https://orcid.org/0000-0003-4292-3738
Figures
Abstract
Background
Autoimmune gastritis (AIG) is a chronic inflammatory condition characterized by the destruction of gastric parietal cells. The invasive nature of diagnostic procedures and risk of confounding factors hinder the development of reliable diagnostic tools for AIG.
Methods
We conducted a systematic search of four databases. After assessing the study quality using the ROBINS-E tool, a meta-analysis was performed using a random-effects model. Meta-regression and sensitivity analyses were conducted to explore the sources of heterogeneity and impact of study bias,
Results
The pooled mean difference in total serum ghrelin (pmol/L) between patients with AIG and healthy controls was −65.28 (95% CI: −178.54, 47.97). Subgroup analysis showed that the mean differences in serum ghrelin for mild, moderate, and severe atrophy were −78.85 (95% CI: −165.17, to 7.48), −91.97 (95% CI: −183.11, to −0.84), and −110.67 (95% CI: −204.77, to −16.56), respectively. The sensitivity analysis confirmed that the exclusion of studies with high-risk bias did not significantly alter the results. Meta-regression indicated that BMI contributed substantially to heterogeneity.
Conclusions
Although total serum ghrelin levels were not significantly different between patients with AIG and healthy controls, significantly lower levels were observed in patients with moderate-to-severe gastric atrophy. Given the high heterogeneity and limitations of existing studies, the diagnostic utility of serum ghrelin in AIG warrants further investigation.
Citation: Taufiqqurrachman I, Witarto AP, Syam AF, Abdullah M, Saputro SA, Normalina I, et al. (2026) Diagnostic potential of total serum ghrelin in autoimmune gastritis: A systematic review and meta-analysis. PLoS One 21(3): e0344129. https://doi.org/10.1371/journal.pone.0344129
Editor: Chen Ling, Fudan University, CHINA
Received: July 28, 2025; Accepted: February 16, 2026; Published: March 12, 2026
Copyright: © 2026 Taufiqqurrachman et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: This report is based on work supported in part by grants from the National Institutes of Health (DK62813) (Y.Y) and Grants-in-Aid for Scientific Research from the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) of Japan (221S0002, 21H00346, 22H02871, and 23K24133) (Y.Y). This work was supported in part by the Japan Agency for Medical Research and Development (AMED) [Adopting Sustainable Partnerships for Innovative Research Ecosystem (ASPIRE); 23836904, Science and Technology Research Partnership for Sustainable Development (SATREPS); 21357105] and the Japan International Cooperation Agency (JICA) [SATREPS] (Y.Y). IT is a Ph.D. student supported by the Japanese Government (MEXT) Scholarship Program for 2024. the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Autoimmune gastritis (AIG) is a chronic gastric inflammation that is caused by the destruction of the subunit H+/K + ATPase pump in parietal cells induced by autoreactive T helper 1 cells after the production of anti-parietal cell antibodies (APCA) or anti-intrinsic factor antibodies (AIFA) [1–3]. It is characterized by the damage of oxyntic mucosa or parietal cells at the fundus and corpus of the stomach, and can lead to progressive mucosal atrophy [1,4–6], therefore, it is classified within the scope of chronic atrophic gastritis. The prevalence of AIG is heterogeneous and depends on diagnostic criteria. In the general population, the prevalence of AIG is 0.1%–2.7% if the diagnosis is based on esophagogastroduodenoscopy (EGD) and histopathological examination, but the prevalence increases to 8%–20% if the diagnosis is based on the positive detection of APCA or AIFA [7,8].
Historically, the incidence of AIG in Asian countries was lower than that in Western countries, as chronic atrophic gastritis in Asia has primarily been attributed to Helicobacter pylori infection. A report in Japan showed that from 6,739 subjects, there are 46 (0.49%) had the endoscopic appearance of AIG, but only 33 of 46 were diagnosed as AIG [9]. Another report evaluates the AIG appearance in biopsy sample of several ethnicity, and the results showed that the AIG appearance only found in 1.4% of Asian ethnicity [10]. A recent meta-analysis showed that the Europe, Africa, and Australia region were dominating the prevalence of AIG with the prevalence of 4.94%, 8.46%, and 8.08%. In comparison, the prevalence of AIG in Asia region is only 2.23% [11]. However, recent studies suggest a shifting epidemiological trend, with increasing recognition of AIG among Asian populations.
