Sexual dimorphism of gut microbiota at different pubertal status

Abstract

Background: Accumulating evidence infer that gut microbiome-host relations are key mediators or modulators driving the observed sexual dimorphism in some disease onset and progression. To date, the sex-differences of gut microbiota at different pubertal status have not been reported.

Objective: To determine the characteristics of gut microbiota of both genders at different pubertal status.

Methods: Gut microbiota was analyzed in 89 Chinese participants aged 5-15 years. Participants were divided into pre-puberty and puberty groups for both male and female. The composition of gut microbiota was investigated by 16S rRNA-based metagenomics. Ecological representations of microbial communities were computed. The prediction of metagenomic functional content from 16S rRNA gene surveys was conducted.

Results: There were 49 males (9.76 ± 2.15 years) and 40 females (9.74 ± 1.63 years); 21 males and 26 females were at puberty. At genus level, Alistipes, Megamonas, Oscillospira and Parabacteroides were more prevalent in girls than in boys (p < 0.05). There were no significantly differences of alpha-diversity between genders, which was independent of pubertal status. The beta-diversity was significantly different in pubertal subjects between genders. Using statistical analyses, we assigned genera Dorea, Megamonas, Bilophila, Parabacteroides and Phascolarctobacterium as microbial markers for pubertal subjects. The predicted metabolic profiles differ in both pubertal and pre-pubertal groups between genders.

Conclusion: This cross-sectional study revealed that sex differences in the gut microbiota composition and predicted metabolic profiles exist before puberty, which become more significant at puberty. The identification of novel puberty bacterial markers may disclose a potential effects of gender-related microbiota profiles on puberty onset.

Keywords: Children; Gender; Gut microbiota; Puberty.

Fig. 1

Bar chart representing Mann–Whitney U-test results on operational taxonomic units (OTUs) grouped in phyla (a, b) and in genus (c, d) of the male and female groups. Each column in the plot represents a group, and each color in the column represents: a, c the percentage of relative abundance for each OTU; b, d the values of relative abundance for each OTU

Fig. 2

Principal coordinates analysis (PCoA) plot of male and female subjects (a), and of pubertal male, and pubertal female subjects (b). The plots show the first two principal coordinates (axes) for PCoA using Bray–Curtis Distance method

Fig. 3

Differential biomarkers associated with genders in general population (a, b), pubertal subjects (c, d) and pre-pubertal subjects (e, f). A linear discriminant effect size (LeFse) analysis have been performed (α value = 0.05, logarithmic LDA score threshold = 2.0)

Fig. 4

Canonical discriminant plot. Scatter plot of canonical discriminant analysis (DA) based on univariate ANOVA and Fisher’s coefficient applied to all OTUs of samples belonging to pubertal males, pubertal females, pre-pubertal males, and pre-pubertal females

Fig. 5

Receiver operating characteristic (ROC) curve plots. The areas under the ROC curves (AUROC) represent the specificity and sensitivity of the five OTUs (AUROC > 0.7) able to discriminate the gender in pubertal subjects

Fig. 6

KEGGs biomarkers associated with male (1) and female (2) conditions in general population (a), pubertal subjects (b) and pre-pubertal subjects (c)

Fig. 6

KEGGs biomarkers associated with male (1) and female (2) conditions in general population (a), pubertal subjects (b) and pre-pubertal subjects (c)

Fig. 6

KEGGs biomarkers associated with male (1) and female (2) conditions in general population (a), pubertal subjects (b) and pre-pubertal subjects (c)