Background: Although several studies have investigated the association between ABO blood type and risk of gastric cancer (GC), atrophic gastritis (AG), and Helicobacter pylori (HP) infection, no study has investigated these associations by using ABO genotype.

Methods: We conducted a case–control study in 703 patients with GC and 1,465 noncancer patients. We also conducted a cross-sectional study by using 1,406 of these 1,465 controls, who were examined for pepsinogens and anti-HP IgG antibody levels in serum. ABO genotype was determined from single nucleotide polymorphisms in ABO gene. We used rs8176719 to mark the O allele, and rs8176746 and rs8176747 to mark the B allele. ORs and 95% CIs were calculated by a multivariate logistic model.

Results: We observed significant associations between ABO genotype and GC, AG, and HP infection. ORs (95% CIs) of GC were 0.70 (0.50–0.99) for OO and 0.53 (0.36–0.77) for BO relative to AA genotype. An increased risk of GC was observed with addition of the A allele (Ptrend < 0.001), and a decreased risk with that of the B allele (Ptrend = 0.023). An OR of AG was 0.73 (95% CI, 0.53–0.99) for blood type B relative to blood type A, and an OR of HP infection was 0.39 (95% CI, 0.17–0.87) for BB relative to AA genotype.

Conclusion: This study identified a statistically significant association between ABO genotype and GC risk. In addition, ABO gene locus may influence AG prevalence and HP infection.

Impact: Further studies are necessary to confirm these findings. Cancer Epidemiol Biomarkers Prev; 20(8); 1665–72. ©2011 AACR.

This article is featured in Highlights of This Issue, p. 1565

Although the age-standardized incidence of gastric cancer (GC) in Japan is decreasing, it remains one of the most common cancers (1). Worldwide, GC is still the fourth most common cancer and the second most common cause of cancer death (2, 3). Although the major risk factors of GC have been established, specifically Helicobacter pylori (HP) infection, male sex, family history of GC, and smoking (3), epidemiologic studies to explore GC risk still play an important role in identifying GC high-risk groups and ultimately in decreasing the number of GC deaths.

A recent large prospective cohort study identified a statistically significant association between ABO blood type and the risk of GC in a Western population (4). Although the association between ABO blood type and GC risk has been investigated for more than half a century, results have been somewhat conflicting (5–9). Meanwhile, although several studies have used single nucleotide polymorphisms (SNP) within the ABO gene locus to show a statistically significant association between ABO genotype and risk of pancreatic cancer (10–12), previous studies of the association between GC risk and ABO blood type have used serotype-derived ABO blood type, and not ABO genotype.

Here, we conducted a case–control study to assess the impact of ABO genotype on the risk of GC among a Japanese population. In addition, because HP infection is a well-established risk factor for GC and the inflammation caused by HP infection is thought to cause atrophic gastritis (AG) and GC (13–16), we also assessed the difference among ABO genotypes in AG prevalence and HP infection.

Study population

Cases comprised 703 GC patients with no prior history of cancer who were diagnosed at Aichi Cancer Center Hospital (ACCH), Nagoya, Japan, between January 2001 and November 2005. Control subjects comprised 1,465 randomly selected noncancer outpatient visitors to ACCH during the same period who had no history of any cancer. All subjects making their first visit to ACCH between January 2001 and November 2005 were enrolled at first visit in the Hospital-based Epidemiological Research Program II at ACCH (HERPACC-II). The framework of HERPACC-II has been described elsewhere (17, 18). Briefly, all first-visit outpatients at ACCH ages 20 to 79 years are asked to fill out a self-administered questionnaire regarding their lifestyle before development of the current symptoms. Responses are checked by trained interviewers. Outpatients are also asked to provide a 7-mL blood sample. Approximately 95% of eligible subjects complete the questionnaire and 50% provide blood samples. All data are loaded into the HERPACC database, which is periodically synchronized with the hospital cancer registry system to update the data on cancer incidence. Approximately 35% of subjects (46% of male subjects and 28% of female subjects) were diagnosed with cancer within a year of first visit. In this study, we defined patients diagnosed with GC within a year of first visit as the case population. Among cases, histologic information was available for 98.15% (310 cases, intestinal type; 380 cases, diffuse type; and 13 cases, unknown). Our previous study showed that the lifestyle patterns of first-visit outpatients at ACCH corresponded with those of individuals randomly selected from Nagoya's general population, confirming external validity for the study (19). This study was approved by the Ethics Committee of Aichi Cancer Center and informed consent to participate was obtained at first visit from all participants.

