GBAP1 polymorphisms (rs140081212, rs1057941 and rs2990220) contribute to reduced risk of gastric cancer
Abstract
Aim: This study was designed to evaluate the contribution of GBAP1 variants to gastric cancer (GC) risk in a Chinese Han population. Methods: The genotypes of GBAP1 polymorphisms were detected using the Agena MassARRAY platform. Logistic regression analysis was used to calculate odds ratios (ORs) and 95% CIs. Results:GBAP1 rs140081212 (OR = 0.51, p = 4.50 × 10-07), rs1057941 (OR = 0.48, p = 1.19 × 10-08) and rs2990220 (OR = 0.46, p = 7.34 × 10-09) contribute to reduced GC risk, especially gastric adenocarcinoma. Interestingly, the contribution of GBAP1 variants to GC susceptibility was associated with age, sex, BMI, smoking and drinking. Conclusion: This research suggested that GBAP1 polymorphisms might provide a protective effect against GC occurrence in a Chinese Han population.
Gastric cancer (GC) is a highly malignant tumor of the digestive tract, originating from the epithelial cells of the gastric mucosa. GC (7.7% of all cancer deaths) is the fourth leading cause of cancer deaths worldwide, following only lung, colorectal and liver cancer in mortality [1]. More than one million new cases of GC are diagnosed worldwide every year. GC is more prevalent in males, and the ratio of males to females with GC incidence is approximately 2.2:1 in developed countries and 1.83:1 in developing countries [2]. GC poses a major threat to the health of patients worldwide, especially in China [3]. GC is a complex and heterogeneous disease and the occurrence and development of GC are associated with genetic, environmental and lifestyle factors [4]. Previous studies have shown that the accumulation of genetic abnormalities, including SNPs, plays an important role in gastric carcinogenesis [5–7]. An in-depth study of gene polymorphisms is useful for the assessment of risk for GC susceptibility.
The GBA gene encodes the enzyme glucocerebrosidase, which catalyzes the hydrolysis of the membrane glucosylceramide to ceramide and glucose [8]. GBA variants have been reported to be associated with GC susceptibility [9]. GBAP1 located downstream of the GBA gene, a DNA sequence with high homology to GBA, can act as a competing endogenous RNA by binding competitively with miRNA to regulate GBA expression [10]. GBAP1 was reported as a candidate biomarker for the diagnosis and prognosis of hepatocellular carcinoma [11]. The exon dosage alteration in GBA-GBAP1 was associated with Parkinson's disease [12]. The expression of GBAP1 and GBA was higher and positively correlated in GC tissues, and overexpression of GBAP1-promoted cell proliferation, invasion and metastasis. Previous genome-wide association studies (GWASs) have identified a genetic variation in GBAP1 that is significantly associated with decreased GC risk, in which SNP rs2990245, located in the promoter of pseudogene GBAP1, is associated with GC risk [13]. However, there are still many GC risk-related genetic polymorphisms in GBAP1 that have not been explored.
Based on a minor allele frequency (MAF) >0.05 in the Chinese population from the 1000 Genomes Project data (https://www.internationalgenome.org/) [14] and genotyping call rate ≥95%, three SNPs in GBAP1, including rs140081212 (g.155184975A >G), rs1057941 (g.155216951G >C) and rs2990220 (g.155190254T >A) were randomly selected from all SNPs that met the criteria for genotyping. Here, GBAP1 polymorphisms were genotyped to evaluate the contribution of GBAP1 genetic variants to the risk of GC occurrence among a Chinese Han population. The association of these variants with age-, sex-, BMI-, smoking- and drinking-related differences in GC predisposition was assessed, along with the relation of these variants to clinical phenotypes (pathological type, lymph nodes metastasis and stage).
Methods
Study population
This study included 509 patients with GC and 507 healthy controls who were recruited from the Affiliated Hospital of Xizang, Minzu University. All participants were unrelated and of the Han Chinese population. Patients with GC were confirmed by two pathologists through analysis of biopsies of gastric tumors obtained by endoscopy. Patients with other tumor histories, any radiotherapy/chemotherapy prior to the study and serious chronic or immunological diseases were excluded. Individuals with a history of cancer, chronic gastritis, chronic atrophic gastritis or intestinal metaplasia or other serious diseases were excluded from the control group. Patients with GC and healthy controls were age- and sex-matched. Sociodemographic and medical characteristics of subjects were recorded from interviews and medical records. This study was approved by the institutional review board of the Affiliated Hospital of Xizang, Minzu University (no. 2017010) and was in accordance with the World Medical Association Declaration of Helsinki. All participants signed written informed consent.
SNP genotyping
DNA was extracted from peripheral blood samples (5 mL) using a commercially available GoldMag DNA Blood Mini Kit (GoldMag Co. Ltd., Xi'an, China). The genotypes of GBAP1 polymorphisms (rs140081212, rs1057941 and rs2990220) were detected using the Agena MassARRAY platform (Agena, CA, USA) following the manufacturer's specifications [15,16]. Primers for amplification and unextended mini-sequencing (UEP) are displayed in Supplementary Table 1. About 10% of samples were randomly regenotyped for quality control and the results were in 100% concordance.
