Polymorphism in autophagy-related genes LRP1 and CAPZA1 may promote gastric mucosal atrophy

The C/C Genotype of rs1231760 in RGS2 Is a Risk Factor for the Progression of H. pylori-Positive Atrophic Gastritis by Increasing RGS2 Expression

BACKGROUND

Chronic gastritis caused by Helicobacter pylori (H. pylori) infection can progress to gastric cancer through atrophic gastritis (AG). The risk of gastric cancer increases with the progression of AG. Therefore, investigating the risk factors for the progression of AG is important.

METHODS

Using the GTEx and GEO databases, we extracted thirty-four candidate genes involved in the progression of AG. Then, with in silico analysis using HaploReg v4.1 and JASPAR (Matrix ID: MA0113.3), we extracted rs1231760 of RGS2 as a key single-nucleotide polymorphism (SNP) that could be involved in the functional change in the candidate gene. A correlation analysis between the selected SNP and AG in 200 H. pylori-positive and 302 H. pylori-negative participants was conducted. For functional analysis of the SNP, a dual-luciferase assay using reporter plasmids with a major or minor allele sequence was carried out.

RESULTS

The frequency of the C/C genotype of rs1231760 was higher in the AG group than in the non-AG group (p = 0.0471). Functional analysis showed that the transcriptional activities were higher at the dexamethasone-stimulating C allele than at the others (p < 0.05).

CONCLUSIONS

The C/C genotype of rs1231760 in RGS2 could be a biomarker of high-risk H. pylori-positive AG because of an increase in RGS2 expression.

Autophagy-Related Gene ATG7 Polymorphism Could Potentially Serve as a Biomarker of the Progression of Atrophic Gastritis

Cytotoxin-associated gene A (CagA) is an oncoprotein that H. pylori injects into the host's gastric epithelial cells and that induces proinflammatory cytokines, such as interleukin (IL)-18 and IL-1β. As a result, it leads to atrophic gastritis (AG), a precancerous lesion of gastric cancer. On the other hand, host cells degrade CagA using autophagy systems. However, few studies exist about the single nucleotide polymorphisms (SNPs) in MAP1LC3A, MAP1LC3B, ATG4A, ATG4B, ATG4C, ATG7, and ATG13, which belong to the autophagy-related genes concerning AG. This study aimed to detect biomarkers associated with AG. Herein, H. pylori-positive subjects (n = 200) were divided into the AG (n = 94) and non-AG (n = 106) groups. Thirty tag SNPs were selected from the above seven candidate genes. The SNP frequency between the two groups was analyzed. The frequency of the C/T or T/T genotype at rs4683787 of ATG7 was significantly lower in the AG group than in the non-AG group (p = 0.034, odds ratio = 0.535). Based on multivariate analysis, the C/C genotype of rs4684787 and age were independently associated with gastric mucosal atrophy. This finding helps stratify the patients needing timely endoscopic screening or early eradication of H. pylori.

ATG16L1 and ATG12 Gene Polymorphisms Are Involved in the Progression of Atrophic Gastritis

Helicobacter pylori (H. pylori) infection causes a progression to atrophic gastritis and results in gastric cancer. Cytotoxin-associated gene A (CagA), a major virulence factor of H. pylori, is injected into gastric epithelial cells using the type IV secretion system. On the other hand, gastric epithelial cells degrade CagA using an autophagy system, which is strictly regulated by the autophagy-related (ATG) genes. This study aimed to identify SNPs in ATG5, ATG10, ATG12, and ATG16L1 associated with gastric mucosal atrophy (GMA). Here, two-hundred H. pylori-positive participants without gastric cancer were included. The degree of GMA was evaluated via the pepsinogen method. Twenty-five SNPs located in the four candidate genes were selected as tag SNPs. The frequency of each SNP between the GMA and the non-GMA group was evaluated. The rs6431655, rs6431659, and rs4663136 in ATG16L1 and rs26537 in ATG12 were independently associated with GMA. Of these four SNPs, the G/G genotype of rs6431659 in ATG16L1 has the highest odd ratio (Odds ratio = 3.835, 95% confidence intervals = 1.337-1.005, p = 0.008). Further functional analyses and prospective analyses with a larger sample size are required.