Selection and genotyping of ABO blood group allele

In this study, we examined 3 loci on the ABO gene, rs8176719, rs8176746, and rs8176747. Those loci are responsible for the ABO blood group phenotype in the Japanese population. Examination of the cDNA nucleotide sequence of the ABO gene on chromosome 9q34.2 revealed the following for the Japanese population: a 261G deletion in exon 6 (rs8176719) results in the O allele, and C796A and G803C in exon 7 (rs8176746 and rs8176747, respectively) distinguish the B allele from A allele (20–23). DNA of each subject was extracted from the buffy-coat fraction by using the DNA Blood Mini Kit (Qiagen). All loci were examined by TaqMan assays (Applied Biosystems). The principle of the TaqMan real-time PCR assay system using fluorogenic probes and 5′ nuclease has been described by Livak (24). Custom probes and primers were specifically designed for the 3′ loci. Genotyping for the ABO 261G deletion (rs8176719) was done by PCR with 5′-CCTGTGTGGATGTGCAGTAGGA-3′ and 5′-CGTTGAGGATGTCGATGTTGAA-3′ primers, and Fam-TCCTCGTGGTGACCCCTTGGC-TAMRA and Vic-ATGTCCTCGTGGTACCCCTTGGCT-TAMRA probes (21). Genotyping for the ABO C796A and G803C (rs876746 and rs876747, respectively) was done by PCR with 5′-CTGCACCTCTTGCACCGAC-3′ and 5′-AGGCCTTCACCTACGAGCG-3′ primers, and Fam-CCCGAAGAACCCCCCCAGGTAGTAGAAA-TAMRA and Vic-CCCGAAGAACGCCCCCATGTAGTAGAAA-TAMRA probes (21). All of the assays were carried out in 96-well PCR plates by using a 7500 Fast Real-time PCR System with the corresponding 7500 Fast System SDS software (Applied Biosystems). Amplification reactions were done in duplicate with 30 ng (5 μL) of template DNA, 2× TaqMan Universal Master Mix buffer (Applied Biosystems), and 20× primer and probe mix (Applied Biosystems). Thermal cycling was carried out under the following conditions: denaturation at 95°C for 20 seconds followed by 40 cycles of 95°C for 3 seconds and 62°C for 30 seconds. In our laboratory, the quality of genotyping is routinely statistically assessed by using the Hardy–Weinberg test and retyping of a random sampling of 5% of subjects. We also confirmed that there were no allelic distributions among the controls that departed from the Hardy–Weinberg frequency.

AG and HP infection assessment

Among the 1,465 controls, 1,406 were available for measurement of serum pepsinogens and IgG levels for HP. Serum pepsinogens (PG) were measured by chemiluminescence enzyme immunoassay, and gastric mucosal atrophy was defined by a PG I value of 70 ng/mL or less and PG I/PG II ≤ 3 (13, 25). Serum IgG levels for HP were measured by a commercially available direct ELISA kit (“E Plate ‘Eiken’ HP Antibody” Eiken Kagaku). This ELISA kit was developed in Japan by using the antigen extracted from a domestic strain in Japan and is commonly used in medical studies (26, 27). Positivity for HP infection was defined as an anti-HP IgG antibody level greater than 10 U/mL in serum.

Assessment of lifestyle exposures

Exposure to potential GC risk factors was assessed from the self-administered questionnaire results, which were completed before diagnosis during the first visit to ACCH and reviewed by trained interviewers. Subjects were specifically questioned about their lifestyle before the onset of the symptoms which impelled their visit to ACCH. Daily alcohol consumption in grams was determined by summing the pure alcohol amount in the average daily consumption of Japanese sake (rice wine), shochu (distilled spirit), beer, wine and whiskey, with 1 cup of Japanese sake (180 mL) considered equivalent to 23 g of ethanol, 1 drink of shochu (108 mL) to 23 g, 1 large bottle of beer (633 mL) to 23g, 1 glass of wine (80 mL) to 10 g, and 1 shot of whiskey (28.5 mL) to 11.5 g. Cumulative smoking exposure was measured in pack-years, the product of the average number of packs per day and the number of years of smoking. Family history of GC was considered positive when at least one parent or sibling had a history of GC.

Statistical analysis

All statistical analyses were carried out by Stata version 10 (Stata Corp.). P < 0.05 was considered statistically significant. Differences in characteristics between cases and controls were assessed by the χ2 test. ORs and 95% CIs were estimated by using an unconditional logistic regression model adjusted for potential confounders. Potential confounders considered in multivariate analysis were age, sex, pack-years of smoking (<5, <20, <40, or ≥41), drinking habit (nondrinker, <23, <46, or ≥46 g/day), and family history of GC (yes or no). Accordance with Hardy–Weinberg equilibrium was assessed by the χ2 test.

Background characteristics of GC cases and controls are shown in Table 1. Patients with GC had a significantly higher ratio of heavy smokers (P < 0.001) and heavy drinkers (P = 0.002), and a marginally higher ratio of a family history of GC (P = 0.051). Characteristics of the 1,406 participants examined for serum anti-HP IgG antibody and pepsinogens levels were closely similar to those of the total 1,465 noncancer participants (Table 2). High age, male sex, and heavy smoking were more common in HP-positive than -negative patients, whereas high age and HP infection were more common in AG-positive than -negative patients.

