Longitudinal body mass index trajectories at preschool age: children with rapid growth have differential composition of the gut microbiota in the first year of life

Determining the interplay of prenatal parental BMI in shaping child BMI trajectories: the CHILD Cohort Study

BACKGROUND

Obesity is a major public health concern affecting millions of people globally. Early identification of individuals susceptible to obesity is crucial for reducing the burden of obesity. Obesity is often defined based on body-mass-index (BMI), and tracking BMI trajectories from early childhood offers a valuable tool for risk stratification. Although the role of mothers in shaping these trajectories is well-recognized, the paternal influence on childhood obesity development remains a knowledge gap. We hypothesize that children of fathers with obesity have higher odds of being in the rapid BMI growth trajectory with stronger estimates when the mother is also with overweight or obesity.

METHODS

We analyzed data from the Canadian CHILD Cohort Study, a pregnancy cohort in which both parents were enrolled in early pregnancy when BMI was assessed. The child's BMI was repeatedly collected from birth to age five. We used group-based trajectory modeling to identify offspring BMI z-score (BMIz) trajectory groups (age-and-sex standardized) and weighted multinomial logistic regression analysis to determine the associations between prenatal paternal BMI and offspring growth trajectories, stratified by maternal weight categories.

RESULTS

Among 2 238 participants, the mean prenatal paternal BMI was 27.44 (SD = 4.77), and 22.83% of fathers were with obesity. The four identified offspring BMIz trajectories were: low stable (n = 220, 9.83%), normative (n = 1 356, 60.59%), high stable (n = 572, 25.56%), and rapid BMIz growth trajectory (n = 90, 4.02%). Children of normal-weight mothers and fathers with obesity had 1.86 higher odds (OR: 1.86; 95%CI: 1.22-2.84) of being classified in the rapid growth BMIz trajectory, compared to children of normal-weight fathers. The odds of being in the rapid growth BMIz trajectory were higher when both mothers and fathers were with obesity (OR: 4.35; 95%CI: 2.65-7.14).

CONCLUSIONS

Children of fathers with obesity had higher odds of being in the rapid BMI growth trajectory, particularly when also the mother was with overweight or obesity. These results support the need for preconception advice and interventions for couples to optimize their offspring's health.

Association of body index with fecal microbiome in children cohorts with ethnic-geographic factor interaction: accurately using a Bayesian zero-inflated negative binomial regression model

The exponential growth of high-throughput sequencing (HTS) data on the microbial communities presents researchers with an unparalleled opportunity to delve deeper into the association of microorganisms with host phenotype. However, this growth also poses a challenge, as microbial data are complex, sparse, discrete, and prone to zero inflation. Herein, by utilizing 10 distinct counting models for analyzing simulated data, we proposed an innovative Bayesian zero-inflated negative binomial (ZINB) regression model that is capable of identifying differentially abundant taxa associated with distinctive host phenotypes and quantifying the effects of covariates on these taxa. Our proposed model exhibits excellent accuracy compared with conventional Hurdle and INLA models, especially in scenarios characterized by inflation and overdispersion. Moreover, we confirm that dispersion parameters significantly affect the accuracy of model results, with defects gradually alleviating as the number of analyzed samples increases. Subsequently applying our model to amplicon data in real multi-ethnic children cohort, we found that only a subset of taxa were identified as having zero inflation in real data, suggesting that the prevailing understanding and processing of microbial count data in most previous microbiome studies were overly dogmatic. In practice, our pipeline of integrating bacterial differential abundance in microbiome data and relevant covariates is effective and feasible. Taken together, our method is expected to be extended to the microbiota studies of various multi-cohort populations.

IMPORTANCE

The microbiome is closely associated with physical indicators of the body, such as height, weight, age and BMI, which can be used as measures of human health. Accurately identifying which taxa in the microbiome are closely related to indicators of physical development is valuable as microbial markers of regional child growth trajectory. Zero-inflated negative binomial (ZINB) model, a type of Bayesian generalized linear model, can be effectively modeled in complex biological systems. We present an innovative ZINB regression model that is capable of identifying differentially abundant taxa associated with distinctive host phenotypes and quantifying the effects of covariates on these taxa, and demonstrate that its accuracy is superior to traditional Hurdle and INLA models. Our pipeline of integrating bacterial differential abundance in microbiome data and relevant covariates is effective and feasible.

Is Family History for the Management of Cardiovascular Health in Youth Still Relevant in Clinical Practice?

