Failure to Confirm Association of vac A Gene Mosaicism with Duodenal Ulcer Disease

Abstract

Background: Mosaicism of the Helicobacter pylori vac A gene comprises two families of allelic variations of the signal sequence region (s1, s2) and of the mid-region (m1, m2). Initial studies suggested that peptic ulcer disease correlated with the s1 subtype of vac A. We compared the prevalence of various vac A genotypes of H. pylori isolates obtained from duodenal ulcer (DU) patients and subjects with simple gastritis. Those isolates with s1 type were further examined to determine whether the specific vac A s1 (s1a versus s1b) genotype enabled prediction of gastroduodenal disease. Methods: H. pylori isolates were obtained from 38 patients with endoscopically documented DU and 39 individuals with asymptomatic H. pylori gastritis from Houston, Texas. The vac A genotype of each isolate was determined by polymerase chain reaction (PCR) amplification of genomic DNA for specific regions of the vac A gene. Those isolates with s1 vac A subtype were further examined to determine whether they had s1a or s1b mosaicism. Results: There was no difference in frequency of the s1 genotype of isolates obtained from patients with duodenal ulcer or asymptomatic H. pylori gastritis in this sample (84% versus 79%, respectively; P = 0.77). The s1/m1 vac A genotype was detected in isolates from 16 duodenal ulcer patients versus 15 with H. pylori gastritis (P = 0.82). Detailed analysis of the s1 region failed to show a correlation of either s1a or s1b with duodenal ulcer. Both s1a and s1b genotypes were detected in 24 strains, and both m1 and m2 mid-gene PCR amplicons were seen in 16 strains. Conclusions: We were unable to use H. pylori vac A genotyping to predict type of gastroduodenal disease in our patient sample. This failure to confirm an association of vac A genotype and duodenal ulcer disease differs from samples from other regions. This most likely represents an example of differences in H. pylori strains infecting host populations in different geographic regions. This study confirms the importance of establishing statistical associations with isolates from widely separate geographic regions before concluding that disease-related associations exist.