Table 1.

Characteristics of GC case and control

Case (%); n = 703Control (%); n = 1,465Pa
Age    
 <40 34 (4.84) 75 (5.12) 0.759 
 ≥40 but <50 72 (10.24) 147 (10.03)  
 ≥50 but <60 246 (34.99) 479 (32.70)  
 ≥60 but <70 214 (30.44) 484 (33.04)  
 ≥70 137 (19.49) 280 19.11)  
Sex    
 Male 527 (74.96) 1,097 (74.88) 0.966 
 Female 176 (25.04) 368 (25.12)  
Cigarette pack-years    
 <5 239 (34.00) 638 (43.55) <0.001 
 ≥5 but <20 84 (11.95) 206 14.06)  
 ≥20 but <40 160 (22.76) 308 (21.02)  
 ≥40 213 (30.30) 304 (20.75)  
 Unknown 7 (1.00) 9 (0.61)  
Drinking, g ethanol/day    
 Nondrinking 229 (32.57) 488 (33.31) 0.002 
 <23 169 (24.04) 425 (29.01)  
 ≥23 but <46 160 (22.76) 342 (23.34)  
 ≥46 134 (19.06) 193 (13.17)  
 Unknown 11 (1.56) 17 (1.16)  
Family history of GC    
 No 548 (77.95) 1,190 (81.23) 0.051 
 Yes 155 (22.05) 270 (18.43)  
 Unknown 0 (0.00) 5 (0.34)  
Case (%); n = 703Control (%); n = 1,465Pa
Age    
 <40 34 (4.84) 75 (5.12) 0.759 
 ≥40 but <50 72 (10.24) 147 (10.03)  
 ≥50 but <60 246 (34.99) 479 (32.70)  
 ≥60 but <70 214 (30.44) 484 (33.04)  
 ≥70 137 (19.49) 280 19.11)  
Sex    
 Male 527 (74.96) 1,097 (74.88) 0.966 
 Female 176 (25.04) 368 (25.12)  
Cigarette pack-years    
 <5 239 (34.00) 638 (43.55) <0.001 
 ≥5 but <20 84 (11.95) 206 14.06)  
 ≥20 but <40 160 (22.76) 308 (21.02)  
 ≥40 213 (30.30) 304 (20.75)  
 Unknown 7 (1.00) 9 (0.61)  
Drinking, g ethanol/day    
 Nondrinking 229 (32.57) 488 (33.31) 0.002 
 <23 169 (24.04) 425 (29.01)  
 ≥23 but <46 160 (22.76) 342 (23.34)  
 ≥46 134 (19.06) 193 (13.17)  
 Unknown 11 (1.56) 17 (1.16)  
Family history of GC    
 No 548 (77.95) 1,190 (81.23) 0.051 
 Yes 155 (22.05) 270 (18.43)  
 Unknown 0 (0.00) 5 (0.34)  

aχ2 test.

Table 2.

Characteristics of noncancer 1,406 participants according to HP infection status and AG status

