Gut microbiota composition alteration analysis and functional categorization in children with growth hormone deficiency

Objective To study changes in the composition and functions of the gut microbiota (GM) in children with growth hormone deficiency (GHD) using high-throughput sequencing. Methods Thirty-three children with GHD diagnosed in Longgang District Maternity and Child Health Hospital were included in the disease group and 24 healthy children of the same age comprised the control group. Total DNA was extracted and amplified from stool samples obtained from all subjects. High-throughput sequencing was used to analyze the GM composition and functions. Results The GM from the two groups of children showed significant differences in α-diversity (P < 0.05). In comparison with the control group, the abundance of the phylum Bacteroidetes was significantly higher (45.96% vs. 65.71%) while the Firmicutes count was significantly lower (47.09% vs. 25.20%). At the genus level, the abundance of Prevotella in the disease group was significantly higher (3.16% vs. 20.67%) and that of Lachnospiracea incertae sedis, Clostridium XlVa, and Megamonas was lower (6.576% vs. 1.75%; 4.51% vs. 0.80%; 5.08% vs. 2.02%, respectively). GM functions, including those involved in membrane_transport, energy_metabolism, poorly_characterized, metabolism_of_cofactors_and_vitamins, glycan_biosynthesis_and_metabolism, transcription, folding,_sorting,_and_degradation, were significantly altered in the disease group. The abundance of various GM components was correlated with endocrine hormone levels. Conclusion Significant alterations in the GM are seen in children with growth hormone deficiency, which may affect both energy metabolism and the levels of endocrine hormones, potentially leading to growth restriction.


Introduction
Short stature is defined as a height of less than two standard deviations or less than the third percentile among children of the same sex, age, or race. Growth hormone deficiency (GHD) is a growth disorder caused by reduced or absent production of growth hormone (GH). It is one of the most common causes of short stature in children, accounting for 38.6% of all causes (1). The worldwide incidence of GHD in children varies between 1/4,000 and 1/10,000 and most children show idiopathic GHD (2).
The stability of the gut microbiota (GM) is an important factor influencing the growth and development of children (3). Intestinal microorganisms and metabolites such as short-chain fatty acids (SCFAs) can regulate the production of hormones related to bone health, including sex steroids, vitamin D, and serotonin (4,5). In addition, they mediate signal transduction via the intestinal-brain axis and affect the secretion of GH-releasing peptide, somatostatin, and leptin, all of which regulate the GH/ insulin-like growth factor-1 (IGF-1) axis and modulate processes such as GH secretion, appetite regulation, and bone growth (1,(6)(7)(8)(9)(10). Growth hormone can not only directly promote the growth of all organs but also stimulate the production of IGF-1. The latter is an effective growth factor that plays a synergistic role with growth hormone to maintain overall growth and metabolism (11,12). Conversely, GH or IGF-1 can also affect the composition and functions of the GM in different ways (1). Li et al. (13) reported significant changes in the GM of children with idiopathic short stature where intestinal Clostridium and Eubacterium were significantly and positively correlated with their height standard deviation score (SDS) and IGF-1 SDS. The authors believed that the decrease in IGF-1 synthesis by Clostridium and Eubacterium through SCFAs might be one of the underlying causes.
The hypothalamus-pituitary-IGF-1 axis is the main hormonal regulator of growth and development, of which GH and IGF-1 are key components (14). GHD children have reduced levels of GH and IGF-1. Imbalances in the GM can lead to endocrine hormone disorders. We speculate that children with GHD may also have GM imbalances. In this study, the intestinal composition and function of GHD children and healthy children of the same age were compared, and correlations between their GM and several hormones were analyzed to explore the characteristics of the GM of GHD children and the possible mechanism of action.

Sample screening
We selected 33 children with GHD diagnosed at Longgang District Maternity and Child Health Hospital as the disease group, and 24 healthy children of the same age as the control group. The ages of children in the two groups ranged between 5 and 14 years, with no statistical difference seen in the comparative analysis (P > 0.05) ( Table 1). All the children with GHD were diagnosed at the Department of Growth and Development, Shenzhen Longgang District Maternity and Child Health Hospital. The disease group met the diagnostic criteria for GHD in Chinese children (15): ① Below the third percentile of the height of normal healthy children of the same age and sex (−1.88 standard deviations [−1.88 SD] or minus 2 standard deviations [−2 SD]); ② Annual growth rate <5 cm/year; ③ Symmetrical dwarfism and childish face; ④ Normal intelligence development; ⑤ Bone age lagging behind actual age; ⑥ Peak values of two GH drug provocation tests of <10 µg/L; ⑦ Lower than normal level of serum IGF-1. The exclusion criteria for children in the two groups included: ① Severe liver or gastrointestinal disorders; ② Severe infection; ③ Treatment with antibiotics or probiotic preparations within one month before the test. All children provided informed consent from their guardians before enrollment.

