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Abstract
The human milk microbiome is thought to partly contribute to the assembly of the infant gut microbiome, a microbial community with important implications for infant health and development. While obesity has well-established links with the adult gut microbiome, less is known about how it affects the human milk microbiome. In this scoping review, we synthesize the current literature on the microbial composition of human milk by maternal weight status, defined broadly as BMI (prepregnancy and postpartum) and gestational weight gain (GWG). This study followed the a priori protocol published in Prospero (registration #: CRD42020165633). We searched the following databases for studies reporting maternal weight status and a characterization of milk microbiota through culture-dependent and culture-independent methods: MEDLINE, Embase, Web of Science, CINAHL, and Scopus. After screening 6,365 studies, we found 20 longitudinal and cross-sectional studies investigating associations between maternal weight status and the composition of the milk microbiome. While some studies reported no associations, many others reported that women with a pre-pregnancy or postpartum BMI characterized as overweight or obese, or with excessive GWG, had higher abundances of the genus Staphylococcus, lower Bifidobacterium abundance, and lower alpha diversity (within-sample diversity). This review suggests that maternal weight status is minorly associated with the composition of the milk microbiome in various ways. We offer potential explanations for these findings, as well as suggestions for future research.
Citation: Daiy K, Harries V, Nyhan K, Marcinkowska UM (2022) Maternal weight status and the composition of the human milk microbiome: A scoping review. PLoS ONE 17(10): e0274950. https://doi.org/10.1371/journal.pone.0274950
Editor: Corrie Whisner, Arizona State University, UNITED STATES
Received: September 23, 2021; Accepted: September 7, 2022; Published: October 3, 2022
Copyright: © 2022 Daiy et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All data files are available on https://osf.io/r786n/.
Funding: The authors received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Obesity—a global epidemic with far-reaching implications for maternal and child health—is characterized by excess adiposity, increased energy intake, reduced energy expenditure, and systemic low-grade inflammation [1]. Recent research has implicated the gut microbiome as a key mediator in the pathophysiology of obesity [2]. In particular, individuals with obesity harbor gut microbiota with low diversity and greater metagenomic capacity for dietary energy harvest [3].
Maternal nutritional status may contribute to intergenerational cycles of obesity via microbiome-related pathways. Maternal obesity and gestational weight gain (GWG) are associated with increased risk for childhood obesity and metabolic syndrome [4, 5]. Additionally, obesity in pregnant women is associated with alterations in maternal gut microbiome communities. For instance, one study reported that pregnant women with a prepregnancy body mass index (BMI) of overweight (defined as 25 to <30 kg/m2) or obese (defined as >30 kg/m2) have higher abundances of Bacteroides and Staphylococcus in the gut microbiome compared to women with normal BMI (defined as <24.9 kg/m2) [6]. This study also reported that excessive GWG–defined as greater than 16.0 kg for women with normal weight or 11.5 kg for women with overweight or obesity [7]–is associated with increased levels of Bacteroides in the maternal gut [6]. Another study found that women with overweight prepregnancy BMI also exhibit increased Staphylococcus, Escherichia coli, and lower Bifidobacterium than women with normal weight, compositional features that are typically observed in non-pregnant individuals with obesity [8]; however, this study [8] found that women with overweight prepregnancy BMI had lower Bacteroides, contrasting to other work [6]. While this evidence suggests that maternal weight status influences the maternal gut microbiome, little is known about how maternal weight status affects other maternal microbiomes involved in the early life maternal-infant microbial exchange, such as the milk microbiome.
The initial colonization and composition of infant gut microbial communities is thought to be critical for immune and metabolic programming, and is associated with infant health outcomes, including overweight and obesity [9]. For instance, greater abundance of Staphylococcus and lower Bifidobacterium in infancy were associated with increased risk of childhood obesity at 7 years [10]. Another study found that the composition of infant gut microbiome in early infancy and at 2 years of age predicted childhood BMI, and that the taxonomic subset associated most strongly with later childhood BMI overlapped with the gut microbiota of women with overweight BMIs, obesity, and excessive GWG [11]. While many early life factors affect the infant gut microbiome (e.g., delivery mode, antibiotics [12]), breastfeeding is another critical factor, providing infants with a continuous source of microbes and prebiotic factors (i.e., human milk oligosaccharides) that help to seed the infant’s first gut microbiome communities.
Human milk contains a low-biomass community of microorganisms known as the milk microbiome [13], which accounts for a small portion (27%) of infant gut bacteria [14]. Although previously thought to be sterile, research involving culture-dependent approaches (culturing of microbes on selective media) and culture-independent approaches (i.e., next-generation sequencing) have shown that human milk contains viable bacteria [15]. The origin of the human milk microbiome is uncertain–milk microbes may originate from the maternal skin, the infant oral cavity through suckling, breast tissue, and from the maternal gut microbiome through an immunologically-mediated “entero-mammary” pathway in late pregnancy [16–18]. Milk microbiome composition can be measured in terms of the relative abundance of different microbial taxa, as well as by its alpha diversity, or the diversity of taxa within samples. Previous systematic and scoping reviews have identified a broad range of factors that influence the composition of the milk microbiome [19–22]. However, to the best of our knowledge, no reviews to date have specifically examined how, and to what extent, maternal weight status is associated with the composition of milk microbial communities. As the human milk microbiome is a small, yet potentially important contributor to the assembly of an infant’s first gut microbiome, delineating how maternal weight status influences its composition is a key step in understanding the maternal factors that contribute to intergenerational cycles of obesity.
Given that the milk microbiome is an emerging area of research, a scoping review design is optimal for examining the associations between maternal characteristics and the composition of the milk microbiome. In this scoping review, we aimed to investigate the extent and range of knowledge on the association between maternal weight status, broadly defined, and the composition of the milk microbiome.
Methods
The purpose of a scoping review is to rapidly explore and describe key concepts and evidence, often in underexplored areas of study. Compared to systematic reviews, which gather specific empirical evidence with a narrow and focused research question, scoping reviews are more flexible in the breadth of literature reviewed, thus allowing authors to comprehensively review the “scope” of a topic [23]. Because of the breadth of their research questions, scoping reviews are also suited to synthesizing topics with heterogenous or disparate evidence [24]. Thus, a scoping review is well-suited to exploring relationships with the milk microbiome.
This review follows an a priori protocol deposited in PROSPERO; because of the 2020 SARS-CoV-2 pandemic, it was published by PROSPERO without an official eligibility check. Its registration number is CRD42020165633 and it may be accessed at https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020165633..
Peer-reviewed journal articles describing prospective longitudinal, cross-sectional, cohort, observational, and experimental studies were eligible for inclusion if they measured relationships between maternal weight status and the human milk microbiome. Maternal weight status could be measured as any of the following: GWG (as defined by Institute of Medicine [7]) gestational change in BMI, prepregnancy maternal weight, BMI, or percentage body fat, and/or postpartum maternal weight, BMI, or percentage body fat. For inclusion, the human milk microbiome could be measured by culture-dependent and culture-independent based methods at a single or multiple time points during lactation. Culture-dependent based methods refer to culturing, isolating and characterizing microbial taxa by phenotype and/or genotype (such as through whole genome sequencing). Culture-independent based methods include next generation sequencing techniques (16S ribosomal RNA [rRNA]), amplicon analysis (metataxonomics), qPCR (i.e., real-time PCR), total DNA sequencing (metagenomics), and gel electrophoresis.