Serum pepsinogens and anti-HP IgG antibody measurable participants (%); n = 1,406HP-positive (%); n = 798HP-negative (%), n = 608PaAG case (%); n = 496AG-negative (%); n = 910Pa
Age        
 <40 74 (5.26) 18 (2.26) 56 (9.21) <0.001 4 (0.81) 70 (7.69) <0.001 
 ≥40 but <50 142 (10.10) 52 (6.52) 90 (14.80)  18 (3.63) 124 (13.63)  
 ≥50 but <60 466 (33.14) 273 (34.21) 193 (31.74)  144 (29.03) 322 (35.38)  
 ≥60 but <70 460 (32.72) 292 (36.59) 168 (27.63)  194 (39.11) 266 (29.23)  
 ≥70 264 (18.78) 163 (20.43) 101 (16.61)  136 (27.42) 128 (14.07)  
Sex        
 Male 1,062 (75.53) 628 (78.70) 434 (71.38) 0.002 388 (78.23) 674 (74.07) 0.083 
 Female 344 (24.47) 170 (21.30) 174 (28.62)  108 (21.77) 236 (25.93)  
Cigarette pack-years        
 <5 605 (43.03) 321 (40.23) 284 (46.71) 0.004 209 (42.14) 396 (43.52) 0.258 
 ≥5 but <20 200 (14.22) 108 (13.53) 92 (15.13)  69 (13.91) 131 (14.40)  
 ≥20 but <40 301 (21.41) 175 (21.93) 126 (20.72)  99 (19.96) 202 (22.20)  
 ≥40 291 (20.70) 191 (23.93) 100 (16.45)  117 (23.59) 174 (19.12)  
 Unknown 9 (0.64) 3 (0.38) 6 (0.99)  2 (0.40) 7 (0.77)  
Drinking, g ethanol/day        
 Nondrinking 457 (32.50) 255 (31.95) 202 (33.22) 0.321 162 (32.66) 295 (32.42) 0.762 
 <23 416 (29.59) 227 (28.45) 189 (31.09)  139 (28.02) 277 (30.44)  
 ≥23 but <46 330 (23.47) 189 (23.68) 141 (23.19)  119 (23.99) 211 (23.19)  
 ≥46 189 (13.44) 118 (14.79) 71 (11.68)  71 (14.31) 118 (12.97)  
 Unknown 14 (1.00) 9 (1.13) 5 (0.82)  5 (1.01) 9 (0.99)  
Family history of GC        
 No 1,146 (81.51) 643 (80.58) 503 (82.73) 0.245 394 (79.44) 752 (82.64) 0.118 
 Yes 258 (18.35) 155 (19.42) 103 (16.94)  102 (20.56) 156 (17.14)  
 Unknown 2 (0.14) 0 (0.00) 2 (0.33)  0 (0.00) 2 (0.22)  
HP    < 0.001   
 Positive 798 (56.76)    448 (90.32) 350 (38.46) <0.001 
 Negative 608 (43.24)    48 (9.68) 560 (61.54)  
Serum pepsinogens and anti-HP IgG antibody measurable participants (%); n = 1,406HP-positive (%); n = 798HP-negative (%), n = 608PaAG case (%); n = 496AG-negative (%); n = 910Pa
Age        
 <40 74 (5.26) 18 (2.26) 56 (9.21) <0.001 4 (0.81) 70 (7.69) <0.001 
 ≥40 but <50 142 (10.10) 52 (6.52) 90 (14.80)  18 (3.63) 124 (13.63)  
 ≥50 but <60 466 (33.14) 273 (34.21) 193 (31.74)  144 (29.03) 322 (35.38)  
 ≥60 but <70 460 (32.72) 292 (36.59) 168 (27.63)  194 (39.11) 266 (29.23)  
 ≥70 264 (18.78) 163 (20.43) 101 (16.61)  136 (27.42) 128 (14.07)  
Sex        
 Male 1,062 (75.53) 628 (78.70) 434 (71.38) 0.002 388 (78.23) 674 (74.07) 0.083 
 Female 344 (24.47) 170 (21.30) 174 (28.62)  108 (21.77) 236 (25.93)  
Cigarette pack-years        
 <5 605 (43.03) 321 (40.23) 284 (46.71) 0.004 209 (42.14) 396 (43.52) 0.258 
 ≥5 but <20 200 (14.22) 108 (13.53) 92 (15.13)  69 (13.91) 131 (14.40)  
 ≥20 but <40 301 (21.41) 175 (21.93) 126 (20.72)  99 (19.96) 202 (22.20)  
 ≥40 291 (20.70) 191 (23.93) 100 (16.45)  117 (23.59) 174 (19.12)  
 Unknown 9 (0.64) 3 (0.38) 6 (0.99)  2 (0.40) 7 (0.77)  
Drinking, g ethanol/day        
 Nondrinking 457 (32.50) 255 (31.95) 202 (33.22) 0.321 162 (32.66) 295 (32.42) 0.762 
 <23 416 (29.59) 227 (28.45) 189 (31.09)  139 (28.02) 277 (30.44)  
 ≥23 but <46 330 (23.47) 189 (23.68) 141 (23.19)  119 (23.99) 211 (23.19)  
 ≥46 189 (13.44) 118 (14.79) 71 (11.68)  71 (14.31) 118 (12.97)  
 Unknown 14 (1.00) 9 (1.13) 5 (0.82)  5 (1.01) 9 (0.99)  
Family history of GC        
 No 1,146 (81.51) 643 (80.58) 503 (82.73) 0.245 394 (79.44) 752 (82.64) 0.118 
 Yes 258 (18.35) 155 (19.42) 103 (16.94)  102 (20.56) 156 (17.14)  
 Unknown 2 (0.14) 0 (0.00) 2 (0.33)  0 (0.00) 2 (0.22)  
HP    < 0.001   
 Positive 798 (56.76)    448 (90.32) 350 (38.46) <0.001 
 Negative 608 (43.24)    48 (9.68) 560 (61.54)  

aχ2 test.

Using rs8176719 as a marker for the O allele, and rs8176746 and rs8176747 for the B allele, all participants' 2 ABO alleles were inferred. Allele frequencies of the O, A, and B allele among the noncancer control subjects were 54.64%, 28.33%, and 17.03%, respectively. These frequencies were consistent with information from the HapMap project and previous studies (22, 23, 28).