Bioinformatics analysis
HaploReg v4.1 (https://pubs.broadinstitute.org/mammals/haploreg/haploreg.php) was used to predict the potential functions of the candidate SNPs. The association of these SNPs with the mRNA expression of GBAP1 in stomach tissue was evaluated using the GTEx Portal (https://gtexportal.org/home/).
Statistical analysis
The χ2 test or the Student's t-test was applied to compare the difference in characteristics between patients and controls. Hardy–Weinberg equilibrium (HWE) is a general and far-reaching principle in population genetics that is incorporated into a wide range of applications [17]. HWE testing is commonly used to detect genotyping errors in genetic association studies, and the genotype of all SNPs was consistent with HWE (p > 0.05), which indicated the subjects were representative of the population. The genotype frequencies of each SNP in controls were analyzed for HWE by χ2 test. The wild-type allele (rs140081212-G, rs1057941-A and rs2990220-A) was used as a reference, and the mutation-type allele (rs140081212-A, rs1057941-G and rs2990220-T) was used as a risk factor. Logistic regression analysis was used to test the association between GBAP1 polymorphisms and GC predisposition by calculating ORs and 95% CIs adjusted for age and sex. Stratification analysis was used to evaluate the heterogeneity of association between subgroups defined by age (>60 years and ≤60 years), sex (males and females), BMI (>24.99 kg/m2 and ≤24.99 kg/m2), smoking (yes and no) and drinking (yes and no) on GC predisposition. SPSS® 20.0 software (SPSS Inc., IL, USA) and PLINK 1.07 software [18] (http://softwaretopic.informer.com/plink-software/) were used for statistical analysis. False-positive report probability (FPRP) analysis was used to evaluate noteworthy associations of the significant findings. A 0.2 FPRP threshold and a prior probability of 0.1 were set for associations. A p-value <0.05 was regarded as statistically significant. Given the multiple testing, Bonferroni corrections should be applied for multiple comparisons of the gene model. In the study, three SNPs and five models were included, so the p-values were adjusted using Bonferroni correction; the statistical significance of the Bonferroni-corrected p-values was set at p < α/(no. SNPs × no. models), namely 0.05/(3 × 5).
Results
Participant characteristics
Demographic and clinicopathological characteristics including age, sex, BMI, smoking and drinking status, pathological type, lymph nodes metastasis and stage are displayed in Table 1. A total of 509 patients with GC (382 males and 127 females) and 507 healthy controls (379 males and 128 females) were recruited. The mean ages for cases and controls were 61.12 ± 11.33 years and 61.35 ± 8.84 years, respectively. No significant difference was found in age (p = 0.712) or sex (p = 0.942). However, significant differences (p = 0.001) were observed in BMI and smoking and drinking. The main type of GC was gastric adenocarcinoma (n = 314).
| Variable | Case (n = 509) | Control (n = 507) | p-value |
|---|---|---|---|
| Age, year (mean ± SD) | 61.12 ± 11.33 | 61.35 ± 8.84 | 0.712 |
| Gender, n Male Female | 382 127 | 379 128 | 0.942 |
| BMI, n >24.99 kg/m2 ≤24.99 kg/m2 Unavailable | 45 428 36 | 139 214 124 | <0.001 |
| Smoke, n Yes No Unavailable | 233 270 6 | 114 172 221 | <0.001 |
| Drink, n Yes No Unavailable | 133 357 29 | 119 142 246 | <0.001 |
| Pathological type, n Adenocarcinoma Other | 314 195 | – – | |
| Lymph nodes metastasis, n Yes No Unavailable | 235 97 177 | – – | |
| Stage, n I–II III–IV Unavailable | 109 239 161 | – – |
Association between GBAP1 polymorphisms & GC predisposition
Three SNPs (rs140081212, rs1057941 and rs2990220) within GBAP1 were genotyped and the call rate of genotyping was ≥99.8%. The MAF and HWE of the selected SNPs were greater than 0.05 (Supplementary Table 2). By HaploReg annotation, the selected SNPs were found to be associated with regulation of promoter and/or enhancer histone, DNase, motifs changed and selected eQTL hits. Based on the GTEx Portal database, the genotypes of rs140081212 (p = 6.0 × 10-16), rs1057941 (p = 6.0 × 10-12) and rs299022 (p = 2.0 × 10-22) were related to the mRNA expression of GBAP1 in stomach tissue (Supplementary Figure 1).
