A prospective cohort analysis of gut microbial co-metabolism in Alaska Native and rural African people at high and low risk of colorectal cancer

Abstract

Background: Alaska Native (AN) people have the world's highest recorded incidence of sporadic colorectal cancer (CRC) (∼91:100,000), whereas rural African (RA) people have the lowest risk (<5:100,000). Previous data supported the hypothesis that diet affected CRC risk through its effects on the colonic microbiota that produce tumor-suppressive or -promoting metabolites.

Objectives: We investigated whether differences in these metabolites may contribute to the high risk of CRC in AN people.

Methods: A cross-sectional observational study assessed dietary intake from 32 AN and 21 RA healthy middle-aged volunteers before screening colonoscopy. Analysis of fecal microbiota composition by 16S ribosomal RNA gene sequencing and fecal/urinary metabolites by 1H-NMR spectroscopy was complemented with targeted quantification of fecal SCFAs, bile acids, and functional microbial genes.

Results: Adenomatous polyps were detected in 16 of 32 AN participants, but not found in RA participants. The AN diet contained higher proportions of fat and animal protein and less fiber. AN fecal microbiota showed a compositional predominance of Blautia and Lachnoclostridium, higher microbial capacity for bile acid conversion, and low abundance of some species involved in saccharolytic fermentation (e.g., Prevotellaceae, Ruminococcaceae), but no significant lack of butyrogenic bacteria. Significantly lower concentrations of tumor-suppressive butyrate (22.5 ± 3.1 compared with 47.2 ± 7.3 SEM µmol/g) coincided with significantly higher concentrations of tumor-promoting deoxycholic acid (26.7 ± 4.2 compared with 11 ± 1.9 µmol/g) in AN fecal samples. AN participants had lower quantities of fecal/urinary metabolites than RA participants and metabolite profiles correlated with the abundance of distinct microbial genera in feces. The main microbial and metabolic CRC-associated markers were not significantly altered in AN participants with adenomatous polyps.

Conclusions: The low-fiber, high-fat diet of AN people and exposure to carcinogens derived from diet or environment are associated with a tumor-promoting colonic milieu as reflected by the high rates of adenomatous polyps in AN participants.

Keywords: Alaska Native people; bile acids; butyrate; colorectal cancer; deoxycholic acid; dietary fiber; gut microbiota; rural African people; short-chain fatty acids.

Copyright © The Author(s) 2019.

Figures

FIGURE 1

The fecal microbiota of AN participants shows a separate clustering and abundance pattern at genus level compared with RA participants. (A) Shannon effective index and (B) MDS plot of generalized UniFrac distances (including permutational multivariate ANOVA test to determine group separation) showing distinct clustering of fecal microbiota profiles detected in the fecal microbiota of AN and RA study participants by 16S rRNA gene sequencing. (C) Cumulative relative abundance of the major gut-related phyla acquired by taxonomic binning of OTUs detected in the fecal microbiota of AN and RA participants by 16S rRNA gene sequencing; each column represents 1 individual. (D) Relative abundance of most abundant genera assigned by taxonomic binning of OTUs detected in the AN and RA fecal microbiota by 16S rRNA gene sequencing in box-and-whisker plots showing minimum to maximum. Statistical analysis used the nonparametric Mann–Whitney U test corrected for multiple testing by the Benjamini–Hochberg method with AN n = 29 and RA n = 20 or 21 samples, respectively. P < 0.05 was considered statistically significant: *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001; ns = nonsignificant. AN, Alaska Native; MDS, multidimensional scaling; OTU, operational taxonomic unit; RA, rural African; rRNA, ribosomal RNA.

FIGURE 2

Fecal water and urine of samples from AN participants show separate metabolite profiles and are less diverse compared with RA samples. (A, B) Average 1H-NMR spectrum of AN and RA (A) fecal water or (B) urine samples with significant peaks shown in red (higher in AN participants) and blue (higher in RA participants) in top panels (see Table 3 for metabolites and their chemical shifts). The corresponding bottom panels show the Skyline significance (−log10Q value × sign of regression coefficient β). The horizontal dashed lines indicate the false discovery rate of 5% on the log10 scale. (C, D) Scores plots of the Monte-Carlo cross-validated partial least-squares discriminant analysis model (21) with KDE and model statistics displayed on top of (C) fecal water and (D) urinary data. Average score is displayed in a red cross (for AN participants) and blue circle (for RA participants). The x axis shows the average scores of the first component of the model, the y axis the second component, and the x axis of the top panel shows the predicted overall score with the KDE (distribution of scores across all models). For both data sets the groups show distinct separation [model goodness of prediction (Q2Y) is (C) 0.65 with a high RCV of 0.74 or (D) 0.56 with a high RCV of 0.64]. Statistical analysis was performed with n = 48 urine (27 AN, 21 RA) and n = 53 fecal water samples. AN, Alaska Native; KDE, kernel density estimate; RA, rural African, RCV, robustness of cross-validation.