We assessed the risk of GC according to ABO blood type and ABO genotype among all study participants (Tables 3 and 4). In addition, we also assessed the risk of AG prevalence and HP infection according to ABO blood type and ABO genotype among the 1,406 noncancer participants. Compared with individuals with blood type A, those with blood type B were at lower risk of GC (OR = 0.60; CI, 0.46–0.78) and AG (OR = 0.73; CI, 0.53–0.99). In genotype analysis, ORs of GC relative to that of AA were 0.85 (CI, 0.60–1.18) for AO, 0.70 (CI, 0.50–0.99) for OO, 0.91 (CI, 0.61–1.37) for AB, 0.53 (CI, 0.36–0.77) for BO, and 0.48 (CI, 0.23–1.02) for BB. In addition, compared with individuals with the AA genotype, those with the BB genotype were at lower risk of HP infection (OR = 0.39, CI = 0.17–0.87).

Table 3.

Age- and sex-adjusted, and multivariable-adjusted ORs (95% CIs) for incident GC HP infection and AG by genotype-derived ABO blood type

AOABB
GC     
 No. of cases (%)/controls (%) 319 (45.4)/572 (39.0) 194 (27.6)/428 (29.2) 81 (11.5)/141 (9.6) 109 (15.5)/324 (22.1) 
 Age- and sex-adjusted OR 1 (ref.) 0.81 (0.65–1.01) 1.03 (0.76–1.40) 0.60 (0.47–0.78) 
 Multivariable-adjusted ORa 1 (ref.) 0.80 (0.64–1.00) 1.4 (0.76–1.42) 0.60 (0.46–0.78) 
AG     
 No. of cases (%)/controls (%) 211 (42.5)/341 (37.5) 141 (28.4)/270 (29.7) 45 (9.1)/88 (9.7) 99 (20.0)/211 (23.2) 
 Age- and sex-adjusted OR 1 (ref.) 0.86 (0.65–1.13) 0.83 (0.55–1.26) 0.73 (0.54–0.99) 
 Multivariable-adjusted ORa 1 (ref.) 0.87 (0.66–1.14) 0.84 (0.55–1.27) 0.73 (0.53–0.99) 
HP     
 No. of cases (%)/controls (%) 318 (39.9)/234 (38.5) 241 (30.2)/170 (28.0) 70 (8.8)/63 (10.4) 169 (21.2)/141 (23.2) 
 Age- and sex-adjusted OR 1 (ref.) 1.09 (0.84–1.42) 0.83 (0.56–1.23) 0.88 (0.66–1.17) 
 Multivariable-adjusted ORa 1 (ref.) 1.11 (0.85–1.45) 0.84 (0.57–1.24) 0.89 (0.67–1.19) 
AOABB
GC     
 No. of cases (%)/controls (%) 319 (45.4)/572 (39.0) 194 (27.6)/428 (29.2) 81 (11.5)/141 (9.6) 109 (15.5)/324 (22.1) 
 Age- and sex-adjusted OR 1 (ref.) 0.81 (0.65–1.01) 1.03 (0.76–1.40) 0.60 (0.47–0.78) 
 Multivariable-adjusted ORa 1 (ref.) 0.80 (0.64–1.00) 1.4 (0.76–1.42) 0.60 (0.46–0.78) 
AG     
 No. of cases (%)/controls (%) 211 (42.5)/341 (37.5) 141 (28.4)/270 (29.7) 45 (9.1)/88 (9.7) 99 (20.0)/211 (23.2) 
 Age- and sex-adjusted OR 1 (ref.) 0.86 (0.65–1.13) 0.83 (0.55–1.26) 0.73 (0.54–0.99) 
 Multivariable-adjusted ORa 1 (ref.) 0.87 (0.66–1.14) 0.84 (0.55–1.27) 0.73 (0.53–0.99) 
HP     
 No. of cases (%)/controls (%) 318 (39.9)/234 (38.5) 241 (30.2)/170 (28.0) 70 (8.8)/63 (10.4) 169 (21.2)/141 (23.2) 
 Age- and sex-adjusted OR 1 (ref.) 1.09 (0.84–1.42) 0.83 (0.56–1.23) 0.88 (0.66–1.17) 
 Multivariable-adjusted ORa 1 (ref.) 1.11 (0.85–1.45) 0.84 (0.57–1.24) 0.89 (0.67–1.19) 

aMultivariable adjustment by age, sex, smoking status, drinking habit, and family history of GC.

Table 4.

