Undernourished children exhibit impaired gut microbiota development. Transplanting microbiota from 6- and 18-month old healthy or undernourished Malawian donors into young germ-free mice fed a Malawian diet revealed that immature microbiota from undernourished infants/children transmit impaired growth phenotypes. The representation of several age-discriminatory taxa in recipient animals correlated with lean body mass gain, liver, muscle, and brain metabolism, plus bone morphology. Co-housing mice shortly after receiving microbiota from healthy (H) or severely stunted/underweight (Un) infants demonstrated that invasion of age-/growth-discriminatory taxa from H to Un cagemates’ microbiota ameliorates growth faltering. Adding two invasive species, Ruminococcus gnavus and Clostridium symbiosum, to the Un microbiota also ameliorated growth and metabolic abnormalities. These results provide evidence that microbiota immaturity is causally related to undernutrition, and reveal potential therapeutic targets and agents.

The bacterial community found in the vagina is an important determinant of a woman's health and disease status. A healthy vaginal microbiota is associated with low species richness and a high proportion of one of a number of different Lactobacillus spp. When disrupted, the resulting abnormal vaginal microbiota is associated with a number of disease states and poor pregnancy outcomes. Studies up until now have concentrated on relatively small numbers of American and European populations that may not capture the full complexity of the community or adequately predict what constitutes a healthy microbiota in all populations. In this study, we sampled and characterized the vaginal microbiota found on vaginal swabs taken postpartum from a cohort of 1,107 women in rural Malawi. We found a population dominated by Gardnerella vaginalis and devoid of the most common vaginal Lactobacillus species, even if the vagina was sampled over a year postpartum. This Lactobacillus-deficient anaerobic community, commonly labeled community state type (CST) 4, could be subdivided into four further communities. A Lactobacillus iners-dominated vaginal microbiota became more common the longer after delivery the vagina was sampled, but G. vaginalis remained the dominant organism. These results outline the difficulty in all-encompassing definitions of what a healthy or abnormal postpartum vaginal microbiota is. Previous identification of community state types and associations among bacterial species, bacterial vaginosis, and adverse birth outcomes may not represent the complex heterogeneity of the microbiota present. (This study has been registered at ClinicalTrials.gov as NCT01239693.)IMPORTANCE A bacterial community in the vaginal tract is dominated by a small number of Lactobacillus species, and when not present there is an increased incidence of inflammatory conditions and adverse birth outcomes. A switch to a vaginal bacterial community lacking in Lactobacillus species is common after pregnancy. In this study, we characterized the postpartum vaginal bacterial community of a large group of women from a resource-poor, undersampled population in rural Malawi. The majority of women were found to have a Lactobacillus-deficient community, and even when sampled a year after delivery the majority of women still did not have Lactobacillus present in their vaginal microbiota. The effect of becoming pregnant again for those who do not revert to a Lactobacillus-dominant community is unknown, and this could suggest that not all Lactobacillus-deficient community structures are adverse. A better understanding of this complex community state type is needed.

Diarrheal disease, still a major cause of childhood illness, is caused by numerous, diverse infectious microorganisms, which are differentially sensitive to environmental conditions. Enteropathogen‐specific impacts of climate remain underexplored. Results from 15 studies that diagnosed enteropathogens in 64,788 stool samples from 20,760 children in 19 countries were combined. Infection status for 10 common enteropathogens—adenovirus, astrovirus, norovirus, rotavirus, sapovirus, Campylobacter , ETEC, Shigella , Cryptosporidium and Giardia —was matched by date with hydrometeorological variables from a global Earth observation dataset—precipitation and runoff volume, humidity, soil moisture, solar radiation, air pressure, temperature, and wind speed. Models were fitted for each pathogen, accounting for lags, nonlinearity, confounders, and threshold effects. Different variables showed complex, non‐linear associations with infection risk varying in magnitude and direction depending on pathogen species. Rotavirus infection decreased markedly following increasing 7‐day average temperatures—a relative risk of 0.76 (95% confidence interval: 0.69–0.85) above 28°C—while ETEC risk increased by almost half, 1.43 (1.36–1.50), in the 20–35°C range. Risk for all pathogens was highest following soil moistures in the upper range. Humidity was associated with increases in bacterial infections and decreases in most viral infections. Several virus species' risk increased following lower‐than‐average rainfall, while rotavirus and ETEC increased with heavier runoff. Temperature, soil moisture, and humidity are particularly influential parameters across all enteropathogens, likely impacting pathogen survival outside the host. Precipitation and runoff have divergent associations with different enteric viruses. These effects may engender shifts in the relative burden of diarrhea‐causing agents as the global climate changes.

The relative contribution of genetic risk factors to the progression of subclinical atherosclerosis is poorly understood. It is likely that multiple variants are implicated in the development of atherosclerosis, but the subtle genotypic and phenotypic differences are beyond the reach of the conventional case-control designs and the statistical significance testing procedures being used in most association studies. Our objective here was to investigate whether an alternative approach—in which common disorders are treated as quantitative phenotypes that are continuously distributed over a population—can reveal predictive insights into the early atherosclerosis, as assessed using ultrasound imaging-based quantitative measurement of carotid artery intima-media thickness (IMT). Using our population-based follow-up study of atherosclerosis precursors as a basis for sampling subjects with gradually increasing IMT levels, we searched for such subsets of genetic variants and their interactions that are the most predictive of the various risk classes, rather than using exclusively those variants meeting a stringent level of statistical significance. The area under the receiver operating characteristic curve (AUC) was used to evaluate the predictive value of the variants, and cross-validation was used to assess how well the predictive models will generalize to other subsets of subjects. By means of our predictive modeling framework with machine learning-based SNP selection, we could improve the prediction of the extreme classes of atherosclerosis risk and progression over a 6-year period (average AUC 0.844 and 0.761), compared to that of using conventional cardiovascular risk factors alone (average AUC 0.741 and 0.629), or when combined with the statistically significant variants (average AUC 0.762 and 0.651). The predictive accuracy remained relatively high in an independent validation set of subjects (average decrease of 0.043). These results demonstrate that the modeling framework can utilize the “gray zone” of genetic variation in the classification of subjects with different degrees of risk of developing atherosclerosis.

We tested the hypotheses that a more mature or diverse gut microbiota will be positively associated with infant growth and inversely associated with inflammation. We characterized gut microbiota from the stool samples of Malawian infants at 6 mo (n = 527), 12 mo (n = 632) and 18 mo (n = 629) of age. Microbiota diversity and maturity measurements were based on Shannon diversity index and microbiota for age Z-score (MAZ), respectively. Growth was calculated as change in Z-scores for weight-for-age (WAZ), length-for-age (LAZ) and head circumference-for-age (HCZ) from 6 to 12 mo and 12 to 18 mo. Biomarkers of inflammation (alpha-1-acid glycoprotein (AGP) and C-reactive protein (CRP)) were measured at 6 and 18 mo. Multivariable models were used to assess the association of each independent variable with each outcome. Microbiota diversity and maturity were related to growth in weight from 6 to 12 mo, but not to growth in length or head circumference or to growth from 12 to 18 mo. Microbiota diversity and maturity may also be linked to inflammation, but findings were inconsistent.