Diet is a key regulator of microbiome structure and function across the lifespan. Microbial colonization in the first year of life has been actively researched; however, studies during childhood are sparse. Herein, the impact of dietary intake and pre-and probiotic interventions on microbiome composition of healthy infants and children from birth to adolescence is discussed. The microbiome of breastfed infants has lower microbial diversity and richness, higher Proteobacteria, and lower Bacteroidetes and Firmicutes than those formula-fed. As children consume more complex diets, associations between dietary patterns and the microbiota emerge. Like adults, the microbiota of children consuming a Western-style diet is associated with greater Bacteroidaceae and Ruminococcaceae and lower Prevotellaceae. Dietary fibers and pre-or/and probiotics have been tested to modulate the gut microbiota in early life. Human milk oligosaccharides and prebiotics added to infant formula are bifidogenic and decrease pathogens. In children, prebiotics, such as inulin, increase Bifidobacterium abundance and dietary fibers reduce fecal pH and increase alpha diversity and calcium absorption. Probiotics have been administered to the mother during pregnancy and breastfeeding or directly to the infant/ child. Findings on maternal probiotic administration on bacterial taxa are inconsistent. When given directly to the infant/child, some changes in individual taxa are observed, but rarely is overall alpha or beta diversity affected. Cesarean-delivered infants appear to benefit to a greater degree than those born vaginally. Infancy and childhood represent an opportunity to beneficially manipulate the microbiome through dietary or prebiotic interventions, which has the potential to affect both short-and long-term health outcomes.
Prematurity coupled with the necessary clinical management of preterm (PT) infants introduces multiple factors that can interfere with microbial colonization. This study aimed to review the perinatal, physiological, pharmacological, dietary, and environmental factors associated with gut microbiota of PT infants. A total of 587 articles were retrieved from a search of multiple databases. Sixty studies were included in the review after removing duplicates and articles that did not meet the inclusion criteria. Review of this literature revealed that evidence converged on the effect of postnatal age, mode of delivery, use of antibiotics, and consumption of human milk in the composition of gut microbiota of PT infants. Less evidence was found for associations with race, sex, use of different fortifiers, macronutrients, and other medications. Future studies with rich metadata are needed to further explore the impact of the PT exposome on the development of the microbiota in this high-risk population.
Diet is a key modulator of fecal microbiota composition and function. However, the influence of diet on the microbiota from toddlerhood to adolescence and young adulthood is less well studied than for infancy and adulthood. We aimed to complete a qualitative systematic review of the impacts of diet on the fecal microbiota of healthy humans 1–20 y of age. English-language articles, published after 2008, indexed in the PubMed/MEDLINE, Cochrane, Web of Science, and Scopus databases were searched using keywords and Medical Subject Headings terms. Quality assessment of included studies was conducted using the Quality Criteria Checklist derived from the Nutrition Evidence Library of the Academy of Nutrition and Dietetics. A total of 973 articles were identified through database searching and 3 additional articles were included via cross-reference. Subsequent to de-duplication, 723 articles were screened by title and abstract, of which 709 were excluded based on inclusion criteria established a priori. The remaining 14 studies were independently screened by 2 reviewers for final inclusion. Included studies were published between 2010 and 2019 and included 8 comparative cross-sectional studies, 4 cross-sectional studies, 1 randomized crossover study, and 1 substudy of a randomized 2-period crossover trial. Associations of a diet rich in indigestible plant polysaccharides with Prevotella, or with an enterotype dominated by this genus, often comprised of the species Prevotella copri, were observed. In addition, associations of a high-fat and -sugar diet with Bacteroides, or with an enterotype dominated by this genus, were observed predominantly in comparative cross-sectional and cross-sectional studies spanning the ages of 1–15 y. This review identified a gap in the literature for ages 16–20 y. In addition, randomized controlled trials for dietary intervention are needed to move from association-based observations to causal relations between diet and microbiota composition and function. This systematic review was registered at www.crd.york.ac.uk/prospero as CRD42020129824.