Muitivariable-adjusted ORs (95% CIs) for incident GC, HP infection and AG by genotype-derived ABO blood group allele

Second alleleFirst allele
AOB
A    
GC    
 No. of cases (%)/controls (%) 74 (10.5)/117 (8.0) 245 (34.9)/455 (31.1) 81 (11.5)/141 (9.6) 
 Multivariable-adjusted ORa 1 (ref.) 0.85 (0.60–1.18) 0.91 (0.61–1.37) 
AG    
 No. of cases (%)/controls (%) 43 (8.7)/68 (7.5) 168 (33.9)/273 (30.0) 45 (9.07)/88 (9.7) 
 Multivariable-adjusted ORa 1 (ref.) 0.91 (0.58–1.43) 0.78 (0.45–1.35) 
HP    
 No. of cases (%)/controls (%) 69 (8.7)/42 (6.9) 249 (31.2)/192 (31.6) 63 (10.4)/70 (8.8) 
 Multivariable-adjusted ORa 1 (ref.) 0.73 (0.47–1.13) 0.65 (0.38–1.10) 
O    
GC    
 No. of cases (%)/controls (%) – 194 (27.6)/428 (29.2) 98 (13.9)/290 (19.8) 
 Multivariable-adjusted ORa  0.70 (0.50–0.99) 0.53 (0.36–0.77) 
AG    
 No. of cases (%)/controls (%) – 141 (28.4)/270 (29.7) 87 (17.5)/189 (20.8) 
 Multivariable-adjusted ORa  0.80 (0.51–1.27) 0.65 (0.40–1.06) 
HP    
 No. of cases (%)/controls (%) – 241 (30.2)/170 (28.0) 155 (19.4)/121 (19.9) 
 Multivariable-adjusted ORa  0.86 (0.55–1.34) 0.74 (0.46–1.19) 
B    
GC    
 No. of cases (%)/controls (%) – – 11 (1.6)/34 (2.3) 
 Multivariable-adjusted ORa   0.48 (0.23–1.02) 
AG    
 No. of cases (%)/controls (%) – – 12 (2.42)/22 (2.42) 
 Multivariable-adjusted ORa   0.86 (0.38–1.99) 
HP    
 No. of cases (%)/controls (%) – – 14 (1.8)/20 (3.3) 
 Multivariable-adjusted ORa   0.39 (0.17–0.87) 
Second alleleFirst allele
AOB
A    
GC    
 No. of cases (%)/controls (%) 74 (10.5)/117 (8.0) 245 (34.9)/455 (31.1) 81 (11.5)/141 (9.6) 
 Multivariable-adjusted ORa 1 (ref.) 0.85 (0.60–1.18) 0.91 (0.61–1.37) 
AG    
 No. of cases (%)/controls (%) 43 (8.7)/68 (7.5) 168 (33.9)/273 (30.0) 45 (9.07)/88 (9.7) 
 Multivariable-adjusted ORa 1 (ref.) 0.91 (0.58–1.43) 0.78 (0.45–1.35) 
HP    
 No. of cases (%)/controls (%) 69 (8.7)/42 (6.9) 249 (31.2)/192 (31.6) 63 (10.4)/70 (8.8) 
 Multivariable-adjusted ORa 1 (ref.) 0.73 (0.47–1.13) 0.65 (0.38–1.10) 
O    
GC    
 No. of cases (%)/controls (%) – 194 (27.6)/428 (29.2) 98 (13.9)/290 (19.8) 
 Multivariable-adjusted ORa  0.70 (0.50–0.99) 0.53 (0.36–0.77) 
AG    
 No. of cases (%)/controls (%) – 141 (28.4)/270 (29.7) 87 (17.5)/189 (20.8) 
 Multivariable-adjusted ORa  0.80 (0.51–1.27) 0.65 (0.40–1.06) 
HP    
 No. of cases (%)/controls (%) – 241 (30.2)/170 (28.0) 155 (19.4)/121 (19.9) 
 Multivariable-adjusted ORa  0.86 (0.55–1.34) 0.74 (0.46–1.19) 
B    
GC    
 No. of cases (%)/controls (%) – – 11 (1.6)/34 (2.3) 
 Multivariable-adjusted ORa   0.48 (0.23–1.02) 
AG    
 No. of cases (%)/controls (%) – – 12 (2.42)/22 (2.42) 
 Multivariable-adjusted ORa   0.86 (0.38–1.99) 
HP    
 No. of cases (%)/controls (%) – – 14 (1.8)/20 (3.3) 
 Multivariable-adjusted ORa   0.39 (0.17–0.87) 

aMultivariable adjustment by age, sex, smoking status, drinking habit, and family history of GC.

An increased risk of GC was observed with the addition of the A allele (Ptrend < 0.001; Table 5) and a decreased risk with that of the B allele (Ptrend = 0.023). Although an increased risk of AG was suggested with addition of the A allele (Ptrend = 0.071), no relation was seen with the risk of HP infection (Ptrend = 0.617). Moreover, a decreased risk of HP infection was suggested with the addition of the B allele (Ptrend = 0.052), but no relation was seen between the risk of AG and addition of the B allele (Ptrend = 0.136).

Table 5.