PURPOSE OF REVIEW

Family history of premature cardiovascular disease is a strong predictor of individual cardiovascular risk. However, family history is not always available and not always reliable. Roughly 80% of health outcomes are influenced not by genetic risk but by societal factors, including adverse health behaviors and environment. Furthermore, in the present age of genetic testing, laboratory evaluations, and imaging, a key question remains: What is the contemporary relevance of family history screening in the management of cardiovascular disease in youth?

RECENT FINDINGS

Knowledge of an individual's family history can help clinicians identify not only inherited risk but also familial clustering of unhealthy behaviors and environmental adversity contributing to enhanced cardiovascular disease risk in youth. For those at greatest risk, prevention strategies can be applied sooner and more conservatively. Integrating family history into clinical practice is crucial for cardiovascular risk assessment and for optimizing outcomes, but, in some cases, is more reflective of social factors.

Reduce, reinforce, and replenish: safeguarding the early-life microbiota to reduce intergenerational health disparities

Socioeconomic (SE) disparity and health inequity are closely intertwined and associated with cross-generational increases in the rates of multiple chronic non-communicable diseases (NCDs) in North America and beyond. Coinciding with this social trend is an observed loss of biodiversity within the community of colonizing microbes that live in and on our bodies. Researchers have rightfully pointed to the microbiota as a key modifiable factor with the potential to ease existing health inequities. Although a number of studies have connected the adult microbiome to socioeconomic determinants and health outcomes, few studies have investigated the role of the infant microbiome in perpetuating these outcomes across generations. It is an essential and important question as the infant microbiota is highly sensitive to external forces, and observed shifts during this critical window often portend long-term outcomes of health and disease. While this is often studied in the context of direct modulators, such as delivery mode, family size, antibiotic exposure, and breastfeeding, many of these factors are tied to underlying socioeconomic and/or cross-generational factors. Exploring cross-generational socioeconomic and health inequities through the lens of the infant microbiome may provide valuable avenues to break these intergenerational cycles. In this review, we will focus on the impact of social inequality in infant microbiome development and discuss the benefits of prioritizing and restoring early-life microbiota maturation for reducing intergenerational health disparities.

Associations between maternal microbiome, metabolome and incidence of low-birth weight in Guatemalan participants from the Women First Trial

Background

Low birth weight (LBW; <2,500 g) affects approximately 15 to 20 percent of global births annually and is associated with suboptimal child development. Recent studies suggest a link between the maternal gut microbiome and poor obstetric and perinatal outcomes. The goal of this study was to examine relationships between maternal microbial taxa, fecal metabolites, and maternal anthropometry on incidence of LBW in resource-limited settings.

Methods

This was a secondary analysis of the Women First trial conducted in a semi-rural region of Guatemala. Maternal weight was measured at 12 and 34 weeks (wk) of gestation. Infant anthropometry measures were collected within 48 h of delivery. Maternal fecal samples at 12 and 34 weeks were used for microbiome (16S rRNA gene amplicon sequencing) and metabolomics analysis (34 wk). Linear mixed models using the MaAslin2 package were utilized to assess changes in microbiome associated with LBW. Predictive models using gradient boosted machines (XGBoost) were developed using the H2o.ai engine.

Results

No differences in β-diversity were observed at either time point between mothers with LBW infants relative to normal weight (NW) infants. Simpson diversity at 12 and 34 weeks was lower in mothers with LBW infants. Notable differences in genus-level abundance between LBW and NW mothers (p < 0.05) were observed at 12 weeks with increasing abundances of Barnesiella, Faecalibacterium, Sutterella, and Bacterioides. At 34 weeks, there were lower abundances of Magasphaera, Phascolarctobacterium, and Turicibacter and higher abundances of Bacteriodes, and Fusobacterium in mothers with LBW infants. Fecal metabolites related to bile acids, tryptophan metabolism and fatty acid related metabolites changed in mothers with LBW infants. Classification models to predict LBW based on maternal anthropometry and predicted microbial functions showed moderate performance.

Conclusion

Collectively, the findings indicate that alterations in the maternal microbiome and metabolome were associated with LBW. Future research should target functional and predictive roles of the maternal gut microbiome in infant birth outcomes including birthweight.

Research trends between childhood obesity and gut microbiota: a bibliometric analysis (2002-2023)

Background

In recent years, the prevalence of childhood obesity has escalated alarmingly, posing significant threats to the physical and mental well-being of children, with an elevated likelihood of persisting into adulthood. Notably, recent investigations have uncovered a profound association between intestinal microbiota, a crucial component of the internal milieu, and childhood obesity. Disturbances in intestinal microbiota and their by-products are now understood to be profoundly intertwined with the evolutionary pathway of childhood obesity. Bibliometric analysis offers a deep understanding of the current research landscape, so we apply it to a review of the emerging trends and patterns between childhood obesity and gut microbiota.