The genotypes and alleles frequency of GBAP1 polymorphisms in patients with GC and healthy controls are shown in Table 2. An association between decreased GC risk and these genetic polymorphisms and GC incidence was observed. For rs140081212, the significant relation was found under the allele (OR = 0.51, p = 4.50 × 10-07), genotype (OR = 0.51, p = 1.98 × 10-05), dominant (OR = 0.49, p = 1.99 × 10-06) and additive (OR = 0.53, p = 1.90 × 10-06) models. GBAP1 rs1057941 was significantly related to reduced GC risk with overall effects ranging from 0.23 to 0.52 under the allele (OR = 0.48, p = 1.19 × 10-08), genotype (AG vs AA, OR = 0.52, p = 2.09 × 10-05; GG vs AA, OR = 0.20, p = 4.23 × 10-04), dominant (OR = 0.48, p = 3.87 × 10-07), recessive (OR = 0.23, p = 0.001) and additive (OR = 0.50, p = 6.86 × 10-08) models. Rs2990220 also contributed to decreased GC risk under multiple genetic models (allele: OR = 0.46, p = 7.34 × 10-09; genotype: OR = 0.46, p = 9.59 × 10-07; dominant: OR = 0.43, p = 5.29 × 10-08; additive: OR = 0.47, p = 4.57 × 10-08).
| SNP ID | Model | Genotype | Control | Case | OR (95% CI) | p-value |
|---|---|---|---|---|---|---|
| rs140081212 | Allele | G | 836 | 919 | 1 | |
| A | 176 | 99 | 0.51 (0.39–0.67) | 4.50 × 10-07 | ||
| Genotype | GG | 350 | 418 | 1 | ||
| GA | 136 | 83 | 0.51 (0.38–0.70) | 1.98 × 10-05 | ||
| AA | 20 | 8 | 0.34 (0.15–0.77) | 0.010 | ||
| Dominant | GG | 350 | 418 | 1 | ||
| GA-AA | 156 | 91 | 0.49 (0.36–0.66) | 1.99 × 10-06 | ||
| Recessive | GG-GA | 486 | 501 | 1 | ||
| AA | 20 | 8 | 0.39 (0.17–0.89) | 0.025 | ||
| Log-additive | 0.53 (0.41–0.69) | 1.90 × 10-06 | ||||
| rs1057941 | Allele | A | 818 | 911 | 1 | |
| G | 196 | 105 | 0.48 (0.37–0.62) | 1.19 × 10-08 | ||
| Genotype | AA | 336 | 409 | 1 | ||
| AG | 146 | 93 | 0.52 (0.39–0.71) | 2.09 × 10-05 | ||
| GG | 25 | 6 | 0.20 (0.08–0.49) | 4.23 × 10-04 | ||
| Dominant | AA | 336 | 409 | 1 | ||
| AG-GG | 171 | 99 | 0.48 (0.36–0.63) | 3.87 × 10-07 | ||
| Recessive | AA-AG | 482 | 502 | 1 | ||
| GG | 25 | 6 | 0.23 (0.09–0.57) | 0.001 | ||
| Log-additive | 0.50 (0.39–0.64) | 6.86 × 10-08 | ||||
| rs2990220 | Allele | A | 833 | 928 | 1 | |
| T | 177 | 90 | 0.46 (0.35–0.60) | 7.34 × 10-09 | ||
| Genotype | AA | 347 | 425 | 1 | ||
| AT | 139 | 78 | 0.46 (0.34–0.63) | 9.59 × 10-07 | ||
| TT | 19 | 6 | 0.26 (0.10–0.65) | 0.004 | ||
| Dominant | AA | 347 | 425 | 1 | ||
| AT-TT | 158 | 84 | 0.43 (0.32–0.59) | 5.29 × 10-08 | ||
| Recessive | AA-AT | 486 | 503 | 1 | ||
| TT | 19 | 6 | 0.30 (0.12–0.77) | 0.012 | ||
| Log-additive | 0.47 (0.36–0.62) | 4.57 × 10-08 |
Association between GBAP1 polymorphisms & gastric cancer risk stratified by age, sex & BMI
The contributions of GBAP1 SNPs to GC risk stratified by age, sex and BMI were assessed and the results are shown in Table 3. Stratified by age, rs140081212, rs1057941 and rs2990220 variants were protective factors for GC susceptibility in subjects older than 60 years. Among the subjects aged ≤60 years, rs1057941 and rs2990220 were associated with reduced risk of GC occurrence.