The prior knowledge of low prevalence of AIG in Asian population may be masked by the high rate of H. pylori infection, difficulty in endoscopic diagnosis based on atrophic appearance that can misdiagnose H. pylori infection, and false-positive urea breath test (UBT) results due to the increase in urease-positive, non-H. pylori, bacterial growth induced by achlorydia [12,13]. A supporting report showed that the eradication of H. pylori was followed by the rapid progression of AIG, indicating that H. pylori infection obscures AIG manifestations [12].
This has changed our paradigm regarding the occurrence of AIG, particularly in Asian countries. Therefore, a prompt diagnostic modality is required for AIG. Previous studies have used endoscopic appearance, biopsy examination, and positive APCA or intrinsic factor autoantibodies results to diagnose AIG [14]. However, because endoscopy and biopsy are invasive and it is difficult to differentiate between AIG and prior H. pylori infection [15], and several factors are associated with APCA positivity [16], an alternative non-invasive diagnostic method for AIG with high sensitivity and specificity is needed.
Ghrelin is a potential biomarker of AIG. Ghrelin is a hormone secreted by endocrine cells in the oxyntic glands of the gastric corpus and the fundus, particularly by the P/D1 cells. This hormone has been reported to be associated with several conditions such as gastric cancer and colorectal cancer. In AIG, damage to the oxyntic mucosa or parietal cells at the fundus and corpus of the stomach may lead to progressive gastric mucosal atrophy. The atrophy may affect the level of ghrelin that predominantly produced in stomach [17,18]. (Fig 1)
However, the general difference in serum ghrelin levels between patients with AIG and healthy individuals is unknown, although a few studies have used ghrelin in diagnostic studies of AIG. This study aimed to determine the differences in serum ghrelin levels and corresponding differences in the severity of gastric atrophy between adult patients with AIG and healthy controls.
Methods
Search strategy
A systematic review and meta-analysis was performed based on the PRISMA 2020 checklist [19]. Articles were sourced from four different databases: (1) PubMed, (2) EBSCO Host in MEDLINE Full Text, (3) Scopus, and (4) ProQuest. The search period was August 25 to September 30, 2024. In this study, the population comprised adult patients with normal exposure to autoimmune gastritis (with terms for the search of “Atrophic Gastritis” or “Autoimmune Gastritis” or “Atrophic Autoimmune Gastritis”), and the outcome was total serum ghrelin (with terms for the search of “Ghrelin” or “Serum Ghrelin”). The search strategy used to find relevant articles in this study was based on different databases and registers using the keywords listed in S1 Table.
Eligibility criteria
The inclusion criteria were as follows: (1) adult patients (> 18 years old) and (2) diagnosis of autoimmune gastritis based on gastric atrophic appearance (from EGD or histological examination) and positive APCA with or without H. pylori infection. This criteria was based on the recent finding that AIG could be triggered by H. pylori infection [20]. The exclusion criteria were as follows: (1) history or status of malignancy and its treatment; (2) renal impairment; (3) other conditions that cause gastric inflammation (e.g., prolonged non-steroid anti-inflammatory drug use, prolonged corticosteroid use, and alcohol abuse); (4) history of gastric surgery; and (5) other conditions or procedures that obscure the gastric appearance on EGD.
Selection and data collection process
Studies were progressively selected. Two reviewers considered articles and independently selected relevant studies using a progressive approach (relevance of the title and abstract, deduplication, and full text) based on the eligibility criteria. The total number of full-text relevant studies was compared with each reviewer’s input on a Google sheet spreadsheet. If perceptions differed among the reviewers, discussions and voting were conducted by all five reviewers. Data from the studies were collected from the metadata of the Google spreadsheets. Data collection was performed by two reviewers. No automated or artificial intelligence tools were employed for collecting data from the selected studies. If conflict existed between the two reviewers, discussions and voting were conducted among all five reviewers.
The outcome data of the selected studies were the mean total serum ghrelin levels between two different groups (patients with autoimmune gastritis and healthy controls) and different degrees of atrophic severity. Additional data sought from the selected studies included the number of subjects (total, autoimmune gastritis, normal, and atrophic severity), demographic status of the subjects (age, sex, and body mass index), and the method used to assess serum ghrelin levels.
