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PWE-361 Colonic microbiome-metabonome network interactions in african americans and native africans: a prospective 2-week food exchange study
  1. J Li1,
  2. JM Kinross2,
  3. JP Posma1,
  4. L Lahti3,
  5. V Naidoo4,
  6. J Ou5,
  7. K Newton4,
  8. R Gaskins6,
  9. E Zoetendal7,
  10. S O'Keefe8,
  11. JK Nicholson1
  1. 1Computational and Systems Medicine
  2. 2Biosurgery and Surgical Technology, Imperial College London, London
  3. 3Laboratory of Microbiology, Wageningen University, Wageningen, UK
  4. 4Nelson R Mandela School of Medicine, Nelson R Mandela School of Medicine, University of KwaZulu, Natal, South Africa
  5. 5Department of Gastroenterology, Hepatology and Nutrition, University of Pittsburgh, Pittsburgh
  6. 6Department of Pathobiology, Institute for Genomic Biology and University of Illinois Cancer Center, University of Illinois at Urbana–Champaign, Urbana, United States
  7. 7The Laboratory of Microbiology, Wageningen University, Wageningen, Netherlands
  8. 8Department of Gastroenterology, Hepatology and Nutrition, University of Pittsburgh, Pittsburgh, UK


Introduction Higher rates of colon cancer are seen in African Americans (65:100,000) compared to rural South Africans (<5:100,000). Dietary-microbiome interactions associated with westernised diet may explain this association.

Method This was a prospective, 2-week food exchange study. 20 middle aged healthy Native Africans (NA) and 20 African Americans (AA) (age 50–65, BMI 18.5–35 kg/m2) were studied on their usual diet and after dietary modification to either a high meat and fat, low fibre western diet (protein 27%, fat 52%, carbohydrate 21%, total fibre 12 g/d) or a high fibre African diet under supervision for 2 weeks. Colonoscopy was performed for mucosal biomarkers of cancer risk from the colon (Ki67). Urinary and faecal samples were analysed by 600MHz 1HNMR (Bruker) and interpreted in Matlab v14a. Microbiome analysis was performed by the HITChip microarray. Metabolic reaction networks of metabolites found differentially expressed between different dietary comparisons, were created using the MetaboNetworks software.

Results Orthoganol Partial Least Square Discriminant Analysis regression coefficient plots of AA (faecal: Q2Y = 0.66, R2X = 37.2%, urinary Q2Y = 0.51, R2X 20.8%) and and NA (faecal: Q2Y = 0.37, R2X = 30.7%, urinary Q2Y = 0.83, R2X 27.8%) samples demonstrated distinct metabolic phenotypes for each dietary intervention. Increased diversity of metabolites was seen in faecal water of NAs consuming their usual diet. Faecal metabolites demonstrated a higher number of significant correlations with faecal microbiota compared with urinary metabolites. Eubacterium rectale, Lachnospira pectinoschiza, Roseburia intestinalisand Lactobacillus boviscorrelated strongly with butyrate, acetate and formate. The faceal metabolic network pathway analysis demonstrated reciprocal changes after dietary interventions reflecting reductions in short chain fatty acids and increases in glycosylated proteins and choline metabolism in NAs, and increased amino acid metabolism in AAs. Reciprocal changes in urinary metabolites derived from microbial metabolism of green vegetables, e.g. N-acetyl-S-methyl-L-cysteine sulfoxide (p < 0.001, r2= 0.64), were observed, suggesting increased phytochemical consumption may influence mucosal inflammation.

Conclusion A high fat low fibre western diet is associated with a specific, modifiable metabolic phenotype. This is significantly influenced by the gut microbiome, which in turn may have an important role in the cause of colon cancer.

Disclosure of interest J. Li: None Declared, J. Kinross Grant/ Research Support from: Imperial BRC, Conflict with: Director of Getwell media, J. Posma: None Declared, L. Lahti: None Declared, V. Naidoo: None Declared, J. Ou: None Declared, K. Newton: None Declared, R. Gaskins: None Declared, E. Zoetendal: None Declared, S. O'Keefe: None Declared, J. Nicholson: None Declared.

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