Studies were excluded from this scoping review if they included women who were reported smokers, had a sample of women of whom the majority (>50%) had gestational diabetes, or included women with mastitis as these are known to impact human milk composition, and thus, may affect the milk microbiome [19–21, 25]. Non-human studies and studies in languages other than English were also excluded. No infant characteristics (e.g., gestational age, age at sample collection, birth mode) were included in the inclusion or exclusion criteria.
To identify potentially relevant articles, five bibliographic databases were searched, covering all studies published prior to February 24, 2022 (which includes an original search up to February 13, 2020, and an updated search up to February 24, 2022). These databases were MEDLINE, Embase, Web of Science, CINAHL, and Scopus. Details of database platforms are presented in S1 Table.
Each database was searched from inception (without date limits). No records were excluded from the search results before screening because of publication type. Relevant conference papers were identified in the screening process. The conference papers themselves were not included, because through search updates, we identified related publications with fuller reporting.
The MEDLINE and other search strategies were drafted by an experienced librarian (KN) in collaboration with the other authors and was peer reviewed by an independent medical librarian using the PRESS Guidelines [26]. The MEDLINE search as peer reviewed and conducted in 2020 is presented in S2A Table; the 2022 database search updates for all five bibliographic databases are presented in S2B–S2F Table. The MEDLINE search was translated into appropriate syntax and controlled vocabulary (if available) in the other databases. All the searches shared the same structure: queries retrieving papers about breastmilk, queries retrieving papers about the microbiome (including culture dependent based methods and culture independent based methods), and queries about maternal BMI.
Shortly before submission, forward citation chaining was conducted via Citation Chaser to maximize retrieval of relevant papers [27].
Two reviewers (KD & VH) independently screened the results of the database searches in Covidence [28] in two phases: title-abstract screening and full-text screening. Discrepancies were resolved by a third reviewer (UMM). Reviewers contacted the original authors to attempt to gain access to any important, missing information. A PRISMA flow chart was created to record the search, including the results of the entire search, inclusions, and exclusions (Fig 1; [29]). Data extraction was done independently by two reviewers (KD & VH) within Covidence, based on a form developed for the purpose by the authors. Disagreements were resolved by a third party, UMM.
We chose not to include a risk of bias assessment due to the exploratory nature of this area of research. We present the results in a table of key findings (Table 1) and in a narrative format. For a table with all extracted data, including additional characteristics of each of the studies, see S3 Table.
Results
Results of key findings from extracted data are presented in Table 1. The composition of the milk microbiome composition, as observed by each study, is presented in Table 2.
Study characteristics
We found twenty studies (Tables 1 and 2; S3 Table) investigating associations between the human milk microbiome and maternal weight status. Only 4 of the 20 studies explicitly aimed to investigate relationships between maternal weight status and the milk microbiome [32, 34, 42, 48]. The remaining 16 out of 20 studies investigated weight status-milk microbiome relationships as part of their exploration of the data, not as a specific objective. Maternal weight status was commonly measured in three ways: prepregnancy BMI, postpartum BMI, and GWG. Most studies (17/20) characterized the milk microbiome through 16S rRNA sequencing, while some (6/20) measured specific microbial abundances through qPCR and others through culturing of microbes on selective media, which was often combined with other sequencing techniques (Table 1). One study [37] utilized 18.5S and 5.8S sequencing, which are techniques specific for the assessment of fungal communities. Two studies [37, 38] characterized milk microbial communities through the cultivation of bacteria and fungi on selective media.
In the extracted studies, the time of milk collection ranged from 1–2 days to 5 years postpartum. Human milk composition changes over the lactation period and accordingly, lactation is divided into three stages: colostrum (1–5 days), transitional milk (5–21 days), and mature milk (21+ days; [50]). Just under half of included studies only collected mature milk (8/20), while other studies sampled both colostrum and mature milk (2/20), colostrum only (1/20), colostrum and transitional milk (1/20), transitional and mature milk (3/20), and colostrum, transitional, and mature milk together (5/20). Most studies utilized a cross-sectional study design (14/20), while others (6/20) examined the milk microbiome longitudinally over the course of lactation. Six (6/20) studies collected milk via manual expression, seven (7/20) studies collected milk with an electric or manual breast pump, two studies (2/20) included both manual and breast pump expression, and one study did not report how milk was collected. Nearly all included studies (14/20) had participants who took antibiotics in the gestational and/or postpartum period, three studies (3/20) excluded women who took antibiotics from analyses or from participating, and three (3/20) other studies did not report any information about antibiotic use. Studies had sample sizes ranging from 10 to 393 lactating women, and were conducted in various global locations, including the U.S, Canada, Finland, China, Taiwan, Guatemala, Spain, New Zealand, the Philippines, and South Africa, to name a few.
The studies extracted in this review differed in how they adjusted for confounding variables in their statistical analyses of associations between maternal weight status and milk microbiome composition. While 14 studies did not report any adjustment for confounders, 6 studies did report adjustment. These confounders adjusted for included postpartum milk collection week, maternal age, antibiotic use, mode of delivery, gestational age, sequencing batch effects, and GWG, among others.
Across all studies, the milk microbiome was composed of similar common bacterial taxonomic groups. Common phyla included Proteobacteria, Firmicutes, Actinobacteria and Bacteroidetes [34, 40, 51]. Common genera included Staphylococcus (predominant in 13/20 studies, range of relative abundance: 5–50%), Streptococcus (12/20 studies, 2.9–45.2%), Acinetobacter (6/20, 3.5–14.3%), Pseudomonas (4/20, 11.3–43.4%), Corynebacterium (5/20, 1.3–6.0%), and to a lesser extent, Bifidobacterium (4/20 studies, <1% abundance). It is important to note that the detection of Bifidobacterium is difficult through rRNA sequencing and often depends on the primers used and the type of hypervariable regions of 16S rRNA gene that were sequenced [52]. Only a few studies (6/20) employed specific approaches to detect Bifidobacterium and other low-abundance genera [30, 31, 45, 46, 48, 49].
Maternal weight status and the overall composition and diversity of the milk microbiome
Many included studies (12/20) found that BMI in the prepregnancy and postpartum periods were associated with the milk microbiome, although inconsistently and with low effect sizes. In one of the largest investigations of the milk microbiome to date (n = 393), Moossavi and colleagues [40] found that prepregnancy BMI was associated with the overall composition of the milk microbiome, although explaining <1% of its variation. Among Slovenian women, Treven et al. [43] reported that maternal postpartum BMI was not significantly associated with the specific patterns of the human milk microbiome (no effect size or p-value reported). Pace et al. [44] observed that in a cross-geographic comparison, there was not a significant relationship between postpartum BMI and overall milk microbiome composition (no effect size or p-value reported). Yan et al. [46] did not observe a statistically significant association between family-level milk microbiome community structure and maternal postpartum BMI (R2<0.2; p>0.05). Similarly, Williams and colleagues [34] observed no differences in overall composition at the phylum level between women of different prepregnancy BMIs (no effect size reported).
