Biomedicines 2020, 8, 419; doi:10.3390/biomedicines8100419
2020년 Biomedicines에 실린 연구 내용입니다. AIG 환자와 open type atrophy를 가지고 있는 non-AIG 환자의 임상적 특징, microbiome 분석, gastric cancer (GC) 등의 발생 여부에 대한 약 12년 간의 retrospective cohort study 입니다. 살펴보도록 하겠습니다.
<Study design>
Patients examined from 2005 to 2017 with endoscopy were included in this retrospective, single-center, cohort study.
GI endoscopy 기준: gastric cancer screening or gastroesophageal symptoms
Exclusion criteria: History of gastric cancer diagnosis or gastrectomy within the past year
Patients group (AIG): APCA titer 양성 (1:10 or greater in serological testing)
Control group (non-AIG): APCA tier 음성
Regardless of H. pylori infection status
The first-time measured data were evaluated. (Medication was defined as at least 30 days of use)
H. pylori infection status was evaluated based on the serum levels of H. pylori-IgG antibodies, a 13C-urea breath test, detection by gastric biopsy, stool antigen, or medical records.
Endoscopic atrophy: Kimura-Takemoto classification)
Histological assessment: Two tissue samples from the antrum and greater curvature of the corpus, modified Updated Sydney System)
16S rRNA gene sequencing: Isolated from biopsy samples of the greater curvature of the corpus)
Diversity analyses:
- Alpha-diversity: The total read numbers, number of operational taxonomic units (OTUs), and the Simpson Index between AIG and non-AIG.
- Beta-diversity: The ten most relevant taxa and visualized in a principal coordinate analyses (PcoA) between AIG and non-AIG.
- Sample clustering in the beta-diversity analyses were tested using a general linear model between the groups.
The endpoint was gastric cancer incidence events.
Figure 1. Study flow.
Table 1. Characteristics between autoimmune gastritis (AIG) and non-AIG in patients.
* AIG patients had a statistically higher rate of thyroid diseases.
* Concurrent or previous H. pylori infection was confirmed in 61.66% of AIG patients and in 69.02% of non-AIG patients.
* Gastrin were significantly higher in AIG patients (1412 pg/mL) than in non-AIG patients (353 pg/mL) (p < 0.001).
* Folic acid levels were also significantly higher in AIG patients.
* Higher percentage of corpus-dominant atrophy in AIG (31.67%) than in non-AIG (7.04%) patients (p < 0.001).
* Clusters of ECL cells were observed in 27.59% of AIG patients and 6.67% of non-AIG patients (p = 0.032).
Table 2. Characteristics between AIG and non-AIG in patients undergoing gastric microbiota analysis.
Figure 2. Gastric flora analysis. (A) Taxonomy, genus level. Comparison between AIG and non-AIG; (B) The ten most relevant genus taxa between AIG and non-AIG; (C) Principal coordinate analysis between AIG and non-AIG.
* Gastric microbiota analyses were performed among 29 patients without concurrent H. pylori infection (14 AIG and 15 non-AIG).
* AIG group had a significantly higher number of reads (mean of 32,805 vs. 20,592 reads, respectively; p = 0.043), non-significantly higher number of OTUs (mean of 45 vs. 39 OTUs), and non-significantly lower microbial alpha (within-sample) diversity and Simpson’s indexes.
* The genera Streptococcus (p = 0.046), Selenomonaus (p = 0.031), Granulicatella (p = 0.034), and Bacillus (p < 0.001) were detected in significantly higher proportions in AIG patients.
* Streptococcus, Haemophilus, Selenomonaus, and Granulicatella were detected only in AIG patients.
* The microbiota composition significantly differed between the groups (R-squared = 0.858, p < 0.001).
Figure 3. Gastric flora analysis. (A) Taxonomy, genus level. Comparison between proton pump inhibitor (PPI) and non-PPI; (B) The ten most relevant genus taxa between PPI and non-PPI; (C) Principal coordinate analysis between PPI and non-PPI.
* 16S rRNA gastric microbiota analyses were performed, there were no differences in the microbiota composition of PPI users (n = 7) vs. non-users (n = 22) (Figure 3A,C).
* The most frequently identified genera were Veillonella, Lactobacillus, and Selenomonas in PPI users and Veillonella, Prevotella, and Lactobacillus in non-users (Figure 3B).
Figure 4. Cumulative gastric cancer incidence.
* The mean follow-up period was 6.2 years (interquartile range 2.3–9.8 years) in the AIG group and 7.4 years (interquartile range 4.0–10.0 years) in the non-AIG group.
