Tipping the Balance: Vitamin D Inadequacy in Children Impacts the Major Gut Bacterial Phyla

Abstract

Vitamin D inadequacy appears to be on the rise globally, and it has been linked to an increased risk of osteoporosis, as well as metabolic, cardiovascular, and autoimmune diseases. Vitamin D concentrations are partially determined by genetic factors. Specific single nucleotide polymorphisms (SNPs) in genes involved in vitamin D transport, metabolism, or binding have been found to be associated with its serum concentration, and these SNPs differ among ethnicities. Vitamin D has also been suggested to be a regulator of the gut microbiota and vitamin D deficiency as the possible cause of gut microbial dysbiosis and inflammation. This pilot study aims to fill the gap in our understanding of the prevalence, cause, and implications of vitamin D inadequacy in a pediatric population residing in Qatar. Blood and fecal samples were collected from healthy subjects aged 4-14 years. Blood was used to measure serum metabolite of vitamin D, 25-hydroxycholecalciferol 25(OH)D. To evaluate the composition of the gut microbiota, fecal samples were subjected to 16S rRNA gene sequencing. High levels of vitamin D deficiency/insufficiency were observed in our cohort with 97% of the subjects falling into the inadequate category (with serum 25(OH)D < 75 nmol/L). The CT genotype in rs12512631, an SNP in the GC gene, was associated with low serum levels of vitamin D (ANOVA, p = 0.0356) and was abundant in deficient compared to non-deficient subjects. Overall gut microbial community structure was significantly different between the deficient (D) and non-deficient (ND) groups (Bray Curtis dissimilarity p = 0.049), with deficient subjects also displaying reduced gut microbial diversity. Significant differences were observed among the two major gut phyla, Firmicutes (F) and Bacteroidetes (B), where deficient subjects displayed a higher B/F ratio (p = 0.0097) compared to ND. Vitamin D deficient children also demonstrated gut enterotypes dominated by the genus Prevotella as opposed to Bacteroides. Our findings suggest that pediatric vitamin D inadequacy significantly impacts the gut microbiota. We also highlight the importance of considering host genetics and baseline gut microbiome composition in interpreting the clinical outcomes related to vitamin D deficiency as well as designing better personalized strategies for therapeutic interventions.

Keywords: Bacteroidetes to Firmicutes ratio; Qatar; gut microbiota; host genetics; pediatric vitamin D deficiency.

Figure 1

The chosen candidate genes’ involvement in the vitamin D cascade are displayed. Vitamin D is mostly obtained through sunlight or food sources in humans. UVB light from the sun penetrates the skin and converts 7-dehydrocholesterol (7DHC) to pre-vitamin D, which is rapidly transformed to vitamin D. DHCR7/NADSYN1 removes 7DHC from the vitamin D pathway. D is hydroxylated in the liver to 25(OH)D3, primarily by CYP2R1. Following that, 25(OH)D is delivered to the kidney by vitamin D binding protein (VDBP), which is encoded by GC, where it is converted by CYP27B1 to its active form, 1,25(OH)2D. Finally, CYP24A1 catabolizes both 25(OH)D and 1,25(OH)2D to calcitroic acid, which is physiologically inactive and water soluble. The active form of vitamin D bound to VDBP is delivered in blood to its target cells, where it acts as a ligand for the vitamin D receptor (VDR), a nuclear transcription factor that regulates transcription and translation of messenger RNA, leading to the synthesis of vitamin D-dependent proteins.

Figure 2

Alpha and beta diversity plot comparisons for the vitamin D deficient (D) and non-deficient (ND) groups. (a) Observed species, Chao1, Shannon, and Inverse Simpson boxplots representing the alpha-diversity indices. The horizontal line inside the box indicates the median, while the boxes reflect the interquartile range (IQR) between the first and third quartiles (25th and 75th percentiles, respectively). Whiskers reflect the lowest and greatest values from the first and third quartiles that are within 1.5 times the IQR, respectively. The Wilcoxon test with FDR–Bonferroni corrected p values was used to determine statistical significance. * p < 0.05; (b) CCA plot showing the beta diversity measure ** p < 0.01 deep purple: deficient samples, blue: non-deficient. Each dot represents an individual sample. The figure was generated using RStudio v 1.4 with R v 4.1.

Figure 3

Comparison of the gut microbiota composition in vitamin D deficient (D) and non-deficient (ND) groups at the phylum level. (a) Relative abundance of different bacterial phyla in the deficient and non-deficient groups. The relative abundance of the major bacterial phyla, Firmicutes and Bacteroidetes, showed variation between the two groups. The abundance of Phylum Bacteroidetes was significantly elevated in the D group as compared to ND (Wilcoxon test with false discovery rate (FDR)–Bonferroni corrected, * p < 0.05). The figure was generated using RStudio v 1.4 with R v 4.1. (b) Comparison of the ratio of Bacteroidetes to Firmicutes in vitamin D deficient (D) and non-deficient (ND) groups (Wilcoxon test with false discovery rate (FDR)–Bonferroni corrected, * p < 0.05). The figure was generated using RStudio v 1.4 with R v 4.1. Comparison of the gut microbiota composition in vitamin D deficient (D) and non-deficient (ND) groups at the genus level. (c) Relative abundance of different bacterial genus in the deficient and non-deficient groups. The relative abundance of the major bacterial genera, Prevotella and Bacteroides, showed variation between the two groups. (d) Abundance of genus Prevotella 9 was significantly elevated in the D group as compared to ND. (e) Comparison of the ratio of Bacteroides to Prevotella in vitamin D deficient (D) and non-deficient groups (ND) groups (Wilcoxon test with false discovery rate (FDR)–Bonferroni corrected, * p < 0.05 and ** p < 0.01; **** p < 0.0001. The figure was generated using RStudio v 1.4 with R v 4.1.

Figure 4

PICRUSt was used to infer gut microbiota functions using the 16S rRNA gene sequence data from vitamin D deficient (D) and non-deficient (ND) groups. The differences in projected functions of genes involved in fatty acid metabolism, as well as lipopolysaccharide biosynthesis and lipopolysaccharide biosynthesis proteins, are highlighted.

Figure 5

(a) The CT genotype (SNP rs12512631 in the GC gene) was associated with low levels of serum vitamin D and (b) was highly abundant in the deficient compared to non-deficient subjects (ANOVA * p < 0.05). (c) Overall microbial abundance was significantly different between the three genotypes of SNP rs12512631 (Kruskal–Wallis followed by post hoc Dunn’s test with false discovery rate (FDR)–Bonferroni corrected, ** p < 0.01).

Figure 6

Random forest analysis used to determine the variables that had the largest contribution in determining the vitamin D levels. Inc Node Purity was used as a measure of “variable importance”.