| SNP | Model | Genotype | Age >60 years | Age ≤60 years | Male | Female | BMI >24.99 kg/m2 | BMI≤24.99 kg/m2 | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| OR (95% CI) | p-value | OR (95% CI) | p-value | OR (95% CI) | p-value | OR (95% CI) | p-value | OR (95% CI) | p-value | OR (95% CI) | p-value | |||
| rs140081212 | Allele | G | 1 | 1 | 1 | 1 | 1 | 1 | ||||||
| A | 0.46 (0.32–0.65) | 1.22 × 10-05 | 0.59 (0.39–0.87) | 0.008 | 0.56 (0.41–0.75) | 1.22 × 10-04 | 0.40 (0.23–0.69) | 6.31 × 10-04 | 0.28 (0.11–0.73) | 0.006 | 0.49 (0.35–0.68) | 2.43 × 10-05 | ||
| Genotype | GG | 1 | 1 | 1 | 1 | 1 | 1 | |||||||
| GA | 0.48 (0.32–0.74) | 6.84 × 10-04 | 0.55 (0.34–0.88) | 0.013 | 0.35 (0.14–0.87) | 0.023 | 0.36 (0.20–0.66) | 8.91 × 10-04 | 0.28 (0.10–0.79) | 0.016 | 0.49 (0.33–0.72) | 3.23 × 10-04 | ||
| AA | 0.20 (0.05–0.71) | 0.013 | 0.64 (0.19–2.17) | 0.474 | 0.58 (0.41–0.84) | 0.003 | 0.26 (0.03–2.54) | 0.246 | / | / | 0.24 (0.08–0.69) | 0.008 | ||
| Dominant | GG | 1 | 1 | 1 | 1 | 1 | 1 | |||||||
| GA-AA | 0.44 (0.30–0.66) | 7.47 × 10-05 | 0.56 (0.35–0.88) | 0.012 | 0.55 (0.39–0.77) | 5.50 × 10-04 | 0.35 (0.20–0.64) | 5.50 × 10-04 | 0.25 (0.09–0.70) | 0.008 | 0.46 (0.31–0.66) | 4.20 × 10-05 | ||
| Recessive | GG-GA | 1 | 1 | 1 | 1 | 1 | 1 | |||||||
| AA | 0.23 (0.06–0.82) | 0.024 | 0.73 (0.22–2.47) | 0.617 | 0.40 (0.16–0.97) | 0.042 | 0.33 (0.03–3.23) | 0.341 | / | / | 0.29 (0.10–0.82) | 0.020 | ||
| Log-additive | 0.47 (0.33–0.67) | 3.92 × 10-05 | 0.63 (0.42–0.93) | 0.020 | 0.59 (0.44–0.79) | 3.56 × 10-04 | 0.38 (0.22–0.67) | 7.29 × 10-04 | 0.26 (0.10–0.71) | 0.008 | 0.49 (0.35–0.68) | 1.95 × 10-05 | ||
| rs1057941 | Allele | A | 1 | 1 | 1 | 1 | 1 | 1 | ||||||
| G | 0.45 (0.32–0.63) | 3.17 × 10-06 | 0.52 (0.35–0.77) | 9.27 × 10-04 | 0.48 (0.36–0.65) | 7.60 × 10-07 | 0.48 (0.29–0.80) | 0.005 | 0.24 (0.09–0.63) | 0.002 | 0.49 (0.36–0.68) | 2.38 × 10-05 | ||
| Genotype | AA | 1 | 1 | 1 | 1 | 1 | 1 | |||||||
| AG | 0.50 (0.33–0.74) | 6.47 × 10-04 | 0.55 (0.35–0.88) | 0.012 | 0.19 (0.07–0.50) | 8.87 × 10-04 | 0.45 (0.25–0.80) | 0.007 | 0.28 (0.10–0.78) | 0.015 | 0.50 (0.34–0.73) | 3.91 × 10-04 | ||
| GG | 0.11 (0.02–0.48) | 0.004 | 0.33 (0.10–1.09) | 0.068 | 0.56 (0.39–0.79) | 9.23 × 10-04 | 0.27 (0.03–2.64) | 0.260 | / | / | 0.19 (0.06–0.59) | 0.004 | ||
| Dominant | AA | 1 | 1 | 1 | 1 | 1 | 1 | |||||||
| AG-GG | 0.44 (0.30–0.65) | 3.31 × 10-05 | 0.52 (0.33–0.81) | 0.004 | 0.49 (0.35–0.68) | 2.70 × 10-05 | 0.44 (0.25–0.77) | 0.004 | 0.24 (0.09–0.65) | 0.005 | 0.46 (0.32–0.67) | 4.20 × 10-05 | ||
| Recessive | AA-AG | 1 | 1 | 1 | 1 | 1 | 1 | |||||||
| GG | 0.13 (0.03–0.57) | 0.007 | 0.37 (0.11–1.25) | 0.110 | 0.22 (0.08–0.58) | 0.002 | 0.33 (0.03–3.23) | 0.341 | / | / | 0.23 (0.08–0.70) | 0.010 | ||
| Log-additive | 0.45 (0.32–0.64) | 6.78 × 10-06 | 0.56 (0.38–0.82) | 0.003 | 0.51 (0.38–0.68) | 4.46 × 10-06 | 0.46 (0.27–0.78) | 0.004 | 0.25 (0.10–0.66) | 0.005 | 0.48 (0.34–0.66) | 1.16 × 10-05 | ||
| rs2990220 | Allele | A | 1 | 1 | 1 | 1 | 1 | 1 | ||||||