Prepregnancy and postpartum BMI appeared to be negatively associated with the alpha diversity of the milk microbiome, although some studies reported no association. According to Cortes-Macias et al. [48], prepregnancy BMI was negatively associated with alpha diversity (Shannon diversity: rho = -0.05, p = 0.582; richness: rho = -0.03, p = 0.753). Similarly, Cabrera-Rubio et al. [30] reported a negative association: women with obese prepregnancy BMI had more homogenous (less diverse) microbiota than other women (no effect size or p-value reported). Another study by Asbury and colleagues (conference abstract; [35]) demonstrated that over the first 8 weeks postpartum, women with normal prepregnancy BMIs had greater species evenness (i.e., the distribution of the abundances of various taxa [53]) compared to women with overweight or obese prepregnancy BMIs; however, microbial richness, or the number of different species in a sample, was not significantly associated with BMI. In a later study by the same research group, Asbury et al. [41] reported that while milk alpha diversity increased over the first 8 weeks among women with normal prepregnancy BMIs, this increase in diversity was delayed among women with overweight and obese BMIs (p = 0.04, no effect size reported). Finally, one study [42] found no significant differences in richness or diversity by prepregnancy BMI or by 3-month postpartum BMI.
Maternal weight status and specific taxa in the milk microbiome
Across the studies extracted by our review, maternal weight status appeared to be variably associated with the abundance of specific microbial taxa, particularly with Staphylococcus, Streptococcus, and Bifidobacterium. Higher prepregnancy BMI was associated with greater abundance of the phylum Firmicutes, greater abundance of Staphylococcus, lower abundance of Bifidobacterium, and lower Streptococcus (although this latter relationship was more variable). At the genus level, Davé and colleagues [32] observed in a small, cross-sectional sample of Mexican-American women that prepregnancy BMI was negatively associated with Streptococcus abundance (r = -0.67; p = 0.048) and positively associated with alpha diversity (r = 0.77; p = 0.016). Similarly, Cortes-Macias and colleagues [48] observed that compared to women with overweight prepregnancy BMI, women with normal BMI had greater Bifidobacterium (incidence rate ratio [IRR]: 4.67 [95% CI: 2.53–8.64]), lower Staphylococcus (IRR: 0.89 [95% CI: 0.83–0.96]), and greater Ralstonia (IRR: 1.16 [95% CI: 1.03–1.32]). Lundgren and colleagues [39] observed that milk microbial composition clustered into four breastfeeding microbiome types (BMTs). Prepregnancy BMI was associated with “breastfeeding microbiome type” (BMT), such that for every one-unit increase in prepregnancy BMI, there was an increased odds for belonging to BMT1 (high Staphylococcus and Streptococcus, low alpha diversity) versus BMT 2 (high Streptococcus, high alpha diversity; [OR = 1.13 (95% CI: 1.02, 1.24)]), and BMT 3 (high Acinetobacter) compared to BMT2 (high Acinobacter and Pseudomonas, low alpha diversity; [OR = 1.12 [95% CI: 1.01–1.25]). That prepregnancy BMI was associated with BMT1 is of interest: BMT1 had a higher abundance of Firmicutes, a phylum that is typically higher in the overweight and obese gut microbiome [54]. Moossavi et al. [40] note that higher prepregnancy BMI was associated with less diversity within the phylum Proteobacteria and greater diversity within the phylum Firmicutes. LeMay-Nedjelski et al. [42] reported that women with obese prepregnancy BMI had lower Proteobacteria (IRR: 0.62 [95% CI: 0.43–0.90]), as well as greater Bacteroidetes (IRR: 3.70 [95% CI: 1.61–8.48]) and Actinobacteria (IRR: 2.34 [95% CI: 1.38–3.98]) compared to women with overweight and normal BMIs.
In terms of postpartum BMI, Ding et al. [38] found that postpartum BMI was positively associated with Staphylococcus (Pearson’s r = 0.325) and Streptococcus (r = 0.194) and negatively correlated with Lactobacillus (r = - 0.204) although these relationships were not statistically significant. Interestingly, the finding that postpartum BMI was positively associated with Streptococcus contrasts with the findings of Davé et al. [32], who reported a negative association. Among women in the Philippines, Bayaga et al. [45] reported that women with overweight postpartum BMI had lower counts of Bifidobacterium and Lactobacillus for the first 4 months postpartum than others (no effect size reported; p = 0.017). LeMay-Nedjelski et al. [42] showed that women with obese BMIs at 3 months postpartum had greater Staphylococcus ((IRR: 2.50 [95% CI: 1.09–5.72]) compared to overweight women, greater Corynebacterium compared to overweight and normal weight women (IRR: 5.13 [95% CI: 1.79–14.70], and greater Actinobacteria (IRR: 2.34 [95% CI: 1.38–3.98]) compared to overweight and normal weight women. Focusing on class-level differences, Li et al. [36] observed that among Mayan women in Guatemala, a normal postpartum BMI was associated with higher proportions of the classes Alphaproteobacteria and Betaproteobacteria (no effect size or p-value reported).
These relationships between BMI and Staphylococcus, Streptococcus, and Bifidobacterium also appear to hold over the course of lactation. Collado and colleagues [31] found that compared to women with normal BMI, women with overweight BMI harbored higher counts of Staphylococcus-group bacteria at 1 month (median, overweight/obese women (BMI > 25/kg/m2) = 4.94 gene copies/mL milk; median, “normal”/underweight women (BMI < 25 kg/m2) = 4.40 gene copies/mL milk). The study also found that women with overweight/obese BMI had marginally lower counts of Bifidobacterium-group bacteria at both 1 month (median, overweight/obese women = 5.30; median, “normal”/underweight women = 5.84 gene copies/mL of milk) and 6 months (median, overweight/ obese women = 5.19 gene copies/mL; median, “normal”/underweight women = 5.86; [28]). In a similar study, Cabrera-Rubio and colleagues [30] observed that maternal prepregnancy BMI was positively associated with Lactobacillus in colostrum (r = 0.6, p = 0.026), positively associated with Staphylococcus (r = 0.560, p = 0.038) and negatively associated with Bifidobacterium at 6 months (r = 0.651, p = 0.012). This study also found that over the first 6 months postpartum, women with obesity had higher total bacterial counts in milk (ratio: 0.34 [95% CI: 0.08–0.60]; p = 0.011), 0.48 times fewer Bifidobacterium (ratio: -0.48 [95% CI: -0.78–0.18]; p = 0.002), 0.62 times more Staphylococcus abundance (ratio: 0.62 [95% CI: 0.30–0.93]) and 0.52 times more Lactobacillus (ratio: 0.52 [95% CI: 0.02–2.02]; p = 0.038) compared to women with normal prepregnancy BMIs [30]. Asbury et al. [41] reported that women with normal prepregnancy BMIs had increased Corynebacteria and Escherichia-Shigella abundance over time (no effect size reported; p <0.05) and an inverted parabolic shift in Streptococcus in the first 6 weeks postpartum, patterns which contrasted with women with overweight and obese BMIs. The same study also found that women with obese prepregnancy BMI had higher Staphylococcus and lower abundance of Acinetobacter, Streptococcus and Prevotella in milk compared to women with normal prepregnancy BMIs over the first 6 weeks postpartum (p < 0.05; no effect size reported). Finally, Williams and colleagues [34] found that postpartum BMI was negatively correlated with the genus Bacteroides (Pearson’s r = -0.46; p = 0.037).