Materials and methods

We conducted a rigorous and extensive search of the Web of Science (WoS) Core Collection database, spanning the years from 1900 to 2023, to analyze scholarly articles pertaining to childhood obesity and gut microbiota. Utilizing VOSviewer, CiteSpace, the R package "bibliometrix," and the online bibliometric analysis platform (https://bibliometric.com/), we delved into the intricate details of research hotspots, academic collaborations, and emerging trends within this domain.

Results

The exhaustive search encompassed the globe, uncovering a cumulative total of 1,384 pertinent studies originating from 429 nations. The results were compelling, revealing a profound influence exerted by the United States and China in this specific field of research. Furthermore, it was observed that the volume of scholarly works pertaining to childhood obesity and gut microbiota is steadily growing year on year. The current hot topics in this field include "abuse," "maltreatment," "adverse childhood experiences," "students," and "food addiction".

Conclusion

This comprehensive review offers a meticulous exploration of the evolving trends and emerging research agendas pertaining to childhood obesity and gut microbiota over the past two decades. It strives to equip researchers with a thorough understanding of the key nations, institutions, journals, and potential collaborators in these specialized fields. Additionally, it sheds light on the current frontiers of research and strategic avenues for further exploration, thus serving as an invaluable resource for scholars delving deeper into the intricacies of childhood obesity and the gut microbiome.

Maternal smoking during pregnancy increases the risk of gut microbiome-associated childhood overweight and obesity

Childhood obesity is linked to maternal smoking during pregnancy. Gut microbiota may partially mediate this association and could be potential targets for intervention; however, its role is understudied. We included 1,592 infants from the Canadian Healthy Infants Longitudinal Development Cohort. Data on environmental exposure and lifestyle factors were collected prenatally and throughout the first three years. Weight outcomes were measured at one and three years of age. Stool samples collected at 3 and 12 months were analyzed by sequencing the V4 region of 16S rRNA to profile microbial compositions and magnetic resonance spectroscopy to quantify the metabolites. We showed that quitting smoking during pregnancy did not lower the risk of offspring being overweight. However, exclusive breastfeeding until the third month of age may alleviate these risks. We also reported that maternal smoking during pregnancy significantly increased Firmicutes abundance and diversity. We further revealed that Firmicutes diversity mediates the elevated risk of childhood overweight and obesity linked to maternal prenatal smoking. This effect possibly occurs through excessive microbial butyrate production. These findings add to the evidence that women should quit smoking before their pregnancies to prevent microbiome-mediated childhood overweight and obesity risk, and indicate the potential obesogenic role of excessive butyrate production in early life.

Breastfeeding enrichment of B. longum subsp. infantis mitigates the effect of antibiotics on the microbiota and childhood asthma risk

BACKGROUND

Early antibiotic exposure is linked to persistent disruption of the infant gut microbiome and subsequent elevated pediatric asthma risk. Breastfeeding acts as a primary modulator of the gut microbiome during early life, but its effect on asthma development has remained unclear.

METHODS

We harnessed the CHILD cohort to interrogate the influence of breastfeeding on antibiotic-associated asthma risk in a subset of children (n = 2,521). We then profiled the infant microbiomes in a subset of these children (n = 1,338) using shotgun metagenomic sequencing and compared human milk oligosaccharide and fatty acid composition from paired maternal human milk samples for 561 of these infants.

FINDINGS

Children who took antibiotics without breastfeeding had 3-fold higher asthma odds, whereas there was no such association in children who received antibiotics while breastfeeding. This benefit was associated with widespread "re-balancing" of taxonomic and functional components of the infant microbiome. Functional changes associated with asthma protection were linked to enriched Bifidobacterium longum subsp. infantis colonization. Network analysis identified a selection of fucosylated human milk oligosaccharides in paired maternal samples that were positively associated with B. infantis and these broader functional changes.

CONCLUSIONS

Our data suggest that breastfeeding and antibiotics have opposing effects on the infant microbiome and that breastfeeding enrichment of B. infantis is associated with reduced antibiotic-associated asthma risk.

FUNDING

This work was supported in part by the Canadian Institutes of Health Research; the Allergy, Genes and Environment Network of Centres of Excellence; Genome Canada; and Genome British Columbia.

Different gut microbiota in U.S. formula-fed infants consuming a meat vs. dairy-based complementary foods: A randomized controlled trial

Objective

This project aimed to evaluate the impact of meat- vs. dairy-based complementary foods on gut microbiota and whether it relates to growth.

