrin- and casein-derived peptides showed antibacterial, proliferative, and antioxidant effects. |
| Dmitry Grapov et al., 2014, USA | Proteomics | LC/MS/MS | Uniprot and Repository of Adventitious Proteins databases | Colostrum from GDM and non-GDM mothers. | Identified 27 proteins, with 10 differing between GDM and controls; GDM milk had more apolipoprotein A1, heavy chain Ig V–II region, and prostatin. |
| Kasper A. Hettinga et al., 2015, USA | Proteomics | LC/MS/MS | Uniprot database | Mature milk from allergic and non-allergic mothers | Identified 357 proteins in allergic mothers and 355 in non-allergic mothers; 9 were unique to allergic and 7 to non-allergic mothers. |
| Lingli Chen et al., 2018, USA | Proteomics | LC-MS/MS | UniProt database | Colostrum from hypothyroid and non-hypothyroid mothers | Identified 44 proteins; 29 related to energy metabolism and cell structure decreased in hypothyroid mothers, while 15 immune-related proteins increased. |
| Laura Di Francesco et al., 2018, Italy | Proteomics | MALDI-TOF-MS | Not reported | Colostrum and mature milk from healthy mothers | Early milk showed higher signals for peptides, proteins, and vitamins compared to mature milk, with a higher proportion of proteins <10 kDa in colostrum. |
| Jing Zhu et al., 2019, Netherlands | Proteomics | LC-MS/MS | UniProt database | Mature milk from healthy mothers | Identified 109 non-human peptides grouped into 36 proteins, mainly bovine caseins and β-lactoglobulin, likely from maternal diet. |
| Lina Zhang et al., 2019, China | Proteomics | LC-MS/MS | UniProt database | Mature milk from healthy mothers | Identified 693 proteins, most abundant were lactoferrin, serum albumin, polymeric Ig receptor, macrophage mannose receptor 1, and bile salt-activated lipase; 34 proteins varied by geography and ethnicity. |
| Jing Zhu et al., 2020, Netherlands | Proteomics | LC/MS/MS | Uniprot Swiss-Prot database | Colostrum, transition milk and mature milk from healthy mothers. | Identified 1,320 proteins and 2,096 peptides, adding 60 novel proteins to the human milk peptidome; 65% of peptides belonged to caseins, followed by osteopontin. |
| Kelly A. Dingess et al., 2021, Netherlands | Proteomics | LC-MS/MS | UniProt database, Byonic database | Transitional and mature milk from healthy mothers | Observed decreased phosphosite occupancy and O-glycosylation of β-casein during lactation, which may influence calcium binding; O-glycans localized to the β-casein C-terminal. |
| Vaksha Patel et al., 2021, England | Proteomics | LC-MS/MS | UniProt database | Mature milk from healthy mothers | Identified 136 previously unreported proteins, 21 linked to calcium metabolism; main proteins included serum albumin, lysozyme, lactotransferrin, and lactalbumin; FAM20A detected in all samples. |
| Juanjuan Guo et al., 2022, China | Proteomics | LC-MS/MS | Uniprot Swiss-Prot database, Byonic database | Colostrum and mature milk from healthy mothers and mothers with COVID-19 | COVID-19 colostrum had 4.1× higher total protein, 3.9× lower caseins, and 7.2× higher whey proteins compared to controls; differences diminished by 1 month postpartum. |
| Marincola et al., 2012, Italy | Metabolomics | H-NRM and GC-MS | Human Metabolome Database | Transitional and mature milk from healthy mothers with preterm newborn | Observed transient changes in carbohydrate composition (increased lactose) during the first 3 weeks of life; fatty acid profile was dominated by oleic and linoleic acids; no differences between late and extreme preterm infants. |
| Villaseñor A, 2014, United Kingdom | Metabolomics | LC-MS and GC-MS | KEGG, METLIN, and LipidMAPS databases | Colostrum, transitional and mature milk from healthy mothers | Identified previously undescribed metabolites, including fatty esters, aldehydes, ceramides, PG and PA; also detected amino acids, organic acids, fatty acids, sugars, TCA intermediates, cholesterol, and disaccharides across lactation. |
| Li K et al., 2018, China | Metabolomics | UPLC-Q-TOF-MS | 2002 Chinese food composition database | Colostrum, transitional milk and mature milk from healthy mothers | Identified 84 metabolites, including glycerolipids, glycerophospholipids, sphingolipids, vitamins, nucleotides, amino acids, dipeptides, steroid hormones, and others; tryptophan, histidine, and glycerolipids increased over lactation. |
| Gaitan A et al., 2018, USA | Metabolomics | LC-MS | Not reported | Transitional milk and mature milk from healthy mothers | Identified ARA as main metabolite; DHA, a DHEA precursor, may support infant brain and cognitive development; OEA predominated over PEA in mature milk; glycerol group accounted for > 90% of PG glycerols. |
| Wen L et al., 2019, China | Metabolomics | GC-MS-NMR | HMDB and NIST database | Colostrum, transitional milk and mature milk from healthy mothers and women with gestational diabetes mellitus. | Demonstrated dynamic milk metabolome over early lactation; colostrum enriched in fatty amino acids, mature milk enriched in saturated/unsaturated fatty acids and TCA intermediates; 28 metabolites differed in GDM mothers. |