Interactions between weight status, feeding mode, and the milk microbiome
One study [48] investigated the possibility that relationships between maternal weight status and the milk microbiome are dependent on feeding mode. Cortes-Macias et al. [48] reported that prepregnancy BMI was associated with the overall milk microbiome composition in exclusively breastfeeding (EBF) women, but not in mixed-feeding (MF) women (EBF: Adonis Bray-Curtis R2 = 0.0254, p = 0.05; MF; Adonis Bray-Curtis R2 = 0.022, p = 0.029). Notably, this was only observed in women with normal prepregnancy BMI, and not in women with overweight prepregnancy BMI. EBF women with normal prepregnancy BMI also had higher diversity and richness, higher Bifidobacterium (no effect size reported; p = 0.033), and lower Pseudomonas (no effect size reported; p<0.01) compared to other groups [48]. These findings suggest that relationships between prepregnancy weight status and the milk microbiome may be partly dependent on feeding mode, particularly among women with normal prepregnancy BMIs. Lastly, Butts et al. [47] observed no significant differences in the milk microbiome composition at the genus and phylum level according to postpartum BMI categories (no effect size or p-value reported).
Gestational weight gain and the milk microbiome
Six studies (6/20) reported relationships between GWG and the milk microbiome. In terms of milk alpha diversity, Cortes-Macias et al. [48] found that GWG was positively associated with alpha diversity; specifically, women with normal GWG had lower milk microbiome diversity (no effect size reported; p = 0.026). Similarly, according to Lundgren et al. [39], for every 10 pounds gained during gestation, the milk microbiome exhibited a 1-unit increase in alpha diversity (Simpson’s diversity, β = 0.23, p = 0.022).
In terms of specific taxa in milk, the results with GWG corroborated other findings involving prepregnancy and postpartum BMI; greater GWG appeared to be linked to greater abundance of Staphylococcus, Streptococcus, and lower Bifidobacterium. For example, Lundgren et al. [39] reported that women with differing GWG (normal vs. excessive) had distinct patterns of milk microbiome composition; increasing maternal GWG (per 10 pounds) was associated with decreased probability of belonging to BMT1 (high Staphylococcus and Streptococcus, low alpha diversity) vs BMT 2 (high Streptococcus, high alpha diversity) (OR = 0.66 [95% CI: 0.44–1.00]). Similarly, Cabrera-Rubio et al. [30] found that women with excessive GWG had more homogenous milk composition and higher counts of Staphylococcus aureus (median bacterial count, excessive GWG = 3.79; median bacterial count, normal GWG = 3.00; p = 0.03) at 1 month, higher Lactobacillus (median bacterial count, excessive GWG = 6.50; median bacterial count, normal GWG = 5.91; p 0.03) and lower Bifidobacterium at 6 months (median bacterial count, excessive GWG = 4.82; median bacterial count, normal GWG = 5.85; p = 0.02). Collado et al. [31] found that excessive GWG was associated with higher Staphylococcus in colostrum (p = 0.05; marginally statistically significant) and lower Bifidobacterium at 1 month (p = 0.03). Additionally, these authors ran mixed-models and showed that excessive GWG was associated with 0.42 times fewer Bifidobacterium-group bacteria in milk throughout the course of lactation (β = -0.42, p = 0.004, [95% CI: -0.71 to -0.14]). Cortes-Macias et al. [48] found that compared to women who had excessive GWG, women with normal GWG had greater incidence of Bifidobacterium (IRR: 3.20 (1.71–5.98)) and lower Ralstonia (IRR: 0.53 [95% CI: 0.46–0.61]); contrasting to findings from other studies, women with normal GWG had greater incidence of Streptococcus (IRR: 1.38 [95% CI: 1.27–1.51]). Cortes-Macias and colleagues [48] also found that mixed-feeding women with normal GWG had marginally greater abundance of Staphylococcus (p = 0.049) and Pseudomonas (p = 0.019).
Maternal weight status and non-bacterial components of the microbiome
Lastly, while most of the extracted studies (19/20) investigated only the composition of the milk bacteriome, one study described the composition of the milk fungal composition, or mycobiome, alongside the bacteriome of milk [37]. This cross-sectional, cross-geographic study (Spain, Finland, South Africa and China) found no associations with overall milk mycobiome composition and prepregnancy BMI. However, prepregnancy BMI was positively associated with the abundance of fungal genera Davidella and Sistotrema among South African women, and Staphylococcus and Bacilli abundance in Spanish women, and was negatively associated with Ascomycota and Sistotrema in Chinese women, and with unclassified Bacilli in Finnish women [37].
Discussion
In this review, we investigated the scope of current knowledge on the relationship between maternal weight status and the composition of the milk microbiome. We conducted a comprehensive search in electronic databases and found 20 studies, 11 of which only reported significant associations, 4 reported both significant and null associations, and 5 reported only null associations between maternal weight status and the milk microbiome. We found that the aims and objectives of these studies varied—while a few studies explicitly focused on delineating maternal weight-milk microbiome relationships, most others reported these associations in their exploration of the data. As in previous reviews [19, 22], milk microbiota was typically characterized by high relative abundances of Staphylococcus, Streptococcus, Acinobacter, and other microbial species that overlap with the communities of the skin microbiome (Tables 1 and 2). In general, women who had an overweight or obese BMI in the prepregnancy or postpartum periods, or who experienced excessive GWG, all harbored milk microbiota with higher Staphylococcus, higher Streptococcus (although this was more variable), lower Bifidobacterium abundance, and lower alpha diversity than women with lower BMIs or normal GWG (Tables 1 and 2). However, despite these findings, weight status does not appear to be a major predictor of overall milk microbiome composition. In fact, one study reported that maternal BMI explained less than 1% of the variation in the milk microbiome [40], and several others reported that there were no significant associations between maternal weight status and overarching milk microbial composition and community structure [43, 44, 46]. In all, the composition of the milk microbiome may be mildly affected by maternal weight status. We suggest that a) the composition of the maternal gut microbiome, b) maternal diet, and c) breastfeeding and delivery practices may explain this minor effect of weight status on the milk microbiome.
First, the weight-based differences in the milk microbiome reported by the included studies may be explained by differences in the maternal gut microbiome composition attributable to the metabolic effects of overweight or obesity. The composition of the human gut microbiome has been shown to be interlinked with metabolic status; individuals with obesity harbor gut microbiota with decreased abundance of the phylum Bacteroidetes, increased Firmicutes, lower alpha diversity, and altered microbial gene expression favoring increased energy uptake [3, 55–57]. The gut microbiota of women during pregnancy and the postpartum period is associated with maternal weight status. Pregnant women with obesity and excessive GWG harbor higher Staphylococcus, including the pathobiont Staphylococcus aureus, and lower Bifidobacterium abundances in the gut microbiome [6]. Over the course of pregnancy, the maternal gut microbiome appears to shift to a pro-inflammatory, insulin-resistant state, a change that persists in the maternal gut through the early postpartum period [58, 59; but see 60]. Excess GWG or pre-existing overweight/obesity may amplify or modulate these gut microbiota characteristics [61].