| T | 0.40 (0.28–0.58) | 7.57 × 10-07 | 0.53 (0.35–0.79) | 0.002 | 0.45 (0.33–0.62) | 4.58 × 10-07 | 0.47 (0.27–0.80) | 0.005 | 0.16 (0.05–0.53) | 0.001 | 0.48 (0.34–0.66) | 2.71 × 10-05 | ||
| Genotype | AA | 1 | 1 | 1 | 1 | 1 | 1 | |||||||
| AT | 0.44 (0.29–0.67) | 1.56 × 10-04 | 0.47 (0.29–0.76) | 0.002 | 0.48 (0.33–0.69) | 7.12 × 10-05 | 0.41 (0.23–0.75) | 0.004 | 0.15 (0.04–0.54) | 0.003 | 0.47 (0.30–0.70) | 2.02 × 10-04 | ||
| TT | 0.07 (0.01–0.57) | 0.012 | 0.61 (0.18–2.05) | 0.421 | 0.24 (0.09–0.66) | 0.006 | 0.41 (0.04–4.55) | 0.464 | / | / | 0.22 (0.07–0.69) | 0.009 | ||
| Dominant | AA | 1 | 1 | 1 | 1 | 1 | 1 | |||||||
| AT-TT | 0.39 (0.26–0.59) | 9.81 × 10-06 | 0.49 (0.31–0.77) | 0.002 | 0.44 (0.31–0.63) | 4.64 × 10-06 | 0.41 (0.23–0.75) | 0.003 | 0.14 (0.04–0.48) | 0.002 | 0.44 (0.30–0.65) | 2.71 × 10-05 | ||
| Recessive | AA-AT | 1 | 1 | 1 | 1 | 1 | 1 | |||||||
| TT | 0.09 (0.01–0.67) | 0.019 | 0.72 (0.21–2.42) | 0.593 | 0.28 (0.10–0.77) | 0.013 | 0.50 (0.04–5.59) | 0.574 | / | / | 0.26 (0.08–0.70) | 0.021 | ||
| Log-additive | 0.40 (0.28–0.59) | 3.14 × 10-06 | 0.56 (0.38–0.84) | 0.005 | 0.48 (0.35–0.65) | 2.95 × 10-06 | 0.44 (0.25–0.78) | 0.004 | 0.15 (0.04–0.51) | 0.002 | 0.47 (0.34–0.0.66) | 1.25 × 10-05 | ||
Stratified by sex, associations between rs140081212, rs1057941 and rs2990220 and GC predisposition in males were found. Among females, rs140081212 was associated with decreased GC risk under multiple genetic models, and rs2990220 conferred reduced risk of GC. Among the subjects with BMI >24.99 kg/m2, the protective effect of rs1057941 and rs2990220 for GC predisposition was observed. In subjects with BMI ≤24.99 kg/m2, rs140081212, rs1057941 and rs2990220 were associated with reduced GC risk.
Association between GBAP1 polymorphisms & gastric cancer risk stratified by smoking & drinking
The association between GBAP1 polymorphisms and GC risk stratified by smoking and drinking was also evaluated (Table 4). SNPs rs140081212, rs1057941 and rs2990220 were associated with lower susceptibility to GC in smokers. Furthermore, GBAP1 polymorphisms were related to decreased risk of GC among nonsmokers. Among drinkers, rs1057941 and rs2990220 were found to be related to reduced risk of GC. Moreover, rs140081212, rs1057941 and rs2990220 had a protective effect against GC susceptibility in nondrinkers.
| SNP | Model | Genotype | Smokers | Nonsmokers | Drinkers | Nondrinkers | ||||
|---|---|---|---|---|---|---|---|---|---|---|
| OR (95% CI) | p | OR (95% CI) | p | OR (95% CI) | p | OR (95% CI) | p | |||
| rs140081212 | Allele | G | 1 | 1 | 1 | 1 | ||||
| A | 0.47 (0.30–0.74) | 0.001 | 0.53 (0.36–0.78) | 0.001 | 0.50 (0.29–0.86) | 0.012 | 0.50 (0.34–0.74) | 4.22 × 10-04 | ||
| Genotype | GG | 1 | 1 | 1 | 1 | |||||
| GA | 0.46 (0.26–0.82) | 0.008 | 0.60 (0.38–0.96) | 0.031 | 0.61 (0.32–1.16) | 0.128 | 0.45 (0.28–0.71) | 6.93 × 10-04 | ||
| AA | 0.38 (0.11–1.34) | 0.131 | 0.22 (0.06–0.85) | 0.028 | 0.12 (0.01–1.03) | 0.053 | 0.46 (0.14–1.49) | 0.194 | ||