FIGURE 3

The fecal water/urinary metabolite profiles of AN participants cluster in separate metabolic networks and correlate with distinct microbial genera compared with RA participants. (A) Metabolic reaction networks of metabolites found differentially expressed between AN and RA participants’ urine and feces. The network shows links between metabolites, if the reaction entry in Kyoto Encyclopedia of Genes and Genomes indicates a main reactant pair and the reaction is either mediated by 1) an enzyme linked to human genes, 2) an enzyme linked to genes from identified bacterial groups, or 3) it is part of a spontaneous process. The color of the metabolites indicates whether the metabolite is found in higher concentrations in the AN (red) or RA (blue) urine/feces, or whether the metabolites are not significantly associated with any comparison but are part of the metabolic network (white). (B) Heat map of Spearman correlations between fecal and urinary metabolites associated with differences in AN and RA participants with 16S rRNA gene sequencing data. Correlations were adjusted for multiple testing using the Benjamini–Hochberg FDR. Significant correlations (at FDR of 1%) are indicted by a white '+'. A thick black line indicates a split between either kingdom (x axis) or biofluid (y axis), a solid line indicates different phyla, and a dashed line indicates different class (x axis) and a different sign of association between AN and RA samples (y axis). The color of the metabolites/microbial genera indicates whether it is found in greater concentrations in AN (red) or RA (blue) participants or if there is no significant difference between both groups (black). Statistical analysis was performed with sample numbers as listed for previous analyses in Figures 1 and 2. ADMA, asymmetric dimethyl arginine; AN, Alaska Native; DMA, dimethylamine; FAICAR, 5-Formamido-1-(5-phosphoribosyl)imidazole-4-carboxamide; FDR, false discovery rate; GAR, glycinamide ribonucleotide; GSH, glutathione; 2HIB, 2-hydroxyisobutyrate; IMP, inosine monophosphate; LTA4, leukotriene A4; LTC4, leukotriene C4; NA, nicotinamide; NAAG, N-Acetylaspartylglutamate; NANA, N-Acetylneuraminic acid; PAG, phenylacetylglutamine; PAP, phosphoadenosine phosphate; PRPP, 5-Phosphoribosyl 1-pyrophosphate; RA, rural African; SMCSO=S-methylcysteine sulfoxide; TCA, tricarboxylic acid; TMA, Trimethylamine, XMP, Xanthosine monophosphate.

FIGURE 4

Concentrations of SCFAs are significantly lower in AN than in RA fecal samples, not correlating with the abundance of bacterial genes involved in butyrate synthesis. Concentrations of (A) acetic acid, (B) propionic acid, (C) butyric acid, and (D) total SCFAs detected by GC in feces of AN and RA participants. (E) Percentaged ratio of major SCFAs to total concentrations of SCFAs in feces of AN and RA participants. Gene copy numbers of (F) bcoA and (G) buk representative for butyrate-producing bacteria, (H) dsrA representative for sulfate-reducing bacteria, and (I) mcrA involved in production of methane by Archaea in the AN and RA fecal microbiota using qPCR. Dashed line indicates the detection limit of qPCR. Statistical analysis was performed by an unpaired t test (data normally distributed) or a nonparametric Mann–Whitney U test (data not normally distributed) with AN n = 32, RA n = 21 samples. P < 0.05 was considered statistically significant: **P < 0.01; ***P < 0.001; ****P < 0.0001. AN, Alaska Native; bcoA, butyryl CoA:acetate-CoA transferase; buk, butyrate kinase; dsrA, dissimilatory sulfite reductase subunit A; mcrA, methyl coenzyme-M reductase A; RA, rural African.

FIGURE 5

Concentrations of major primary and secondary bile acids are higher in AN than in RA fecal samples, consistent with a greater capacity for bile acid conversion and independent of conjugation status. Concentrations of (A) CA, (B) CDCA, and (C) DCA detected by LC-MS in feces of AN and RA participants. (D) Gene copy numbers of baiCD representative for 7α-dehydroxylating bacteria detected in the fecal microbiota of AN and RA participants by qPCR. Dashed line indicates the detection limit of qPCR. Concentrations of (E) LCA, (F) UDCA, and bile acids conjugated to (G) glycine (GCA, GCDCA, GDCA) or (H) taurine (TCA, TCDCA, TDCA) detected by LC-MS in AN and RA fecal samples. Statistical analysis was performed by an unpaired t test (data normally distributed) or a nonparametric Mann–Whitney U test (data not normally distributed) with AN n = 32, RA n = 21 samples. P < 0.05 was considered statistically significant: *P < 0.05; **P < 0.01; ****P < 0.0001. AN, Alaska Native; baiCD, bile acid-inducible operon; CA, cholic acid; CDCA, chenodeoxycholic acid; DCA, deoxycholic acid; GCA, glycocholic acid; GCDCA, glycochenodeoxycholic acid; GDCA, glycodeoxycholic acid; LCA, lithocholic acid; RA, rural African; TCA, taurocholic acid; TCDCA, taurochenodeoxycholic acid; TDCA, taurodeoxycholic acid; UDCA, ursodeoxycholic acid.

FIGURE 6

Adenomatous polyps in the colon have minor impact on the fecal microbiota of AN participants. (A) MDS plot of generalized UniFrac distances (including permutational multivariate ANOVA test to determine group separation) showing no distinct clustering of fecal microbiota profiles detected in the fecal microbiota of AN study participants with (AN +p) or without (AN -p) adenomatous polyps in the colon by 16S rRNA gene sequencing. (B, C) Relative abundance of genera of the fecal microbiota of AN participants that are significantly differently abundant between AN study participants with (AN +p) or without (AN -p) adenomatous polyps in the colon assigned by taxonomic binning of operational taxonomic units detected in the AN and RA fecal microbiota by 16S rRNA gene sequencing. Statistical analysis used a nonparametric Mann–Whitney U test corrected for multiple testing by the Benjamini–Hochberg method with AN n = 29 samples. P < 0.05 was considered statistically significant: *P < 0.05. AN, Alaska Native; MDS, multidimensional scaling.