| Isganaitis E et al., 2019, USA | Metabolomics | LC-GC-MS | Kyoto Encyclopedia of Genes and Genomes | Mature milk, from obese and healthy mothers. | Found 20 metabolites that were elevated in obese mothers’ milk; adenine positively correlated with maternal BMI and infant adiposity; suggested potential milk-mediated mechanisms for obesity transmission. |
| Arias-Borrego A, 2021, Spain | Metabolomics | UHPLC-MS | METLIN and HMDB database | Colostrum, from iodine-deficient mothers. | Identified 31 altered metabolites (e.g., glycerophospholipids) in iodine-deficient mothers, distinguishing them from normal, even with normal urine iodine levels; alterations may impact neurodevelopment. |
| Wu Y et al., 2021, China | Metabolomics | LC-MS/MS | Human Metabolome Database | Colostrum, transitional and mature milk from healthy mothers and mothers with diabetes mellitus | Identified 620 components — including keto acids, carboxylated acids, glycerophospholipids, fatty acids, organic compounds, nucleotides, and benzenoids — in healthy and diabetic mothers over the course of lactation. |
| Li M, 2022, China | Metabolomics | GC-TOF-MS | LECO-Fiehn Rtx5 database | Colostrum and mature milk from healthy mothers | Characterised 159 metabolites in colostrum and mature milk; 17 up-regulated and 55 down-regulated in colostrum; observed pathway differences in amino acid, lipid, inositol phosphate, glutathione, and galactose metabolism. |
| Zhang W, 2022, China | Metabolomics | HPLC-MS/MS | In-house MS2 database | Mature milk from healthy mothers | Identified two metabolites; PC1 associated with linoleic and α-linolenic acid derivatives; PC2 associated with phospholipids including glycerophospholipids and sphingomyelins, which may facilitate allergen absorption. |
| Koulman A, 2019, England | Lipidomics | LESA-MS and CID | Not reported | Transitional milk and mature milk of healthy mothers | LESA-MS revealed that mammary glands within an individual can produce distinct triacylglycerol (TG) profiles; also identified very long-chain fatty acids (C26:0 and C26:1), not previously reported in human milk. |
| George A et al., 2020, Australia | Lipidomics | LC-IM-MS | LIPID MAPS structure database, Australian Food Composition Database | Mature milk from healthy mothers with preterm newborn | Identified 205 TAGs, including 98 novel species; observed high levels of odd-chain fatty acids likely from diet; TAGs varied across the day, lactation stage, and between breasts; fish intake linked to DHA levels. |
| Xu L et al., 2020, China | Lipidomics | LC-MS/MS | Not reported | Colostrum from healthy mothers with term newborn and preterm newborn | Found significant differences in 16 lipid subclasses between term and preterm milk; preterm milk had higher phosphatidylethanolamine and phosphatidylcholine but lower diacylglycerol and ceramide; dysregulated lipids were related to metabolism, neuronal signaling, and LXR/RXR pathways. |
| Hewelt-Belka W et al., 2020, Poland | Lipidomics | RPLC-Q-TOF-MS | LIPID MAPS Structure Database (LMSD) | Colostrum, transitional milk and mature milk from healthy mothers | Mature milk contained 76 lipids at higher levels compared to colostrum, which had 40 lipids elevated; colostrum was richer in TGs with > 20 carbons, ether glycerophospholipids, and LC-PUFAs like eicosatetraenoic acid. |
| Song S et al., 2021, China | Lipidomics | LC-MS-MS | LIPID MAPS Structure Database | Colostrum, transitional milk and mature milk from healthy mothers | Phosphatidylcholine was the most abundant lipid; plasmalogens and polyunsaturated phospholipids decreased over lactation; early changes included declines in phosphatidylcholines and phosphatidylglycerols and increases in lysophosphatidylethanolamines and lysophosphatidylcholines; lipid profile stabilized after ~200 days. |
| Alexandre-Gouabau M et al., 2019, France | Glycomics, lipidomics, metabolomics, proteomics | LC-HR-MS | LIPID Metabolites and Pathways Strategy Database (LipidMaps), Human Metabolite Data base (HMDB), Biofluid Metabolites Database (MetLin), Milk Metabolome Database (MCDB) | Mature milk from healthy mothers | Identified biomarkers (arginine, tyrosine, hydroxybutyrate, niacinamide, choline, and lacto-N-fucopentaose I) predictive of infant weight gain; arginine, tyrosine, medium-chain fatty acids, triglycerides, and phospholipids were associated with faster growth, whereas oleic acid, plasmalogens, ceramide, and very long-chain TGs were associated with slower growth. Non-secretor mothers had very low 2′-FL, while secretors had high 2′-FL levels. |
| McJarrow P et al., 2019, New Zealand | Glycomic, lipidomic | HPLC-MS | Not reported | Transitional milk and mature milk from healthy mothers | Found higher concentrations of HMOs and ganglioside GD3 in transitional milk compared to mature milk, except for 3-fucosyllactose and GM3, which were higher in mature milk. |