| Dominant | GG | 1 | 1 | 1 | 1 | |||||
| GA-AA | 0.45 (0.26–0.77) | 0.004 | 0.54 (0.35–0.85) | 0.007 | 0.51 (0.28–0.95) | 0.034 | 0.45 (0.29–0.70) | 4.21 × 10-04 | ||
| Recessive | GG-GA | 1 | 1 | 1 | 1 | |||||
| AA | 0.44 (0.12–1.56) | 0.203 | 0.25 (0.06–0.95) | 0.042 | 0.13 (0.02–1.13) | 0.064 | 0.55 (0.17–1.78) | 0.320 | ||
| Log-additive | 0.52 (0.33–0.82) | 0.005 | 0.55 (0.38–0.82) | 0.003 | 0.51 (0.30–0.87) | 0.014 | 0.52 (0.36–0.77) | 8.86 × 10-04 | ||
| rs1057941 | Allele | A | 1 | 1 | 1 | 1 | ||||
| G | 0.36 (0.23–0.57) | 4.43 × 10-06 | 0.57 (0.39–0.83) | 0.003 | 0.41 (0.24–0.71) | 0.001 | 0.50 (0.34–0.73) | 2.36 × 10-04 | ||
| Genotype | AA | 1 | 1 | 1 | 1 | |||||
| AG | 0.40 (0.23–0.71) | 0.001 | 0.68 (0.43–1.07) | 0.093 | 0.59 (0.31–1.12) | 0.108 | 0.48 (0.31–0.76) | 0.002 | ||
| GG | 0.18 (0.05–0.60) | 0.006 | 0.15 (0.03–0.71) | 0.017 | / | / | 0.32 (0.10–1.02) | 0.054 | ||
| Dominant | AA | 1 | 1 | 1 | 1 | |||||
| AG-GG | 0.36 (0.21–0.60) | 1.15 × 10-04 | 0.60 (0.39–0.93) | 0.023 | 0.45 (0.25–0.84) | 0.011 | 0.47 (0.30–0.72) | 5.24 × 10-04 | ||
| Recessive | AA-AG | 1 | 1 | 1 | 1 | |||||
| GG | 0.22 (0.06–0.73) | 0.014 | 0.16 (0.03–0.77) | 0.023 | / | / | 0.38 (0.12–1.22) | 0.105 | ||
| Log-additive | 0.41 (0.27–0.64) | 6.63 × 10-05 | 0.58 (0.40–0.86) | 0.006 | 0.43 (0.25–0.73) | 0.002 | 0.51 (0.35–0.75) | 4.73 × 10-04 | ||
| rs2990220 | Allele | A | 1 | 1 | 1 | 1 | ||||
| T | 0.35 (0.22–0.55) | 4.06 × 10-06 | 0.53 (0.36–0.80) | 0.002 | 0.44 (0.25–0.77) | 0.003 | 0.47 (0.31–0.70) | 1.62 × 10-04 | ||
| Genotype | AA | 1 | 1 | 1 | 1 | |||||
| AT | 0.34 (0.19–0.60) | 2.31 × 10-04 | 0.59 (0.37–0.93) | 0.025 | 0.51 (0.27–0.97) | 0.041 | 0.43 (0.27–0.68) | 3.80 × 10-04 | ||
| TT | 0.23 (0.06–0.85) | 0.027 | 0.20 (0.04–0.99) | 0.049 | 0.12 (0.01–0.98) | 0.048 | 0.40 (0.10–1.52) | 0.177 | ||
| Dominant | AA | 1 | 1 | 1 | 1 | |||||
| AT-TT | 0.32 (0.19–0.55) | 4.16 × 10-05 | 0.54 (0.35–0.85) | 0.008 | 0.44 (0.24–0.82) | 0.009 | 0.42 (0.27–0.67) | 2.12 × 10-04 | ||
| Recessive | AA-AT | 1 | 1 | 1 | 1 | |||||
| TT | 0.29 (0.08–1.05) | 0.059 | 0.22 (0.04–1.12) | 0.068 | 0.13 (0.02–1.12) | 0.063 | 0.48 (0.13–1.82) | 0.281 | ||
| Log-additive | 0.39 (0.25–0.62) | 6.99 × 10-05 | 0.55 (0.36–0.82) | 0.004 | 0.45 (0.26–0.78) | 0.004 | 0.48 (0.32–0.72) | 3.79 × 10-04 | ||
Association between GBAP1 polymorphisms & gastric adenocarcinoma risk
SNPs rs140081212, rs1057941 and rs2990220 were associated with decreasing risk of gastric adenocarcinoma under multiple genetic models (Table 5). For rs140081212, A allele, GA genotype and GA-AA genotype were identified with reduced risk of gastric adenocarcinoma. The protective effect of rs1057941 for the predisposition to gastric adenocarcinoma was observed under the allele, genotype, dominant and additive models. For rs2990220, T allele, AT genotype and AT-TT genotype were significantly connected with reduced risk of gastric adenocarcinoma.
