Race-dependent association of sulfidogenic bacteria with colorectal cancer

Abstract

Objective: Colorectal cancer (CRC) incidence is higher in African Americans (AAs) compared with non-Hispanic whites (NHWs). A diet high in animal protein and fat is an environmental risk factor for CRC development. The intestinal microbiota is postulated to modulate the effects of diet in promoting or preventing CRC. Hydrogen sulfide, produced by autochthonous sulfidogenic bacteria, triggers proinflammatory pathways and hyperproliferation, and is genotoxic. We hypothesised that sulfidogenic bacterial abundance in colonic mucosa may be an environmental CRC risk factor that distinguishes AA and NHW.

Design: Colonic biopsies from uninvolved or healthy mucosa from CRC cases and tumour-free controls were collected prospectively from five medical centres in Chicago for association studies. Sulfidogenic bacterial abundance in uninvolved colonic mucosa of AA and NHW CRC cases was compared with normal mucosa of AA and NHW controls. In addition, 16S rDNA sequencing was performed in AA cases and controls. Correlations were examined among bacterial targets, race, disease status and dietary intake.

Results: AAs harboured a greater abundance of sulfidogenic bacteria compared with NHWs regardless of disease status. Bilophila wadsworthia-specific dsrA was more abundant in AA cases than controls. Linear discriminant analysis of 16S rRNA gene sequences revealed five sulfidogenic genera that were more abundant in AA cases. Fat and protein intake and daily servings of meat were significantly higher in AAs compared with NHWs, and multiple dietary components correlated with a higher abundance of sulfidogenic bacteria.

Conclusions: These results implicate sulfidogenic bacteria as a potential environmental risk factor contributing to CRC development in AAs.

Keywords: COLONIC MICROFLORA; COLORECTAL CANCER; HYDROGEN SULPHIDE.

Figure 1

Differences in mean gene copy numbers of sulfidogenic bacteria comparing colorectal cancer cases and controls in African Americans (AAs) and non-Hispanic whites. A. Scatterplot representations of mean gene copy numbers per nanogram of DNA of sulfidogenic bacterial targets in African Americans compared with non-Hispanic whites with median and upper and lower quartiles indicated. African Americans are represented in green, and non-Hispanic whites are represented in purple. All comparisons had a p<0.001. B. Scatterplot representations of mean gene copy numbers per nanogram of DNA of sulfidogenic bacterial targets in cases and controls in each racial group. African Americans cases are represented in light green and controls in dark green. Non-Hispanic white cases are represented in light purple and controls in dark purple.

Figure 1

Differences in mean gene copy numbers of sulfidogenic bacteria comparing colorectal cancer cases and controls in African Americans (AAs) and non-Hispanic whites. A. Scatterplot representations of mean gene copy numbers per nanogram of DNA of sulfidogenic bacterial targets in African Americans compared with non-Hispanic whites with median and upper and lower quartiles indicated. African Americans are represented in green, and non-Hispanic whites are represented in purple. All comparisons had a p<0.001. B. Scatterplot representations of mean gene copy numbers per nanogram of DNA of sulfidogenic bacterial targets in cases and controls in each racial group. African Americans cases are represented in light green and controls in dark green. Non-Hispanic white cases are represented in light purple and controls in dark purple.

Figure 2

Analysis of bacterial 16S rDNA data identifies differences in bacterial abundances comparing African American colorectal cancer (CRC) cases and controls. A. Differences identified by linear discriminant analysis. Effect sizes were calculated by the LEfSe algorithm and genera associated with effect size differences ≤−log2 and ≥log2 are shown. Genera associated with control samples are in green, and genera associated with CRC are in red. B. Scatterplot representations of the bacterial genera identified by LEfSe analysis in cases and controls. Each point is the logarithm of the proportion of each indicated bacterial genera with median and average indicated. The null measurements are not indicated on the plot. The numbers of nulls for each subject (case/control) by genera is Faecalibacterium 1 case/1 control, Pseudomonas 22/31, Peptostreptococcaceae 58/64, Alistipes 61/94, Delftia 62/79, Mogibacteriaceae 62/94, Micrococcus 62/94, Pyramidobacter 58/92, Christensenellaseae 54/92, Cc_115 Erysipelotrichaceae 60/93, Bacteroidales S24-7 49/81 and Ruminococcus 32/65. C. Scatterplot representations of abundances of three selected sulfidogenic bacteria—Fusobacterium, Desulfovibrio and Bilophila—shown as in B. The numbers of nulls for each subject (case/control) by genera are Fusobacterium 34/55, Bilophila 52/81 and Desulfovibrio 57/83. LDA, linear discriminant analysis.

Figure 2

Analysis of bacterial 16S rDNA data identifies differences in bacterial abundances comparing African American colorectal cancer (CRC) cases and controls. A. Differences identified by linear discriminant analysis. Effect sizes were calculated by the LEfSe algorithm and genera associated with effect size differences ≤−log2 and ≥log2 are shown. Genera associated with control samples are in green, and genera associated with CRC are in red. B. Scatterplot representations of the bacterial genera identified by LEfSe analysis in cases and controls. Each point is the logarithm of the proportion of each indicated bacterial genera with median and average indicated. The null measurements are not indicated on the plot. The numbers of nulls for each subject (case/control) by genera is Faecalibacterium 1 case/1 control, Pseudomonas 22/31, Peptostreptococcaceae 58/64, Alistipes 61/94, Delftia 62/79, Mogibacteriaceae 62/94, Micrococcus 62/94, Pyramidobacter 58/92, Christensenellaseae 54/92, Cc_115 Erysipelotrichaceae 60/93, Bacteroidales S24-7 49/81 and Ruminococcus 32/65. C. Scatterplot representations of abundances of three selected sulfidogenic bacteria—Fusobacterium, Desulfovibrio and Bilophila—shown as in B. The numbers of nulls for each subject (case/control) by genera are Fusobacterium 34/55, Bilophila 52/81 and Desulfovibrio 57/83. LDA, linear discriminant analysis.

Figure 3

Linear discriminant analysis identifies differences between colorectal cancer (CRC) cases and controls. Effect size calculated by the LEfSe algorithm identifies genera strongly associated with differences between CRC cases and controls in right-sided colonic biopsies (A) and in left-sided colonic biopsies (B), as well as differences based on age, comparing cases <50 and controls <50 (C) and comparing cases <50 and cases ≥50 (D). Genera associated with control samples are in green and genera associated with CRC are in red in panels A–C; genera associated with cases <50 are in red and cases ≥50 are in green in panel D. LDA, linear discriminant analysis.

Figure 4

Comparison of selected factors that explain differences in sulfidogenic bacteria in African Americans and non-Hispanic whites. A. Scatterplot representations of residuals of linear models for selected bacterial targets, namely, pan-dsrA, Desulfovibrio spp. and B. wadsworthia. African Americans are represented in green, and non-Hispanic whites are represented in purple. Cases are represented as open circles and controls as closed circles. B. Forest plots of effect size estimates from the linear models. Outcome variables are log-transformed gene copy abundances of pan-dsrA, Desulfovibrio spp. and B. wadsworthia. Points and lines on each plot represent the point estimate and 95% CI, respectively, for each covariate in the model. Estimates reflect predicted change in variable for one unit change in outcome. Positive associations are in blue, negative associations are in red. p value for each covariate is represented on the right, and statistically significant values after Bonferroni correction are in bold. The wide CI seen in the body mass index (BMI), underweight class is explained by the small number of observations in this class.