Novel developmental analyses identify longitudinal patterns of early gut microbiota that affect infant growth

Abstract

It is acknowledged that some obesity trajectories are set early in life, and that rapid weight gain in infancy is a risk factor for later development of obesity. Identifying modifiable factors associated with early rapid weight gain is a prerequisite for curtailing the growing worldwide obesity epidemic. Recently, much attention has been given to findings indicating that gut microbiota may play a role in obesity development. We aim at identifying how the development of early gut microbiota is associated with expected infant growth. We developed a novel procedure that allows for the identification of longitudinal gut microbiota patterns (corresponding to the gut ecosystem developing), which are associated with an outcome of interest, while appropriately controlling for the false discovery rate. Our method identified developmental pathways of Staphylococcus species and Escherichia coli that were associated with expected growth, and traditional methods indicated that the detection of Bacteroides species at day 30 was associated with growth. Our method should have wide future applicability for studying gut microbiota, and is particularly important for translational considerations, as it is critical to understand the timing of microbiome transitions prior to attempting to manipulate gut microbiota in early life.

Figure 1. Theoretical description of the relationship between weight at six months and change in Z-score, as defined by the WHO growth curves.

The relationship is displayed for multiple birthweight percentiles. A change in Z-score of 0 corresponds to theoretically perfect growth at six months. If a male child was born at the 75th percentile, then their expected weight at six months would be 8.5 kg (y-axis), corresponding to 0 change in Z-score (x-axis) on the right panel. If the child instead weighed 9.0 kg at six months (y-axis), then that would correspond to a change in Z-score (x-axis).

Figure 2. All possible exposure patterns in the data.

“ ” and “ ” represent detection and non-detection respectively. For example, pattern 8 indicates detection at day 4, followed by non-detection at days 10, 30, and 120.

Figure 3. Results from the time-specific analyses for males.

Coloured areas indicate significant results at 20% false discovery rate, and are labelled with their effect estimates, while white areas indicate non-significant results. Significant results at 5% false discovery rate are indicated by . Only the results for males are displayed, as no significant results were found for females.

Figure 4. Results from the pattern analysis.

The exposure pattern is represented by four characters, constructed from “”, “”, and “X”, which represent detection, non-detection, and irrelevance, respectively, for the four time points of the analysis (days 4, 10, 30, and 120). The black points and lines represent estimated means and 95% confidence intervals for patterns that were found to be significantly close to zero at an false discovery rate of 5%. The crude contrasts (i.e. if “XX” was significant, the crude contrast would be “XX”) that were significantly different to zero at have their estimated means and 95% confidence intervals displayed in red. For the testing of the difference of the means of the two patterns, significant results (at ) is indicated by , otherwise significance is . Vertical lines are displayed at and , representing the boundaries of expected growth.