| SNP ID | Model | Genotype | Control | Case | OR (95% CI) | p-value |
|---|---|---|---|---|---|---|
| rs140081212 | Allele | G | 836 | 572 | 1 | |
| A | 176 | 56 | 0.47 (0.34–0.64) | 1.70 × 10-06 | ||
| Genotype | GG | 350 | 264 | 1 | ||
| GA | 136 | 44 | 0.43 (0.30–0.63) | 1.20 × 10-05 | ||
| AA | 20 | 6 | 0.39 (0.16–0.99) | 0.049 | ||
| Dominant | GG | 350 | 264 | 1 | ||
| GA-AA | 156 | 50 | 0.43 (0.30–0.61) | 2.85 × 10-06 | ||
| Recessive | GG-GA | 486 | 308 | 1 | ||
| AA | 20 | 6 | 0.47 (0.18–1.17) | 0.105 | ||
| Log-additive | 0.49 (0.36–0.67) | 8.43 × 10-06 | ||||
| rs1057941 | Allele | A | 818 | 568 | 1 | |
| G | 196 | 58 | 0.43 (0.31–0.58) | 4.43 × 10-08 | ||
| Genotype | AA | 336 | 258 | 1 | ||
| AG | 146 | 52 | 0.47 (0.33–0.67) | 2.66 × 10-05 | ||
| GG | 25 | 3 | 0.15 (0.05–0.52) | 0.002 | ||
| Dominant | AA | 336 | 258 | 1 | ||
| AG-GG | 171 | 55 | 0.42 (0.30–0.59) | 7.94 × 10-07 | ||
| Recessive | AA-AG | 482 | 310 | 1 | ||
| GG | 25 | 3 | 0.18 (0.05–0.61) | 0.006 | ||
| Log-additive | 0.45 (0.33–0.61) | 2.91 × 10-07 | ||||
| rs2990220 | Allele | A | 833 | 575 | 1 | |
| T | 177 | 53 | 0.43 (0.31–0.60) | 2.66 × 10-07 | ||
| Genotype | AA | 347 | 265 | 1 | ||
| AT | 139 | 45 | 0.43 (0.29–0.62) | 7.14 × 10-06 | ||
| TT | 19 | 4 | 0.27 (0.09–0.80) | 0.019 | ||
| Dominant | AA | 347 | 265 | 1 | ||
| AT-TT | 158 | 49 | 0.41 (0.28–0.58) | 8.64 × 10-07 | ||
| Recessive | AA-AT | 486 | 310 | 1 | ||
| TT | 19 | 4 | 0.32 (0.11–0.95) | 0.041 | ||
| Log-additive | 0.45 (0.33–0.62) | 1.23 × 10-06 |
Association between GBAP1 polymorphisms & GC clinicopathologic indicators
The association between GBAP1 polymorphisms and GC clinicopathologic indicators was assessed. However, there was no significant association of GBAP1 variants with lymph node metastasis or stage of patients with GC (p > 0.05, Supplementary Table 3).
False-positive report probability analysis
FPRP analysis was carried out to interrogate whether statistically significant findings were deserving of attention (Supplementary Table 4). At the prior probability level of 0.1, the significant association for rs140081212, rs1057941 and rs2990220 remained noteworthy in the overall analysis. In the subgroup aged >60 years, significant findings remained noteworthy for rs1057941 (FPRP = 0.152) and rs2990220 (FPRP = 0.183). In males and the subjects with BMI ≤24.99 kg/m2, significant findings remained noteworthy for rs140081212, rs1057941 and rs2990220. Moreover, the associations of rs140081212, rs1057941 and rs2990220 with the risk of gastric adenocarcinoma were also positive at the prior probability level of 0.1.
Discussion
GC is a multifactorial disease and its occurrence and development are caused by the interaction of genetic, environmental and lifestyle factors [19]. In this study, GBAP1 polymorphisms (rs140081212, rs1057941 and rs2990220) were found to contribute to the reduced risk of GC incidence among a Chinese Han population. Interestingly, the contribution of GBAP1 genetic variants to GC susceptibility was associated with age, sex, BMI and the status of smoking and drinking. Variants rs140081212, rs1057941 and rs2990220 were related to decreasing risk of gastric adenocarcinoma.
GBAP1 could act as ceRNA, regulating the expression of GBA via miRNA [11]. GBA inhibition suppressed GC growth and survival and sensitized GC to chemotherapy [20]. The overexpression of GBAP1 caused increased GBA expression in the GC cells by absorbing the miR-212-3p in GC [21]. This study is the first to report that rs140081212, rs1057941 and rs2990220 variants in GBAP1 are protective factors for GC susceptibility. However, the potential functions of these variants have not been reported. The HaploReg v4.1 database [22] indicated that these SNPs were associated with the regulation of promoter/enhancer histones, DNAse, changed motifs and/or selected eQTL hits. Based on the GTEx Portal database, the genotypes of rs140081212, rs1057941 and rs299022 were related to the mRNA expression of GBAP1 in stomach tissue. We speculated that the GBAP1 mutation might modify its expression level, which could dramatically affect the downstream regulation of GBA expression and lead to pathological alterations in GC. The exact mechanism of these influences needs further study. Based on the LDproxy tool (https://ldlink.nci.nih.gov/), rs2990220 is in high linkage disequilibrium (LD) with rs4072037, an SNP in the MUC1 gene known to be associated with GC in a GWAS study [23]. LD is a nonrandom allele association and is generated by mutation and recombination. If there is LD between SNPs (r2 >0.8), these SNPs can form an LD block that tends to be passed on to offspring. Functional studies have shown that rs4072037 regulates alternative splicing of the second exon and modifies the transcriptional activity of the MUC1 promoter [24]. Similarly, rs1057941 is in high LD with rs2070803, an SNP in the MUC1 gene known to be associated with GC [25]. The GTEx Portal database indicated that the genotype of rs299022 and rs1057941 was related to MUC1 expression in various tissues but not in stomach tissue. Whether this association of rs299022 and rs1057941 with GC risk is due to dysregulation of GBAP1 or alterations in MUC1 needs to be further explored.