Design

Full-term, formula-fed infants were recruited from the metro Denver area (Colorado, US) and randomized to a meat- or dairy-based complementary diet from 5 to 12 months of age. Infant's length and weight were measured, and stool samples were collected at 5, 10, and 12 months for 16S rRNA gene sequencing and short-chain fatty acids (SCFAs) quantification.

Results

Sixty-four infants completed the dietary intervention (n = 32/group). Weight-for-age Z (WAZ) scores increased in both groups and length-for-age Z scores (LAZ) increased in the meat group only, which led to a significant group-by-time interaction (P = 0.02) of weight-for-length Z (WLZ) score. Microbiota composition (Beta-diversity) differed between groups at 12 months (weighted PERMANOVA P = 0.01) and had a group-by-time interaction of P = 0.09. Microbial community richness (Chao1) increased in the meat group only. Genus Akkermansia had a significant group-by-time interaction and increased in the dairy group and decreased in the meat group. A significant fold change of butyric acid from 5 to 12 months was found in the meat group (+1.75, P = 0.011) but not in the dairy group. Regression analysis showed that Chao1 had a negative association with WLZ and WAZ. Several genera also had significant associations with all growth Z scores.

Conclusion

Complementary feeding not only impacts infant growth but also affects gut microbiota maturation. Complementary food choices can affect both the gut microbiota diversity and structures and these changes in gut microbiota are associated with infant growth.

Human Milk Microbiome and Microbiome-Related Products: Potential Modulators of Infant Growth

Infant growth trajectory may influence later-life obesity. Human milk provides a wide range of nutritional and bioactive components that are vital for infant growth. Compared to formula-fed infants, breastfed infants are less likely to develop later-onset obesity, highlighting the potential role of bioactive components present in human milk. Components of particular interest are the human milk microbiota, human milk oligosaccharides (HMOs), short-chain fatty acids (SCFAs), and antimicrobial proteins, each of which influence the infant gut microbiome, which in turn has been associated with infant body composition. SCFAs and antimicrobial proteins from human milk may also systemically influence infant metabolism. Although inconsistent, multiple studies have reported associations between HMOs and infant growth, while studies on other bioactive components in relation to infant growth are sparse. Moreover, these microbiome-related components may interact with each other within the mammary gland. Here, we review the evidence around the impact of human milk microbes, HMOs, SCFAs, and antimicrobial proteins on infant growth. Breastfeeding is a unique window of opportunity to promote optimal infant growth, with aberrant growth trajectories potentially creating short- and long-term public health burdens. Therefore, it is important to understand how bioactive components of human milk influence infant growth.

Development of the gut microbiota in healthy twins during the first 2 years of life and associations with body mass index z-score: Results from the Wuhan twin birth cohort study

The gut microbiota undergoes rapid and vital changes to microbial community structure and the microbial-immune crosstalk during the first 3 years of life, which is thought to be involved in the pathobiology of later-life disease. Compared to single-born children, little is known about the gut microbiota of twins in early childhood. Based on the Wuhan Twin Birth Cohort study, 344 stool samples from 204 twin families were analyzed to investigate the difference in gut microbiota composition at 6, 12, and 24 months of age. Furthermore, this study evaluated the association between gut microbiota development curves and body mass index z-score (BMI_Z) curves at 6, 12, and 24 months of age. The predominant microbiota phyla identified in twins were Proteobacteria, Actinobacteriota, Firmicutes, Bacteroidota, and Verrucomicrobiota. The richness and diversity of gut microbiota increased from 6 to 24 months old (alpha diversity with p < 0.05). Beta diversity revealed 61 gut microbiota genera that were significantly different in relative abundance among the three age groups. Among the 61 gut microbiota genera, 30 distinct trajectory curves (DTCs) were generated by group-based trajectory models after log2 transformation of their relative abundance. Subsequently, Spearman correlation analysis revealed that only five gut microbiota DTC were correlated with the BMI_Z DTC. Therefore, we further examined the association between the five gut microbiota genera DTC and BMI_Z DTC using generalized estimation equation models. The results revealed a significant association between the DTC groups of Parabacteroides and that of BMI_Z (coefficient = 0.75, p = 0.04). The results of this study validated the hypothesis that the richness and diversity of gut microbiota developed with age in twins. Moreover, participants with a higher DTC of log2-transformed Parabacteroides had a higher BMI_Z DTC during the first 2 years of life. Further studies are needed to confirm the association between Parabacteroides and BMI_Z in other populations.