Several studies [30, 31, 38, 39, 42] found that women with overweight/obesity or excessive GWG had higher Staphylococcus abundance in the milk than women with normal BMI and normal GWG. Staphylococcus is often classified as a “core” bacterial genus in milk [13] and is thought to populate human milk from maternal skin microbiota [62]. However, a high abundance of Staphylococcus spp. in the gut is associated with the inflammatory states of obesity [10]–thus, it is plausible that high Staphylococcus in milk may arise from similarly high Staphylococcus in the gut microbiota of women with higher weight status and excess GWG. Although less frequently observed in this review [30, 32], the observation that overweight, obesity and excessive GWG are correlated with lower Bifidobacterium levels in milk may also be explained by weight-associated shifts in the gut microbiome. In the gut microbiome, Bifidobacterium carries out a variety of functions, such as improving glucose tolerance and reducing plasma levels of lipopolysaccharides [63]. Low abundance of Bifidobacterium in the gut microbiome is linked to the low-grade inflammation, gut dysbiosis (including the proliferation of "energy-extractive" microbial species), and metabolic dysregulation found in obesity [64]. In short, the gut microbiome may be affected by maternal weight status, which in turn, may shape milk microbiome composition.
One possible mechanism is the hypothesized entero-mammary pathway, in which maternal gut microbes travel through circulation and feed into the milk microbiome to subsist on prebiotic human milk oligosaccharides [16–18]. Through this pathway, shifts in maternal gut microbiota related to overweight/obesity or excessive GWG may pass on to the milk microbiome. However, the infant oral cavity, the maternal skin microbiome and the surrounding environment are all other sources that seed the milk microbiome [17], and the maternal gut is likely only a small factor shaping its composition. Additional research could attempt to elucidate the relative contribution of the maternal gut microbiome in driving weight-based differences in milk microbial taxa and diversity.
Second, maternal diet may shape weight-based differences in the milk microbiome, either by directly influencing milk microbiota or by influencing other factors of milk composition (e.g., milk macronutrient profiles, human milk oligosaccharides, etc.). Dietary intake during pregnancy is associated with both maternal BMI and GWG [65] and thus, may explain weight-related variations in the milk microbiome. Previous research has shown that maternal fat and fiber intakes during gestation and lactation are associated with the the macronutrient composition of milk [66], the milk microbiome [34, 51, 67], as well as the maternal gut microbiome [68–70]; these studies suggest that maternal diet may directly or indirectly shape milk microbial communities. Based on our review, it is evident that the current literature assessing maternal weight status-milk microbiome relationships also accounts for maternal dietary intake. For instance, two included studies [34, 40] investigated how maternal diet was related to the composition of the milk microbiome in addition to maternal weight status. Williams and colleagues [34] found that saturated and monounsaturated fatty acid intake were inversely associated with Corynebacterium abundance and total carbohydrate intake was inversely associated with Firmicutes abundance. One study [40] employed structural equation models to demonstrate that the effect of maternal BMI on the milk microbiome was partly driven by effects of maternal diet; the models also demonstrated that maternal BMI influenced the milk microbiome directly and indirectly, by affecting other components of milk (e.g., human milk oligosaccharides, lipids, and cytokines). Adherence to dietary patterns, such as the “Western” pattern–high in saturated fats, sugar, and ultra-processed foods and low in fiber–not only increases risk of obesity, but is also associated with gut dysbiosis [71]. One possibility is that “Western”-like diets may similarly impact milk microbiome communities directly or indirectly by influencing other milk compositional components or the maternal gut microbiome [40].
Third, breastfeeding practices, stage of lactation, and delivery mode may also explain maternal weight-related differences in milk microbiome composition. Women with obesity and excessive GWG report shorter breastfeeding durations, due to various cultural, psychosocial and physiological factors [72]. In addition, it has been shown that the duration of breastfeeding predicts milk macronutrient composition [73]. Following this logic, shorter durations or less exclusivity of breastfeeding in women with overweight or obesity may alter the composition of milk microbiome (or other milk compositional factors) by affecting how long or how frequently the breast is exposed to the infant oral cavity and resident oral microbes, as well as the skin microbiota around the areola [40]. Indeed, in one study in this review [48], prepregnancy BMI and GWG interacted with breastfeeding status to influence the milk microbiome. Specifically, prepregnancy BMI was associated with overall milk microbiome composition only in exclusively breastfeeding women, but not in mixed-feeding women. Similarly, breastfeeding status only influenced the milk microbiome in women with normal GWG, and not in women with excessive GWG [48]. Along with other studies in this review, these results suggest that breastfeeding patterns and maternal weight status influence the milk microbiome independently and in conjunction with each other. Thus, weight-related differences in milk composition may be partly driven by breastfeeding practices.
Like other components of milk composition, the milk microbiome undergoes transitional changes during the period of lactation; thus, stage of lactation may drive the findings we observe in this review. For instance, one study found that over the course of lactation, there were increases in total bacterial concentration in milk, and to a lesser extent, increasing abundances of specific genera, such as Bifidobacterium, Staphylococcus and Lactobacillus [74]. Four studies [33, 36, 40, 48] reported that stage of lactation was associated with milk microbiome composition, while one study explicitly controlled for stage of lactation by collecting all samples at the same postpartum time point [38]. Stage of lactation, if not accounted for, may confound effects of maternal weight status on milk microbiome composition.
Moreover, women with obesity are more likely to have Caesarian sections [75] and thus, delivery mode may partly explain weight-related differences in the milk microbiome. Infants born via Caesarian section have greater abundances of skin microbes, such as Staphylococcus, across various body sites, including the infant oral cavity [76, 77], a site that is known to influence the milk microbiome [40]. However, three of the reviewed studies [41, 42, 48] accounted for delivery mode as a confounder and still observed associations between maternal weight status and milk microbiome composition. Thus, this brings into question whether delivery mode is a strong driver of weight-based variation in the milk microbiome.
Directions for future research
We offer suggestions for future research to help clarify the relationship between maternal weight status and the milk microbiome. First, many investigations identified in our review relied on BMI, a convenient but sometimes inadequate proxy for maternal nutritional status [62]. Maternal adiposity can be more accurately and precisely measured using skinfolds or dual energy x-ray absorptiometry (DXA). Additional research could employ these techniques to evaluate whether maternal body composition, in conjunction with maternal diet and glucose tolerance status [42], are associated with milk microbiome. Second, the association between maternal weight status and the milk microbiome may be confounded with maternal diet and breastfeeding behavior. We suggest that future research attempt to tease apart these relationships by collecting detailed and triangulated measures of maternal diet (e.g., 24-hour recalls, Food Frequency Questionnaires), breastfeeding behavior (e.g., frequency of breastfeeding), alongside maternal anthropometrics and milk microbiome samples. Third, it remains unclear whether the milk microbiota has clinically and biologically meaningful impacts on intergenerational cycles of obesity. Although preliminary evidence suggests that the milk microbiome colonizes the infant gut to a measurable degree [14, 17], it is not known whether variation in milk microbiome composition (stemming from weight status or other maternal factors) begets variation in infant metabolic outcomes, such as in growth patterns or infant adipose deposition [78]. In fact, whether the milk microbiome independently impacts infant health and development has remained an unanswered question for some time [40, 62]. Future research could address this possibility, for example, by employing statistical models to assess whether milk microbiome variation predicts variation in infant gut microbiota and growth. Fifth, the populations included in this review are from industrialized, high-income, and urbanized countries, and likely do not represent the full scope of global variation in the human milk microbiome and its relationship with weight status. Although some cross-geographic research has been conducted on the human milk microbiome [79], future researchers could investigate how relationships between maternal weight status (using non-BMI measures; [80]) and the milk microbiome vary across populations exposed to different nutritional environments.
