Influence of blood group and secretor status on carbohydrate structures in human gastric mucins: implications for peptic ulcer.
|
| Abstract |
1. The content and distribution of carbohydrate was examined in mucus glycopolypeptides from human antral mucosae. 2. The mean amount of carbohydrate per 1000 amino acid residues was found to be similar in glycopolypeptides with A, B or H activity. It was slightly, though significantly, less in glycopolypeptides lacking these determinants, because carbohydrate chains were of a shorter average length than in the A-, B- or H-active preparations. This difference was reflected in the sizes of oligosaccharide-alcohols released from representative glycopolypeptides with alkaline borohydride. 3. Differences between A-, B- or H-active and non-secretor glycopolypeptides in terms of the mean number of carbohydrate chains per 1000 amino acid residues were found to be small, and without significance. 4. The average number of peripheral monosaccharide units per 1000 amino acid residues was greater in A-active than in H-active, and least in non-secretor, glycopolypeptides. This order was reversed for monosaccharide units incorporated into skeletal (core plus backbone) structures. The difference in each case was statistically significant. 5. These findings suggest that the increased risk of peptic ulcer associated with blood group O and non-secretor status is unlikely to be attributable to an inherent deficiency in the protective mucus layer, linked to differences between mucins that are associated with A, B or H activity. Other hypotheses linked to infection with Helicobacter pylori are examined.
|
|---|---|
| Authors | R L Sidebotham, J H Baron, J Schrager, J Spencer, J R Clamp, L Hough |
| Journal | Clinical science (London, England : 1979) (Clin Sci (Lond)) Vol. 89 Issue 4 Pg. 405-15 (Oct 1995) ISSN: 0143-5221 [Print] England |
| PMID | 7493441 (Publication Type: Journal Article) |
| Chemical References |
|
| Topics |
|
Join CureHunter, for free Research Interface BASIC access!
Realize the full power of the drug-disease research graph!