Sample handling and species annotation
2.2.1. Collection of fecal samples for DNA extraction and sequencing from two groups of children Approximately 5 g of the middle section of the feces was collected and immediately frozen and stored at -80°C. The samples were transported on dry ice to Shenzhen Micro Health Gene Technology Co., Ltd. for high-throughput sequencing. MoBio's PowerSoil ® DNA Isolation Kit was used to extract bacterial DNA from fecal samples. Amplification of the V3 -V4 region of the 16S rRNA gene in DNA was performed by polymerase chain reaction (PCR). Amplified samples were sequenced using the Illumina MiSeq high-throughput sequencing platform.

Sequencing data analysis
Low-quality reads were filtered from the sequencing data using self-programming bioinformatics tools, and the data were spliced using FLASH software (v12.11, http://ccb.jhu.edu/software/FLASH/ index.shtml). The splicing sequences were aggregated into OTUs (sortable elements) with USEARCH, which were compared with the bacterial library (Greengene V201305) to obtain the GM compositions of all samples. The bacterial abundance in the samples of both groups was analyzed only at the phylum and genus levels.

Statistical methods
The ade4 package in R (v3.3.3) software was used to perform principal component analysis (PCA) based on the composition TABLE 1 Comparison of clinical information between children in the disease and control groups ( x + s).

Group
Age ( and relative abundance of bacteria in all samples at the genus level. The overall distribution of the microbiota compositions in the two groups was plotted. Bacteria were classified to the phylum and genus levels, and different species between the two groups were investigated by the Wilcoxon method where P < 0.05 indicated a significant difference. The 16S rDNA sequencing data were used to evaluate differences in bacterial functions between the two groups of children based on the functional analysis performed by the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. SPSS 22.0 software was used for general data analysis. The age, weight, height, and IGF-1 values were compared by χ 2 tests or two-group independent sample t-tests.

Comparison of differences in the composition of the GM
The GM of two groups of children showed significant differences in α-diversity (P = 0.033) ( Figure 1). We used PCA to reduce the dimensionality of the GM data of the two groups, finding that there were marked differences in the GM between the two groups. The genera that contributed most to this difference included Prevotella (P < 0.001), Megamonas (P = 0.01), Bacteroides (P = 0.765), Bifidobacterium (P = 0.011), and Faecalibacterium (P = 0.094) (Figure 2).

Comparison of the dominant bacterial phyla between the two groups of children
The top five dominant bacterial phyla differed between the groups with a significant increase in the abundance of Bacteroides in the disease group (P = 0.000) together with a significant reduction in the abundance of Firmicutes (P = 0.000). In addition, there was also a significant difference between the two groups in the abundance of Fusobacteria and Actinomycetes (P < 0.05) ( Table 2 and Figure 3).

Comparison of the dominant bacterial genera between the two groups of children
We selected the top 15 dominant bacterial genera in the two groups for comparison. The results showed that the abundance of Prevotella, Fusobacterium, Klebsiella, and Alistipes was significantly increased in the disease group (P < 0.05) while that of Lachnospiracea incertae sedis, Megamonas, Blautia, Clostridium XlVa, Bifidobacterium, and Eubacterium was significantly decreased (P < 0.05) ( Table 3 and Figure 4).

GM and clinical phenotypes
Spearman's correlation analysis was used to investigate associations between the GM of children with GHD and eight endocrine hormones. Our results showed that Bacteroides were positively correlated and Prevotella was negatively correlated with FIGURE 1 Chart showing comparison of microbiota diversity between the two groups.
Huang et al. 10.3389/fped.2023.1133258 Frontiers in Pediatrics insulin, while Alistipes and Haemophilus showed a negative correlation with GH. A positive correlation was also reported between Fusicatenibacter, Fusobacterium, and Sutterella, whereas Veillonella was negatively correlated with prolactin. Faecaliterium and FSH were positively correlated ( Figure 6).

The GM composition differed markedly between the disease and control groups
Compared with the healthy controls, children in the disease group showed reduced α-diversity in the GM, consistent with results reported in malnourished children (16). The phylum Bacteroides was more abundant in children from the disease group than in those from the control group while the opposite trend was observed for Firmicutes, in contrast to findings on obese and diabetic patients (17). The abundance of Prevotella in the disease group was also significantly higher than that in the control group. Prevotella can degrade broad-spectrum plant polysaccharides (18), and carbohydrate-based diets tend to form a Prevotella-dominated "gut type." Increased abundance of Prevotella abundance has been shown to reduce blood sugar and insulin levels, thus affecting energy absorption and promoting weight loss (19). In the disease group, the abundance of Fusobacterium, Klebsiella, Alistipes, and other genera was found to be significantly increased. Fusobacterium is present in the normal oral flora and can inhibit the immune response as well as promote the transformation of inflammation to malignancy (20). An increase in the abundance of both Klebsiella and Alistipes has been shown to be associated with intestinal inflammation (21,22); therefore, the increase in the population of these genera can promote chronic inflammation in the intestine and disrupt the function of the intestinal barrier. This can lead to a cellular biochemical imbalance, reduced absorption capacity, and increased susceptibility to enteric pathogen infections, and consequently affect energy metabolism and nutrient absorption (23). In addition, Klebsiella and Alistipes are both associated with neurological diseases (24) and can produce neurotransmitterrelated metabolites such as serotonin, dopamine, and histamine Principal component analysis.  (25). These neurotransmitters enter the brain through the gut-brain axis to regulate the energy balance and function of the hypothalamus (26,27). The hypothalamus is the highest regulatory center of thehypothalamic-pituitary-growth axis (HPA) and can reduce appetite and cause weight loss (28,29). Lachnospiracea incertae sedis, Megamonas, Blautia, Clostridium XlVa, and Bifidobacterium were found to be significantly reduced in the intestines of the disease group, which could lead to reduced concentrations of SCFAs such as butyric acid produced by these beneficial bacteria (30). Decreased abundance of Lachnospiracea incertae sedis might also affect protein synthesis (31), disturb the intestinal energy supply, and retard growth and development. Jensen et al. (5) reported that increased Prevotella abundance together with reduced numbers of Bifidobacterium can reduce the levels of growth hormone-releasing peptide (GHRP) and leptin, thus reducing the release of GH.