Strengths and limitations
The strengths of this review include the adherence to an a priori protocol (registration #: CRD42020165633) and the breadth of the guiding research question, allowing us to identify a broad overview of an area of literature that is still underexplored. The findings of this scoping review can be used to guide research on the relationship between maternal metabolic states, the milk microbiome, and intergenerational risk of obesity. This scoping review also has limitations that warrant consideration. First, included studies differed in many ways including: their methods of milk collection, DNA extraction and amplification, sequencing depth, bioinformatic approaches, participant characteristics (e.g., maternal age, mode of breastfeeding), infant characteristics (e.g. gestational age, birth mode, age at data collection), and in the restrictiveness of inclusion/exclusion criteria. In particular, the hypervariable regions that were sequenced via 16S rRNA sequencing varied substantially between studies. This prevents side-by-side comparisons of results and thus limits the conclusions that can be drawn through analysis. In particular, the studies conducted by Asbury et al. [35, 41] had study objectives focused solely on pre-term infants (<37 weeks gestation) in their sample participants. Gestational age is a known influence on milk microbiome composition and thus caution should be taken when comparing results between pre-term and full-term infants [74, 81]. Second, there may have been publication bias towards statistically significant results in the studies we reviewed—for example, excluded studies may have not reported statistically insignificant relationships between maternal weight status measures and milk microbiome composition. Third, as mentioned above, the populations represented by these extracted studies are mostly from industrialized and urbanized regions of the world. Therefore, with some exceptions, the included studies likely do not represent global variation in the milk microbiome as they are confined to settings within industrialized populations.
Conclusion
This scoping review examines how measures of maternal weight status associate with the milk microbiome. Using a scoping review methodology, we found that current research supports the claim that maternal pre-pregnancy BMI, postpartum BMI and GWG are associated with distinct compositions of the milk microbiome. We posit that maternal gut dysbiosis and metabolic dysregulation associated with overweight or obesity, as well as other interrelated maternal factors (e.g., maternal diet, breastfeeding practices, delivery mode, and stage of lactation) are intertwined with weight status, and may explain weight-related differences in composition of the milk microbiome. However, additional research is needed to determine whether these maternal weight-related differences in milk microbiota meaningfully impact infant health, gut microbiome development, and later disease risk.
Supporting information
S1 Table. “Database and platform information”.
https://doi.org/10.1371/journal.pone.0274950.s001
(DOCX)
Acknowledgments
The authors’ responsibilities were distributed as follows: KD and VH: conceptualized the study; KD and VH: organized the publication of protocols; KN: conducted the searches and wrote Methods section; KD, VH and UMM: led the screening of abstracts and full-texts; KD and VH: extracted data; KD: wrote the manuscript; UMM: organized the submission; and all authors: read and approved the final manuscript.
References
- 1. Kopelman PG. Obesity as a medical problem. Nature [Internet]. 2000;404(6778):635–43. Available from: pmid:10766250
- 2. Heintz-Buschart A, Wilmes P. Human gut microbiome: function matters [Internet]. Vol. 26, Trends in Microbiology. 2018 [cited 2019 Nov 17]. p. 563–74. Available from: pmid:29173869
- 3. Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature. 2006;444(7122):1027–31. pmid:17183312
- 4. Catalano PM, Ehrenberg HM. The short- and long-term implications of maternal obesity on the mother and her offspring. BJOG An Int J Obstet Gynaecol. 2006;113(10):1126–33. pmid:16827826
- 5. Sridhar SB, Darbinian J, Ehrlich SF, Markman MA, Gunderson EP, Ferrara A, et al. Maternal gestational weight gain and offspring risk for childhood overweight or obesity. Am J Obstet Gynecol [Internet]. 2014;211(3):259.e1–259.e8. Available from: pmid:24735804
- 6. Collado MC, Isolauri E, Laitinen K, Salminen S. Distinct composition of gut microbiota during pregnancy in overweight and normal-weight women. Am J Clin Nutr. 2008;88(4):894–9. pmid:18842773
- 7.
Medicine I of. Weight gain during pregnancy: reexamining the guidelines. Washington, DC; 2009.
- 8. Santacruz A, Collado MC, García-Valdés L, Segura MT, Marítn-Lagos JA, Anjos T, et al. Gut microbiota composition is associated with body weight, weight gain and biochemical parameters in pregnant women. Br J Nutr. 2010;104(1):83–92. pmid:20205964
- 9. Houghteling PD, Walker WA. Why is initial bacterial colonization of the intestine important to infants’ and children’s health? Vol. 60, Journal of Pediatric Gastroenterology and Nutrition. Lippincott Williams and Wilkins; 2015. p. 294–307.
- 10. Kalliomäki M, Collado MC, Salminen S, Isolauri E. Early differences in fecal microbiota composition in children may predict overweight. Am J Clin Nutr. 2008;87(3):534–8. pmid:18326589
- 11. Stanislawski MA, Dabelea D, Wagner BD, Iszatt N, Dahl C, Sontag MK, et al. Gut Microbiota in the first 2 years of life and the association with body mass index at age 12 in a Norwegian birth cohort. MBio. 2018 Oct 23;9(5).
- 12. Bokulich NA, Chung J, Battaglia T, Henderson N, Jay M, Li H, et al. Antibiotics, birth mode, and diet shape microbiome maturation during early life. Sci Transl Med. 2016;8(343):1–14.
- 13. Gomez-Gallego C, Garcia-Mantrana I, Salminen S, Collado MC. The human milk microbiome and factors influencing its composition and activity. Seminars in Fetal and Neonatal Medicine. 2016. pmid:27286644
- 14. Pannaraj PS, Li F, Cerini C, Bender JM, Yang S, Rollie A, et al. Association between breast milk bacterial communities and establishment and development of the infant gut microbiome. JAMA Pediatr. 2017;171(7):647–54. pmid:28492938
- 15. Togo A, Dufour JC, Lagier JC, Dubourg G, Raoult D, Million M. Repertoire of human breast and milk microbiota: A systematic review. Future Microbiol. 2019 May 1;14(7):623–41. pmid:31025880
- 16. Greer FR. Origins of the human milk microbiome: A complex issue. J Nutr. 2019;149(6):887–9. pmid:31149714
- 17. Kordy K, Gaufin T, Mwangi M, Li F, Cerini C, Lee DJ, et al. Contributions to human breast milk microbiome and enteromammary transfer of Bifidobacterium breve. PLoS One. 2020;15(1):1–10. pmid:31990909
- 18. Rodríguez JM. The origin of human milk bacteria: Is there a bacterial entero-mammary pathway during late pregnancy and lactation? Am Soc Nutr Adv Nutr. 2014;5:779–84.
- 19. Groer MW, Morgan KH, Louis-Jacques A, Miller EM. A scoping review of research on the human milk microbiome. J Hum Lact. 2020;36(4):628–43. pmid:32735471
- 20. Demmelmair H, Jiménez E, Collado MC, Salminen S, McGuire MK. Maternal and perinatal factors associated with the human milk microbiome. Curr Dev Nutr. 2020;4(4):1–14. pmid:32270132
- 21. Zimmermann P, Curtis N. Breast milk microbiota: A review of the factors that influence composition. J Infect. 2020;81(1):17–47. pmid:32035939
- 22. Fitzstevens JL, Smith KC, Hagadorn JI, Caimano MJ, Matson AP, Brownell EA. Systematic review of the human milk microbiota. Nutr Clin Pract. 2017;32(3):354–64. pmid:27679525
- 23. Arksey H , O’Malley L. Scoping studies: Towards a methodological framework. Int J Soc Res Methodol Theory Pract. 2005;8(1):19–32.