* GC: 1 patient from the AIG group / 3 patients from the non-AIG group (p = 0.457, log-rank)
* No significant differences in the rate of GC development
<Discussion>
* Gastric microbiota did not differ between PPI users and non-users in our study
: Small number of PPI users in our study (n = 7), Differences in the dose and duration of PPI use
: Most of our patients had a history of H. pylori eradication, and the effects of PPIs on the gastric microbiome may be different from those in healthy individuals
* Hypergastrinemia & Altered gastric microbiome (associated with increased risk for gastric malignant diseases)
--> In our AIG patients, there was no significant association
: 60% of our AIG patients also had concurrent or previous H. pylori infection
: Missing data in our study might have resulted in differences compared to other studies
* Gastrin differentially influences the development of GCs and NETs
: former likely originating from gastric stem cells and the latter from ECL cells, although the two cell types express the same gastrin receptor. (Waldum, H.L.; Fossmark, R. Role of Autoimmune Gastritis in Gastric Cancer. Clin. Transl. Gastroenterol. 2019, 10, e00080.)
* Limitations
: First, it was a retrospective single-center study.
: Second, the diagnosis of AIG was limited to endoscopically determined atrophy and serological APCA levels; the levels of anti-intrinsic factor antibody were not determined.
: Third, our gastric microbiota analyses were limited to selected patients because consents and gastric mucosal samples could not be obtained for all patients.
In conclusion, AIG patients had higher serum levels of gastrin and differences in their gastric microbiota compared to non-AIG patients. Our data also suggest that, in patients with high H. pylori infection rates, the presence of AIG and hypergastrinemia together with an altered gastric microbiome has a more direct association with ECL cell hyperplasia than with gastric cancer.
Abstract:
In Asia, the incidences of Helicobacter pylori infection and gastric cancer are high, but their association with autoimmune gastritis (AIG) is unclear. This was a retrospective cohort study of patients endoscopically diagnosed with chronic gastritis between 2005 and 2017. AIG was diagnosed according to anti-parietal cell antibody positivity. Laboratory, histological findings, and gastric cancer incidence were compared between AIG and non-AIG patients. The AIG group had more females and a higher rate of thyroid disease. Serum levels of gastrin were significantly higher in AIG patients (mean 1412 and 353 pg/mL, p < 0.001). The endoscopic findings included a significantly higher percentage of corpus-dominant atrophy in AIG (31.67%) than in non-AIG (7.04%) patients (p < 0.001). Clusters of ECL cells were observed in 28% of AIG patients and 7% of non-AIG patients (p = 0.032). The cumulative incidence of gastric cancer at 5 and 10 years was 0% and 0.03% in the AIG group and 0.03% and 0.05% in the non-AIG group, and no significant difference in gastric cancer incidence was observed. Despite significant differences in gastrin levels between AIG and non-AIG patients, there was no evidence of an impact of AIG on the incidence of gastric cancer.
Biomedicines 2020, 8, 419; doi:10.3390/biomedicines8100419
2020년 Biomedicines에 실린 연구 내용입니다. AIG 환자와 open type atrophy를 가지고 있는 non-AIG 환자의 임상적 특징, microbiome 분석, gastric cancer (GC) 등의 발생 여부에 대한 약 12년 간의 retrospective cohort study 입니다. 살펴보도록 하겠습니다.
<Study design>
Patients examined from 2005 to 2017 with endoscopy were included in this retrospective, single-center, cohort study.
GI endoscopy 기준: gastric cancer screening or gastroesophageal symptoms
Exclusion criteria: History of gastric cancer diagnosis or gastrectomy within the past year
Patients group (AIG): APCA titer 양성 (1:10 or greater in serological testing)
Control group (non-AIG): APCA tier 음성
Regardless of H. pylori infection status
The first-time measured data were evaluated. (Medication was defined as at least 30 days of use)
H. pylori infection status was evaluated based on the serum levels of H. pylori-IgG antibodies, a 13C-urea breath test, detection by gastric biopsy, stool antigen, or medical records.
Endoscopic atrophy: Kimura-Takemoto classification)
Histological assessment: Two tissue samples from the antrum and greater curvature of the corpus, modified Updated Sydney System)
16S rRNA gene sequencing: Isolated from biopsy samples of the greater curvature of the corpus)
Diversity analyses:
- Alpha-diversity: The total read numbers, number of operational taxonomic units (OTUs), and the Simpson Index between AIG and non-AIG.
- Beta-diversity: The ten most relevant taxa and visualized in a principal coordinate analyses (PcoA) between AIG and non-AIG.
- Sample clustering in the beta-diversity analyses were tested using a general linear model between the groups.
The endpoint was gastric cancer incidence events.
Figure 1. Study flow.
Table 1. Characteristics between autoimmune gastritis (AIG) and non-AIG in patients.
* AIG patients had a statistically higher rate of thyroid diseases.
* Concurrent or previous H. pylori infection was confirmed in 61.66% of AIG patients and in 69.02% of non-AIG patients.
* Gastrin were significantly higher in AIG patients (1412 pg/mL) than in non-AIG patients (353 pg/mL) (p < 0.001).
* Folic acid levels were also significantly higher in AIG patients.
* Higher percentage of corpus-dominant atrophy in AIG (31.67%) than in non-AIG (7.04%) patients (p < 0.001).