Sex and age are important risk factors that affect GC development. The death rate of GC increases with age [26]. After Bonferroni correction, rs140081212 remained related to reduced GC risk in subjects >60 years, but not in subjects aged ≤60 years. The sex-specific incidence of GC showed an increasing trend, with male-to-female ratios of age-standardized incidence rate rising from 1.86–2.20 [27]. Rs1057941 was associated with decreased GC risk under multiple genetic models among males but not in females. Similarly, many previous studies have also shown that age and sex influence the relation of genetic variants to GC risk [28,29]. High BMI has been suggested as a risk factor for gastric cardia adenocarcinomas [30]. Although the protective effect of GBAP1 polymorphisms for GC predisposition was observed among subjects with BMI >24.99 kg/m2 and BMI ≤24.99 kg/m2, the significance in subjects with BMI ≤24.99 kg/m2 was higher than that in subjects with BMI >24.99 kg/m2. These results suggest that the effect of GBAP1 polymorphisms on GC risk might be confounded by age, sex and BMI.
Other factors affecting GC include lifestyle habits and environmental factors, including tobacco use and alcohol consumption. Smoking and drinking exposure are associated with an increased risk for upper gastrointestinal tract cancers [31]. In the present study, similar results were reported in smokers and nonsmokers but the significance was different between the two groups. Moreover, rs140081212 was related to reduced GC risk in nondrinkers, but not in drinkers. These results suggest a gene–environmental interaction between smoking/drinking and the GBAP1 gene in gastric carcinogenesis. However, a specific mechanism is needed for further study.
This study has some limitations. First, the subjects were from a small single center, therefore, selection bias was inevitable. Second, the detailed mechanisms of GBAP1 variants in the pathogenesis of GC were not investigated. Third, all participants were of the Chinese Han population, so the results are not representative of other ethnic groups. These results should be cautiously interpreted and further studies performed on a larger scale are needed to confirm these findings.
Conclusion
The present study results revealed GBAP1 polymorphisms (rs140081212, rs1057941 and rs2990220) that might provide a protective effect against GC occurrence among a Chinese Han population. The findings might contribute to the increased understanding of molecular genetics in gastric carcinogenesis.
In this study, GBAP1 polymorphisms (rs140081212, rs1057941 and rs2990220) were found to contribute to reduced risk of gastric cancer (GC) incidence among a Chinese Han population.
Interestingly, the contribution of GBAP1 genetic variants to GC susceptibility was associated with age, sex, BMI and the status of smoking and drinking.
Variants rs140081212, rs1057941 and rs2990220 were related to decreasing risk of gastric adenocarcinoma.
At the prior probability level of 0.1, the significant association for rs140081212, rs1057941 and rs2990220 remained noteworthy in the overall analysis.
The effect of GBAP1 polymorphisms on GC risk might be confounded by age, sex and BMI.
These results revealed a gene–environment interaction between smoking/drinking and the GBAP1 gene on gastric carcinogenesis.
These findings might increase the understanding of molecular genetics in gastric carcinogenesis.
Based on the GTEx Portal database, the genotypes of rs140081212, rs1057941 and rs299022 were related to the mRNA expression of GBAP1 in stomach tissue.
Supplementary data
To view the supplementary data that accompany this paper please visit the journal website at: www.futuremedicine.com/doi/suppl/10.2217/fon-2021-0973
Author contributions
X Duan and L Shan: writing and conceptualization; S Shi, B Xu and X Chen: methodology; J Di and B Chen: Data curation; X Li and S Liu: conceptualization.
Acknowledgments
The authors thank all participants and volunteers in this study.
Financial & competing interests disclosure
This study is supported by National Natural Science Foundation of China (81760441), the Key Research and Development Program of Shaanxi Province (2019KW-019, 2019ZDLSF02-09-01 and 2020GXLH-Y-019), Innovation Capability Support Program of Shaanxi Province (2019GHJD-14) and Scientific Research Program Funded by Shaanxi Provincial Education Department (18JC027). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.
No writing assistance was utilized in the production of this manuscript.
Ethical conduct of research
This study was approved by the institutional review boards of the Affiliated Hospital of Xizang Minzu University (no. 2017010) and was in accordance with the World Medical Association Declaration of Helsinki. All participants signed written informed consent.
Open access
This work is licensed under the Attribution-NonCommercial-NoDerivatives 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/
Papers of special note have been highlighted as: • of interest; •• of considerable interest
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