- 24. Aromataris E, Munn Z. JBI Manual for Evidence Synthesis [Internet]. 2020. Available from: https://synthesismanual.jbi.global
- 25. Napierala M, Mazela J, Merritt TA, Florek E. Tobacco smoking and breastfeeding: Effect on the lactation process, breast milk composition and infant development. A critical review. Environ Res [Internet]. 2016;151:321–38. Available from: http://dx.doi.org/10.1016/j.envres.2016.08.002
- 26. McGowan J, Sampson M, Salzwedel DM, Cogo E, Foerster V, Lefebvre C. PRESS Peer Review of Electronic Search Strategies: 2015 Guideline Statement. J Clin Epidemiol [Internet]. 2016;75:40–6. Available from: pmid:27005575
- 27. Haddaway NR, Grainger MJ, Gray CT. Citationchaser: A tool for transparent and efficient forward and backward citation chasing in systematic searching. 2022;(November 2021):1–13.
- 28.
Covidence. Covidence systematic review software, Veritas Health Innovation, Melbourne, Australia.
- 29. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ [Internet]. 2021 Mar 29;372:n71. Available from: http://www.bmj.com/content/372/bmj.n71.abstract pmid:33782057
- 30. Cabrera-Rubio R, Collado MC, Laitinen K, Salminen S, Isolauri E, Mira A. The human milk microbiome changes over lactation and is shaped by maternal weight and mode of delivery. Am J Clin Nutr. 2012;1–84. pmid:22836031
- 31. Collado MC, Laitinen K, Salminen S, Isolauri E. Maternal weight and excessive weight gain during pregnancy modify the immunomodulatory potential of breast milk. Pediatr Res. 2012 Jul;72(1):77–85. pmid:22453296
- 32. Davé V, Street K, Francis S, Bradman A, Riley L, Eskenazi B, et al. Bacterial microbiome of breast milk and child saliva from low-income Mexican-American women and children. Pediatr Res. 2016;79(6):846–54. pmid:26756784
- 33. Li SW, Watanabe K, Hsu CC, Chao SH, Yang ZH, Lin YJ, et al. Bacterial composition and diversity in breast milk samples from mothers living in Taiwan and Mainland China. Front Microbiol. 2017;8(MAY):1–15. pmid:28611760
- 34. Williams JE, Carrothers JM, Lackey KA, Beatty NF, York MA, Brooker SL, et al. Human milk microbial community structure is relatively stable and related to variations in macronutrient and micronutrient intakes in healthy lactating women. J Nutr. 2017;147(9):1739–48. pmid:28724659
- 35. Asbury M, Butcher J, Unger S, Copeland J, Kiss A, Sherman P, et al. Characterizing the microbial composition of milk from mothers with infants born <1250 grams. In: Breastfeeding Medicine. 2018. p. A–59.
- 36. Li C, Gonzalez E, Solomons NW, Scott ME, Koski KG. Human breast milk microbiota is Influenced by maternal age and BMI, stage of lactation and infant feeding practices. FASEB J [Internet]. 2017 Apr 1;31(S1):965.25–965.25. Available from: https://doi.org/10.1096/fasebj.31.1_supplement.965.25
- 37. Boix-Amorós A, Puente-Sánchez F, du Toit E, Linderborg KM, Zhang Y, Yang B, et al. Mycobiome profiles in breast milk from healthy women depend on mode of delivery, geographic location, and interaction with bacteria. Appl Environ Microbiol. 2019;85(9):1–13.
- 38. Ding M, Qi C, Yang Z, Jiang S, Bi Y, Lai J, et al. Geographical location specific composition of cultured microbiota and Lactobacillus occurrence in human breast milk in China. Food Funct. 2019;10(2):554–64. pmid:30681124
- 39. Lundgren SN, Madan JC, Karagas MR, Morrison HG, Hoen AG, Christensen BC. Microbial communities in human milk relate to measures of maternal weight. Front Microbiol. 2019;10(December):1–15. pmid:31921063
- 40. Moossavi S, Sepehri S, Robertson B, Bode L, Goruk S, Field CJ, et al. Composition and variation of the human milk microbiota are influenced by maternal and early-life factors. cell host microbe [Internet]. 2019;25(2):324–335.e4. Available from: pmid:30763539
- 41. Asbury M, Butcher J, Copeland JK, Unger S, Bando N, Comelli EM, et al. Mothers of preterm infants have Individualized breast milk microbiota that changes temporally based on maternal characteristics. Cell Host Microbe [Internet]. 2020;28(5):669–682.e4. Available from: pmid:32888417
- 42. LeMay-Nedjelski L, Butcher J, Ley SH, Asbury MR, Hanley AJ, Kiss A, et al. Examining the relationship between maternal body size, gestational glucose tolerance status, mode of delivery and ethnicity on human milk microbiota at three months post-partum. BMC Microbiol. 2020;20(1):1–14.
- 43. Treven P, Mahnič A, Rupnik M, Golob M, Pirš T, Matijašić BB, et al. Evaluation of human milk microbiota by 16S rRNA gene next-generation sequencing (NGS) and cultivation/MALDI-TOF mass spectrometry identification. Front Microbiol. 2019;10(November):1–12.
- 44. Pace RM, Williams JE, Robertson B, Lackey KA, Meehan CL, Price WJ, et al. Variation in human milk composition is related to differences in milk and infant fecal microbial communities. Microorganisms. 2021;9(6):1–17. pmid:34072117
- 45. Bayaga CLT, Tanguilig KMN, Aba RPM, Pico MB, Gabriel AA. Culturable micro-organisms in human milk were found to be associated with maternal weight, diet and age during early lactation. J Appl Microbiol. 2021;131(2):925–37. pmid:33336459
- 46. Yan W, Luo B, Zhang X, Ni Y, Tian F. Association and occurrence of bifidobacterial phylotypes between breast milk and fecal microbiomes in mother–infant dyads during the first 2 years of life. Front Microbiol. 2021;12(June):1–17. pmid:34163448
- 47. Butts CA, Paturi G, Blatchford P, Bentley-Hewitt KL, Hedderley DI, Martell S, et al. Microbiota composition of breast milk from women of different ethnicity from the Manawatu—Wanganui region of New Zealand. Nutrients. 2020;12(6):1–17. pmid:32545413
- 48. Cortés-Macías E, Selma-Royo M, Martínez-Costa C, Collado MC. Breastfeeding practices influence the breast milk microbiota depending on pre-gestational maternal BMI and weight gain over pregnancy. Nutrients. 2021;13(5). pmid:33946343
- 49. Sanjulián L, Lamas A, Barreiro R, Cepeda A, Fente CA, Regal P. Bacterial diversity of breast milk in healthy Spanish women: Evolution from birth to five years postpartum. Nutrients. 2021;13(7):1–22. pmid:34371924
- 50.