Significant differences in GM function between the two groups
The enriched functional categories in the GHD group included "Replication and repair, Energy metabolism, Poorly characterized, Metabolism of cofactors and vitamins, Nucleotide metabolism, Cellular processes and signaling, Nucleotide metabolism, Glycan biosynthesis and metabolism, Transcription, Folding sorting and degradation". Children with GHD showed dysregulation in energy metabolism, vitamin and related factor metabolism, and polysaccharide metabolism and biosynthesis. Considering that Prevotella significantly increases the catabolism of carbohydrates and that the abundance of butyric acid and other bacteria such as Lachnospiracea incertae sedis is significantly reduced in Comparison of the GM levels in the two groups. Frontiers in Pediatrics children with GHD, the GM imbalance in this population may affect the functions of the flora. This phenomenon may lead to chronic inflammation of the intestine and poor intake and absorption of nutrients such as fats and proteins, affecting both growth and development.

GM is closely related to the clinical phenotype
We conducted a correlation analysis of the GM and endocrine hormones and found that Prevotella abundance was negatively correlated with insulin. Significantly higher abundance of Prevotella can affect insulin secretion, which can not only regulate food intake (19,32) but also modulate blood glucose levels through signaling pathways essential for maintaining energy storage, glucose metabolism, sugar production, adipogenesis, cell growth, survival, and reproduction (33). We speculate that this significant increase in Prevotella abundance may be detrimental to growth and development. We also found a variety of other intestinal bacteria related to endocrine hormones and confirmed the interaction between the GM and endocrine hormones. Maintaining the stability of the GM is conducive to the promotion of growth and development.

Conclusion
There was a significant reduction in the α-diversity of the intestinal microbial composition in GHD children, together with an increased abundance of Bacteroides and reduced numbers of Firmicutes. Fusobacterium, Klebsiella, Alistipes, and other genera were significantly enriched in children with GHD while the numbers of Lachnospiracea incertae sedis, Megamonas, Blautia, Clostridium XlVa, and Bifidobacterium were significantly reduced. These imbalances in the GM were predicted to affect pathways involved in energy metabolism and biosynthesis, as well as induce abnormal secretion of insulin and other endocrine hormones, which may promote the occurrence and development of GHD.

Deficiencies and next steps
There are many factors that cause insufficiency in GH secretion in children with GHD, and GM imbalance may be one of the major factors. On the one hand, GM imbalance leads to the abnormal secretion of endocrine hormones as well as an abnormal production of microbial metabolites, especially neurotransmitters, that can influence the HPA through the gut-brain axis. The sample size in the present study was small, consisting of only 33 children with GHD; hence, large-sample, multi-center research is needed to verify the associations between the GM and GHD. Studies combined with metabolomics could better clarify the mechanism of action of the GM and its metabolites in growth and development. Correlations between GM compositions and endocrine hormones in children with GHD. Legend description: A correlation analysis was performed with eight clinical phenotypes and genera with a relative abundance of ≥0.1%. Results are shown as above where significance was expressed as *P < 0.05 and **P < 0.01. Comparison of GM functions between the two groups of children.

Data availability statement
The data presented in the study are deposited in the NCBI sequence Archive (SRA) database, accession number: PRJNA899674 .The data can be found at the following link: https://dataview.ncbi.nlm.nih. gov/object/PRJNA899674?reviewer= tu7mnej3p04c61u31c6f4v5hgo.

Ethics statement
The studies involving human participants were reviewed and approved by The Ethics Committee of Shenzhen Longgang District Maternity and Child Health Care Hospital approved the study, with the approval number of LGFYYXLL-024. Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin. Written informed consent was obtained from the minor(s)' legal guardian/next of kin for the publication of any potentially identifiable images or data included in this article.

Author contributions
CH and HL: managed the project. DM, YL, SL, and WY: were responsible for the registration of the clinical information of the enrolled children and the collection of stool samples according to the standard configuration. CH, YL, and ZY: were responsible for DNA extraction and biological information analysis, etc. HL and ZY: were responsible for tabulation and statistical analyses. CH and DM: were responsible for interpreting various data and writing papers. All authors contributed to the article and approved the submitted version.