Age- and sex-adjusted, and multivariable-adjusted ORs (95% CIs) for incident GC, HP infection, and AG with the addition of A allele

X, XaA, XaA, APtrend
GC     
 No. of cases/controls 303/752 326/596 74/117  
 Age- and sex-adjusted OR 1 (ref.) 1.36 (1.12–1.64) 1.56 (1.13–2.15) <0.001 
 Multivariable-adjusted ORb 1 (ref.) 1.37 (1.13–1.67) 1.59 (1.15–2.21) <0.001 
AG     
 No. of case/AG negative 240/481 213/361 43/68  
 Age- and sex-adjusted OR 1 (ref.) 1.18 (0.93–1.50) 1.34 (0.87–2.07) 0.069 
 Multivariable-adjusted ORb 1 (ref.) 1.18 (0.93–1.50) 1.34 (0.87–2.07) 0.071 
HP     
 No. of cases/controls 311/410 255/319 42/69  
 Age- and sex-adjusted OR 1 (ref.) 0.92 (0.73–1.16) 1.29 (0.84–1.97) 0.585 
 Multivariable-adjusted ORb 1 (ref.) 0.91 (0.72–1.14) 1.28 (0.84–1.96) 0.617 
X, XaA, XaA, APtrend
GC     
 No. of cases/controls 303/752 326/596 74/117  
 Age- and sex-adjusted OR 1 (ref.) 1.36 (1.12–1.64) 1.56 (1.13–2.15) <0.001 
 Multivariable-adjusted ORb 1 (ref.) 1.37 (1.13–1.67) 1.59 (1.15–2.21) <0.001 
AG     
 No. of case/AG negative 240/481 213/361 43/68  
 Age- and sex-adjusted OR 1 (ref.) 1.18 (0.93–1.50) 1.34 (0.87–2.07) 0.069 
 Multivariable-adjusted ORb 1 (ref.) 1.18 (0.93–1.50) 1.34 (0.87–2.07) 0.071 
HP     
 No. of cases/controls 311/410 255/319 42/69  
 Age- and sex-adjusted OR 1 (ref.) 0.92 (0.73–1.16) 1.29 (0.84–1.97) 0.585 
 Multivariable-adjusted ORb 1 (ref.) 0.91 (0.72–1.14) 1.28 (0.84–1.96) 0.617 

aX represents O or B allele.

bMultivariable adjustment by age, sex, smoking status, drinking habit, and family history of GC.

To explore difference between histologic subtypes (diffuse type and intestinal type), we also carried out subgroup analysis according to histologic subtypes. About diffuse-type GC risk, compared with subjects with blood type A, those with O, AB, and B blood types had ORs of 0.66 (CI, 0.50–0.88), 0.98 (CI, 0.67–1.43), and 0.52 (CI, 0.37–0.74), respectively. On the contrary, regarding the intestinal-type GC risk, compared with subjects with blood type A, those with O, AB, and B blood types had ORs of 1.04 (CI, 0.77–0.1.41), 1.16 (CI, 0.75–1.80), and 0.74 (CI, 0.51–1.05), respectively. Similarly, in genotype analysis, there was only a weak association between intestinal-type GC and ABO genotype.

In this study, we found that the risk of GC was higher among those with the blood type A than those with blood type B in a Japanese population. In addition, we observed suggestive associations between ABO blood group alleles and the risk of AG and HP infection. To our knowledge, this is the first study to indicate a correlation between SNPs at ABO gene loci and the development of GC, AG, and HP infection.

Although the association between ABO blood type and many diseases has been investigated for more than half a century (29, 30), findings to date have been of little practical clinical or disease prevention value. In particular, no clear evidence about the association between ABO blood type and risk of GC, AG, and HP infection has been produced (6–9, 13, 31–33). Meanwhile, some recent studies have shown an association between ABO blood type and pancreatic cancer risk (9, 34), whereas a genome-wide association study (GWAS) comparing patients with pancreatic cancer to controls and subsequent investigations showed a relationship between ABO gene locus and pancreatic cancer risk (10–12). Moreover, one hypothesis proposes that the difference in ABO antigens in gastric mucins influences the properties of HP binding, and explains the difference in pancreatic cancer risk among ABO blood types (35). A recent large prospective cohort study identified a statistically significant association between serologic ABO blood type and the risk of GC in a Western population, and suggested that people with blood type A have a higher risk of GC than those with blood type O (4). In our study, we used SNPs at the ABO gene locus to assess the impact of ABO genotype on the risk of GC. Compared with individuals with the AA genotype, only those with OO and BO genotypes had significantly decreased ORs of 0.70 (CI, 0.50–0.99) and 0.53 (CI, 0.36–0.77), respectively. Risk of GC and AG tended to increase with addition of the A allele, whereas that of GC and HP infection tended to decrease with addition of the B allele. Although the association between BB genotype and GC risk was not statistically significant, this may be because of small number of subjects with BB genotype and/or potential factors. From these findings, we suspect that the association between ABO blood type and GC risk may occur through an effect on the differences among ABO alleles in AG prevalence and HP infection.