Darragh A, Lönnerdal B. Milk | Human Milk. In: Fuquay JWBTE of DS (Second E, editor. San Diego: Academic Press; 2011. p. 581–90. Available from: https://www.sciencedirect.com/science/article/pii/B9780123744074003150
- 51. LeMay-Nedjelski L, Asbury MR, Butcher J, Ley SH, Hanley AJ, Kiss A, et al. Maternal diet and infant feeding practices are associated with variation in the human milk microbiota at 3 months postpartum in a cohort of women with high rates of gestational glucose Intolerance. J Nutr. 2021;151(2):320–9. pmid:32886107
- 52. LeMay-Nedjelski L, Copeland J, Wang P, Butcher J, Unger S, Stintzi A, et al. Methods and strategies to examine the human breastmilk microbiome. In: Microbiome Analysis: Methods and Protocols. Springer Science + Business Media; 2018. p. 53–86. pmid:30298248
- 53. Willis AD. Rarefaction, alpha diversity, and statistics. Front Microbiol. 2019;10(OCT).
- 54. Koliada A, Syzenko G, Moseiko V, Budovska L, Puchkov K, Perederiy V, et al. Association between body mass index and Firmicutes/Bacteroidetes ratio in an adult Ukrainian population. BMC Microbiol. 2017;17(1):4–9.
- 55. Turnbaugh PJ, Gordon JI. The core gut microbiome, energy balance and obesity. J Physiol. 2009;587(17):4153–8. pmid:19491241
- 56. Ley RE. Obesity and the human microbiome. Curr Opin Gastroenterol. 2010;26(1):5–11. pmid:19901833
- 57. Duan M, Wang Y, Zhang Q, Zou R, Guo M, Zheng H. Characteristics of gut microbiota in people with obesity. PLoS One [Internet]. 2021;16(8 August):1–15. Available from: pmid:34375351
- 58. Koren O, Goodrich JK, Cullender TC, Spor A, Laitinen K, Kling Bäckhed H, et al. Host remodeling of the gut microbiome and metabolic changes during pregnancy. Cell. 2012 Aug 3;150(3):470–80. pmid:22863002
- 59. Nuriel-Ohayon M, Neuman H, Koren O. Microbial changes during pregnancy, birth, and infancy. Front Microbiol. 2016;7(JUL):1–13.
- 60. DiGiulio DB, Callahan BJ, McMurdie PJ, Costello EK, Lyell DJ, Robaczewska A, et al. Temporal and spatial variation of the human microbiota during pregnancy. Proc Natl Acad Sci U S A. 2015;112(35):11060–5. pmid:26283357
- 61. Gohir W, Ratcliffe EM, Sloboda DM. Of the bugs that shape us: Maternal obesity, the gut microbiome, and long-term disease risk. Pediatr Res. 2015;77(1):196–204.
- 62. McGuire MK, McGuire MA. Got bacteria? The astounding, yet not-so-surprising, microbiome of human milk. Curr Opin Biotechnol [Internet]. 2017;44:63–8. Available from: pmid:27940404
- 63. Ruiz L, Delgado S, Ruas-madiedo P, Sánchez B. Bifidobacteria and their molecular communication with the immune system. 2017;8(December):1–9.
- 64. Ajslev TA, Andersen CS, Gamborg M, Sørensen TIA, Jess T. Childhood overweight after establishment of the gut microbiota: The role of delivery mode, pre-pregnancy weight and early administration of antibiotics. Int J Obes. 2011;35(4):522–9. pmid:21386800
- 65. Wrottesley S V., Pisa PT, Norris SA. The influence of maternal dietary patterns on body mass index and gestational weight gain in urban black South African women. Nutrients. 2017;9(7). pmid:28696364
- 66. Keikha M, Bahreynian M, Saleki M, Kelishadi R. Macro- and micronutrients of human milk composition: Are they related to maternal diet? A comprehensive systematic review. Breastfeed Med. 2017;12(9):517–27. pmid:28880568
- 67. Padilha M, Danneskiold-Samsøe NB, Brejnrod A, Hoffmann C, Cabral VP, Iaucci J de M, et al. The human milk microbiota is modulated by maternal diet. Microorganisms. 2019;7(11). pmid:31671720
- 68. Maher SE , O’Brien EC, Moore R L, Byrne DF, Geraghty AA, Saldova R, et al. The association between the maternal diet and the maternal and infant gut microbiome: A systematic review. Br J Nutr. 2020; pmid:32129734
- 69. Mandal S, Godfrey KM, McDonald D, Treuren W V., Bjørnholt J V., Midtvedt T, et al. Fat and vitamin intakes during pregnancy have stronger relations with a proinflammatory maternal microbiota than does carbohydrate intake. Microbiome [Internet]. 2016;4:1–12. Available from: http://dx.doi.org/10.1186/s40168-016-0200-3
- 70. Roÿtiö H, Mokkala K, Vahlberg T, Laitinen K. Dietary intake of fat and fibre according to reference values relates to higher gut microbiota richness in overweight pregnant women. Br J Nutr. 2017;118(5):343–52. pmid:28901891
- 71. Zinöcker MK, Lindseth IA. The western diet–microbiome-host interaction and its role in metabolic disease. Nutrients. 2018;10(3):1–15. pmid:29562591
- 72. Amir LH, Donath S. A systematic review of maternal obesity and breastfeeding intention, initiation and duration. BMC Pregnancy Childbirth. 2007;7. pmid:17608952
- 73. Quinn EA, Largado F, Power M, Kuzawa CW. Predictors of breast milk macronutrient composition in filipino mothers. Am J Hum Biol. 2012;24(4):533–40. pmid:22434662
- 74. Khodayar-Pardo P, Mira-Pascual L, Collado MC, Martínez-Costa C. Impact of lactation stage, gestational age and mode of delivery on breast milk microbiota. J Perinatol. 2014;34(8):599–605. pmid:24674981
- 75. Chu SY, Kim SY, Schmid CH, Dietz PM, Callaghan WM, Lau J, et al. Maternal obesity and risk of Cesarean delivery: A meta-analysis. Obes Rev. 2007;8(5):385–94. pmid:17716296
- 76. Dominguez-Bello MG, Costello EK, Contreras M, Magris M, Hidalgo G, Fierer N, et al. Delivery mode shapes the acquisition and structure of the initial microbiota across multiple body habitats in newborns. Proc Natl Acad Sci U S A. 2010;107(26):11971–5. pmid:20566857
- 77. Shin H, Pei Z, Martinez KA, Rivera-Vinas JI, Mendez K, Cavallin H, et al. The first microbial environment of infants born by C-section: the operating room microbes. Microbiome [Internet]. 2015;3:59. Available from: pmid:26620712
- 78. Ong K, Loos R. Rapid infancy weight gain and subsequent obesity: Systematic reviews and hopeful suggestions. Acta Paediatr Int J Paediatr. 2006;95(8):904–8. pmid:16882560
- 79. Lackey KA, Williams JE, Meehan CL, Zachek JA, Benda ED, Price WJ, et al. What’s normal? Microbiomes in human milk and infant feces are related to each other but vary geographically: The inspire study. Front Nutr. 2019;6(April). pmid:31058158
- 80. Quinn EA. Centering human milk composition as normal human biological variation. Am J Hum Biol. 2021;33(1):1–16. pmid:33432701
- 81. Biagi E, Aceti A, Quercia S, Beghetti I, Rampelli S, Turroni S, et al. Microbial community dynamics in mother’s milk and infant’s mouth and gut in moderately preterm infants. Front Microbiol. 2018;9(OCT):1–10. pmid:30405571