Objectives Lutein is a carotenoid found in green leafy vegetables, avocados, and eggs, and is purported to have protective effects against age-related macular degeneration (AMD) as well as benefits for visual and cognitive health. Recent studies have indicated significant variation in serum lutein among individuals and that gastrointestinal (GI) microbial profile may potentially contribute to lutein status. However, the extent to which the GI microbiota contribute to lutein is unclear. The current study aimed to determine GI microbial predictors of serum lutein in a healthy young adult population. Methods Among adults ages 25–45 years (N = 105), venous blood was collected following a 10-hour fast. Serum lutein was determined using HPLC. Fecal DNA was extracted and the V4 region of the 16S rRNA gene was amplified. Amplicon sequence variants were assigned using the GreenGenes 13-8 database and DADA2, followed by analysis in QIIME2 and LDA Effect Size (LEfSe). Participants underwent DXA scan for whole body % fat (%Fat) and completed a 7-day food record to assess lutein consumption. Demographic information on participant's age and sex was also assessed and included in the statistical models. Results Four genera (Dialister, Ruminococcus, Gemmiger, and Phascolarctobacterium) and two species (Bacteroides eggerthii, Ruminococcus torques) were different between individuals in the highest and lowest quartiles of serum lutein. The genera Ruminococcus (Rho = −0.24, P = 0.02) and Phascolarctobacterium (Rho = −0.21, P = 0.03) and species R. torques (Rho = −0.35, P < 0.001) were inversely related to serum lutein. Linear regression modelling, adjusted for age, sex, %Fat, and dietary lutein, revealed that R. torques was the only significant predictor of serum lutein concentrations, accounting for 8.4% of the variance. Conclusions Our results reveal that individuals with lower serum lutein concentrations have a higher relative abundance of R. torques than those with higher lutein concentrations. As R. torques has been shown to be elevated in those with AMD, it is possible the relationship between this microbe and lutein is evident earlier in adulthood. However, further dietary intervention trials are warranted to clarify the relations among R. torques and serum lutein concentrations. Funding Sources This work was supported by funds provided by the Department of Kinesiology and Community Health at the University of Illinois and the USDA National Institute of Food and Agriculture, Hatch Project 1009249. Partial support was also provided by the Hass Avocado Board.
Objectives The extent to which early life factors predict weight status by age two is unclear. This study elucidated early life factors predictive of BMI-for-age z-score (MN24 BMI) in 2-year-olds in the ongoing STRONG Kids 2 longitudinal study. Methods At registration, 6 weeks, 3, 12, 18, and 24 months, parents (N = 126) completed online surveys (questions derived from CDC Infant Feeding Practices questionnaire, Short Form of the MOS Health survey, and Block Kids Food Frequency Questionnaire (Ages 2–7; Nutrition Quest) for diet MN21–24). Height and weight were collected at home visits. Child BMI-for age z-scores were based on WHO growth standards, and dietary patterns at MN24 were derived by principal component analysis (PCA). Mode of delivery (i.e., vaginal or caesarean), timing of introduction to solids, dietary patterns, child's BMI z-score and feeding methods (i.e., exclusive formula or breastfeeding, or both), and maternal weight were obtained. Multiple regression modelling determined the explanatory power of these factors on MN24 BMI. Results Modelling revealed a significant regression equation (P < .001), with an R2 of .359. MN12 BMI-for-age z-score (MN12 BMI) (β = .555, P < .001) explained 31.2% of the variance in MN24 BMI. Child feeding method at MN3 (β = –.218, P = .003) accounted for 4.7% of the variance in MN24 BMI. Conclusions Children with a greater MN12 BMI have a higher MN24 BMI, while those who undergo breastfeeding at MN3 have a lower MN24 BMI. Future studies will expand on these findings by examining if the predictive power of these early life factors on BMI persists in later life. Funding Sources Grants from the National Dairy Council to Sharon Donovan and Barbara H. Fiese (CoPI's), and the Gerber Foundation and NIH R01 DK107561 to Sharon Donovan.
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