As described by the study of Tatemichi and colleagues, HP infection is a risk factor for both diffuse-type and intestinal-type GC, and the high titer of anti-HP IgG antibody is closely associated with diffuse-type GC (36). They also described that AG with intestinal metaplasia is linked to intestinal-type GC. In our study, the degree of association between ABO blood type and GC risk was different between the 2 histologic types, and there was only a weak association in intestinal type. Although the reason for this difference between 2 histologic subtypes is unclear, the association between ABO blood type and AG risk may be affected by potential factors. Moreover, because associations between ABO blood type and risk of AG and HP infection were inconsistent with previous studies (13, 31, 32), further evaluation should be necessarily to confirm these associations. Nonetheless, our study replicated previous findings regarding ABO blood type and GC risk (4). The mechanism by which genetic variants in the ABO gene locus influence the risk of GC, AG, and HP infection has not been fully investigated. The ABO gene encodes a glycosyltransferase, and the A and B alleles encode proteins which differ minimally in amino acid sequence but catalyze the transfer of different carbohydrates (N-acetylgalactosamine or galactose) onto the H antigen to form the A or B antigens (10). In contrast, the O allele contains a single base deletion and does not lead to the production of A or B antigens (10). ABO or ABH antigens are expressed on the surface of red blood cells and numerous other tissues throughout the body (37). Glycoconjugates, such as ABO antigen, are important mediators of intercellular adhesion and membrane signaling, which are both critical to the progression and spread of malignant cells (11, 38). These cell surface molecules are also recognized by the host immune response and may influence immunosurveillance for malignant cells (11, 38, 39). In addition, the activity of the glycosyltransferase, encoded by the ABO gene, has been associated with circulating levels of von Willebrand factor and the risk of venous thromboembolism (12, 40). Furthermore, recent GWASs suggest that SNPs at the ABO gene locus are associated with several serum markers of inflammation–TNF-α, soluble intercellular adhesion molecule-1 (ICAM-1), soluble E-selectin, and soluble P-selectin (41–45). These findings support the possibility that ABO blood group alleles might correlate with systemic inflammatory state and immune cell recruitment, and thereby influence the risk of several cancers and certain diseases (11, 12, 40, 45). We therefore suspect that the association of ABO genotype with the risk of GC, AG, and HP infection results from genetic variations at the ABO gene locus and/or genetic variations which are closely linked to the ABO gene.

Our study has several methodologic issues which warrant discussion. First, the control population was selected from noncancer patients at ACCH. It is reasonable to assume that these patients are from the same base population from which case subjects were selected, warranting internal validity. With regard to external validity, we previously showed that individuals selected randomly from our control population were similar to the general population of Nagoya City in terms of the exposure of interest (19). Second, blood type was derived from genotype rather than serologic data. Although methods for determining blood type on the basis of a subject's DNA are well established (21, 46, 47), measurement error and exposure misclassification might have occurred. Additionally, the non–deletion-type O allele and cis-AB allele could not be detected with our method, albeit that these are extremely rare among Japanese (20, 21, 23). Third, we did not assess the HP infection status of GC cases. Given that the advanced gastric atrophy occurring in many patients with GC induces the elimination of HP from the gastric mucosa, measurement of HP does not necessarily reflect current or former infection status (48, 49). A potential limitation was residual confounding by known and unknown risk factors; in particular, the limited number of cases, particularly when stratified by genotype, indicates that our findings need replication in a larger study. Moreover, case–control studies may have suffered from recall bias. Nevertheless, the HERPACC system is less prone to this bias than typical hospital-based studies as the data for all patients are collected before diagnosis. Finally, our study was limited to a Japanese population and the results cannot necessarily be extrapolated to other populations. In summary, our case–control study showed that SNPs at the ABO gene locus were associated with the risk of GC in a Japanese population. This finding supports the recently reported association between blood type A and elevated risk of GC (4). Moreover, the ABO gene locus may be associated with AG prevalence and HP infection, and these associations may affect the association between ABO blood type and GC risk. Further investigation of these findings in other ethnic groups is warranted, and the mechanism by which the ABO gene locus influences the risk of GC, AG, and HP infection should be fully elucidated.

No potential conflicts of interest were disclosed.

We thank the doctors, nurses, technical staff, and hospital administration staff of Aichi Cancer Center Hospital for their efforts and contribution toward daily management of the HERPACC study. We also thank Dr. Saeko Ogata at the Medico-Legal Section, Criminal Investigation Laboratory, Metropolitan Police Department for her helpful support and comments.

This study was supported by Grants-in-Aid for Cancer Research from the Ministry of Health, Labour and Welfare of Japan; the Japan Society for the promotion of Science A3 Foresight Program; and research grants from the Aichi Cancer Research Foundation.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

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Supplementary data