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Single nucleotide polymorphisms of whole genes and atrophic gastritis susceptibility:a systematic review and
Li-Rong Yan1, Zhi Lv1, Jing-Jing Jing1
1Tumor Etiology and Screening Department of Cancer Institute and General Surgery, The First Affiliated Hospital of China Medical University, Key Laboratory of Cancer Etiology and Prevention, China Medical University, Liaoning Provincial Education Department, Shenyang 110001, China.
Background:
Atrophic gastritis (AG) is one of the important precancerous lesions of gastric cancer. Single nucleotide polymorphisms (SNPs) are closely related to AG susceptibility. However, the research conclusions on the predictive potential of SNPs are inconsistent. The study aims to retrospect the association between SNPs of whole genes and AG risk by meta-analysis.
Materials And Methods:
Up to April 29, 2020, a systematic literature search for the relationship of SNPs with AG susceptibility was performed utilizing PubMed, Web of Science and Chinese National Knowledge Infrastructure. The overall and stratified meta-analyses on extracted data were conducted by Stata11.2.
Results:
33 case-control studies were enrolled containing 9951 AG patients and 17,252 healthy controls, and 17 SNPs in 12 different genes were systematically reviewed. The results indicated that 12 genes could be categorized based on their functions, including immune response, cell proliferation and apoptosis, and DNA damage repair. For the SNPs in immune response-related genes, the C allele of TLR1 rs4833095 T/C increased AG risk to 1.21-fold and the recessive model of TLR4 rs11536878 in the TLR gene family decreased AG susceptibility to 0.48-fold. The variant alleles of IL-10 rs1800871 (OR = 1.21) and IL-8 rs4073 (OR = 1.22) in the IL gene family were positively associated with AG risk. PSCA rs2294008 enhanced AG risk in all genetic models. SNPs associated with AG susceptibility were mainly focused on immune response-related genes.
Conclusion:
These SNPs related to immune response could influence on AG risk and have potential to be AG predictive biomarkers. It is worth noting that the number of studies for each SNPs were insufficient due to the limited published researches and updated meta-analysis needs to be performed based on extensive relevant studies for more reliable results.
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