* Clusters of ECL cells were observed in 27.59% of AIG patients and 6.67% of non-AIG patients (p = 0.032).
Table 2. Characteristics between AIG and non-AIG in patients undergoing gastric microbiota analysis.
Figure 2. Gastric flora analysis. (A) Taxonomy, genus level. Comparison between AIG and non-AIG; (B) The ten most relevant genus taxa between AIG and non-AIG; (C) Principal coordinate analysis between AIG and non-AIG.
* Gastric microbiota analyses were performed among 29 patients without concurrent H. pylori infection (14 AIG and 15 non-AIG).
* AIG group had a significantly higher number of reads (mean of 32,805 vs. 20,592 reads, respectively; p = 0.043), non-significantly higher number of OTUs (mean of 45 vs. 39 OTUs), and non-significantly lower microbial alpha (within-sample) diversity and Simpson’s indexes.
* The genera Streptococcus (p = 0.046), Selenomonaus (p = 0.031), Granulicatella (p = 0.034), and Bacillus (p < 0.001) were detected in significantly higher proportions in AIG patients.
* Streptococcus, Haemophilus, Selenomonaus, and Granulicatella were detected only in AIG patients.
* The microbiota composition significantly differed between the groups (R-squared = 0.858, p < 0.001).
Figure 3. Gastric flora analysis. (A) Taxonomy, genus level. Comparison between proton pump inhibitor (PPI) and non-PPI; (B) The ten most relevant genus taxa between PPI and non-PPI; (C) Principal coordinate analysis between PPI and non-PPI.
* 16S rRNA gastric microbiota analyses were performed, there were no differences in the microbiota composition of PPI users (n = 7) vs. non-users (n = 22) (Figure 3A,C).
* The most frequently identified genera were Veillonella, Lactobacillus, and Selenomonas in PPI users and Veillonella, Prevotella, and Lactobacillus in non-users (Figure 3B).
Figure 4. Cumulative gastric cancer incidence.
* The mean follow-up period was 6.2 years (interquartile range 2.3–9.8 years) in the AIG group and 7.4 years (interquartile range 4.0–10.0 years) in the non-AIG group.
* GC: 1 patient from the AIG group / 3 patients from the non-AIG group (p = 0.457, log-rank)
* No significant differences in the rate of GC development
<Discussion>
* Gastric microbiota did not differ between PPI users and non-users in our study
: Small number of PPI users in our study (n = 7), Differences in the dose and duration of PPI use
: Most of our patients had a history of H. pylori eradication, and the effects of PPIs on the gastric microbiome may be different from those in healthy individuals
* Hypergastrinemia & Altered gastric microbiome (associated with increased risk for gastric malignant diseases)
--> In our AIG patients, there was no significant association
: 60% of our AIG patients also had concurrent or previous H. pylori infection
: Missing data in our study might have resulted in differences compared to other studies
* Gastrin differentially influences the development of GCs and NETs
: former likely originating from gastric stem cells and the latter from ECL cells, although the two cell types express the same gastrin receptor. (Waldum, H.L.; Fossmark, R. Role of Autoimmune Gastritis in Gastric Cancer. Clin. Transl. Gastroenterol. 2019, 10, e00080.)
* Limitations
: First, it was a retrospective single-center study.
: Second, the diagnosis of AIG was limited to endoscopically determined atrophy and serological APCA levels; the levels of anti-intrinsic factor antibody were not determined.
: Third, our gastric microbiota analyses were limited to selected patients because consents and gastric mucosal samples could not be obtained for all patients.
In conclusion, AIG patients had higher serum levels of gastrin and differences in their gastric microbiota compared to non-AIG patients. Our data also suggest that, in patients with high H. pylori infection rates, the presence of AIG and hypergastrinemia together with an altered gastric microbiome has a more direct association with ECL cell hyperplasia than with gastric cancer.
Abstract:
In Asia, the incidences of Helicobacter pylori infection and gastric cancer are high, but their association with autoimmune gastritis (AIG) is unclear. This was a retrospective cohort study of patients endoscopically diagnosed with chronic gastritis between 2005 and 2017. AIG was diagnosed according to anti-parietal cell antibody positivity. Laboratory, histological findings, and gastric cancer incidence were compared between AIG and non-AIG patients. The AIG group had more females and a higher rate of thyroid disease. Serum levels of gastrin were significantly higher in AIG patients (mean 1412 and 353 pg/mL, p < 0.001). The endoscopic findings included a significantly higher percentage of corpus-dominant atrophy in AIG (31.67%) than in non-AIG (7.04%) patients (p < 0.001). Clusters of ECL cells were observed in 28% of AIG patients and 7% of non-AIG patients (p = 0.032). The cumulative incidence of gastric cancer at 5 and 10 years was 0% and 0.03% in the AIG group and 0.03% and 0.05% in the non-AIG group, and no significant difference in gastric cancer incidence was observed. Despite significant differences in gastrin levels between AIG and non-AIG patients, there was no evidence of an impact of AIG on the incidence of gastric cancer.