Risk of bias assessment
The risk of bias in the systematic reviews of observational studies was assessed with the Risk of Bias in Non-Randomized Studies – Of Exposure (ROBINS-E) tool. The components assessed using this tool were as follows: (1) bias due to confounding factors, (2) bias arising from measurement of the exposure, (3) bias in selection of participants into the study (or into the analysis), (4) bias due to post-exposure interventions, (5) bias due to missing data, (6) bias arising from measurement of the outcome, and (7) bias in selection of the reported result, to be accumulated as the overall bias [21]. To evaluate the robustness of the meta-analysis result, a sensitivity analysis will be performed if the included studies had a high risk of bias.
Data synthesis
Data were generated based on the demographic status of the subjects, followed by the collection of effect measures, which included the mean total serum ghrelin (in pmol/L or pg/mL) of AIG patients and healthy controls, and the mean total serum ghrelin level between AIG patients with different atrophic severities and healthy controls. Unavailable data on mean total serum ghrelin levels were reported as N/A (not available) and were not included in the data analysis. The mean total serum ghrelin levels were converted to the pmol/L scale by multiplying the value in pg/mL by a coefficient of 0.3, based on the findings of Aukan et al. (2022) [22]. The generated data are presented in Table 1. Meta-analysis was performed for continuous data with a random effects model using RStudio version 2024.09.0 + 375 (© Posit Software, PBC) to collect data on effect size, variance, heterogeneity, and publication bias, which were presented in forest and funnel plots. Funnel plot asymmetry was measured using Egger’s regression test if > 10 studies were included (k > 10). When heterogeneity was high, meta-regression was performed using STATA version 17.0 (StataCorp).
Results
Study selection
Study selection was performed using a progressive approach from four databases (PubMed, EBSCO Host in MEDLINE full text, Scopus, and ProQuest). The PRISMA flow [19] is shown in Fig 2.
Study characteristics
The study’s characteristics are presented in Table 1. The five included studies comprised a total of 331 participants across Italy, Spain and China with sample sizes ranging from 15 to 100 subjects. All studies diagnosed AIG through a combination of endoscopic evaluation, histopathological confirmation, and APCA positivity, while methods for serum ghrelin measurement varied between ELISA and radioimmunoassay. Participant demographic differed across studies, reflecting differences in diagnostic methods, population characteristics, and sample handling. Key study limitations included lack of BMI stratification, incomplete H. pylori status reporting, absence of atrophy severity subgroup analyses, and potential confounding from comorbid conditions such as type 1 diabetes mellitus.
Risk of bias in studies
The risk of bias was measured using ROBINS-E. Two studies showed a high risk of bias (Panarese, et al. (2007) and Checchi, et al. (2007)), one study had some concern regarding bias (Alonso, et al.), and two studies showed a low risk of bias (Alonso, et al. (2007) and Gao, et al. (2008)) (Fig 3).
Data synthesis
Difference in total serum ghrelin between autoimmune gastritis patients and healthy controls.
The mean difference in total serum ghrelin (pmol/L) between autoimmune gastritis and healthy controls from five studies (311 subjects) was ˗65.28 (95% confidence interval [CI]: ˗178.54, 47.97) pmol/L (Fig 4). However, the heterogeneity of the results was very high, with an I2 value of 98%.
Difference in total serum ghrelin between AIG patient with different degrees of gastric atrophy to healthy controls.
The mean differences between different degrees of atrophy were analyzed. The resulting forest and funnel plots are shown in Fig 5. The mean differences in total serum ghrelin (pmol/L) for three different degrees of atrophy (mild vs healthy control, moderate vs healthy control, and severe vs healthy control) were ˗78.85 (three studies of a total of 189 subjects; 95% CI: ˗165.17, 7.48), ˗91.97 (three studies of a total of 181 subjects; 95% CI: ˗183.11, ˗0.84), and ˗110.67 (three studies of a total of 153 subjects; 95% CI: ˗204.77, ˗16.56), respectively. These results were accompanied by very high heterogeneity.
Sensitivity analysis and meta-regression
Sensitivity analysis was performed to assess the precision of the findings, because there are two studies with a high risk of bias were included in the meta-analysis. Sensitivity analysis was performed by excluding high-risk bias studies and evaluating pairwise meta-analyses. The results showed that the mean difference in serum ghrelin levels between patients with AIG and healthy controls was also not significantly different, with a mean difference of −52.51 (95% CI: −126.34; 21.30) (S1 Fig).
To evaluate the possible causes of high heterogeneity, a meta-regression analysis was performed. Two demographic statuses (mean age and BMI) were analyzed using a meta-regression. The results showed that mean age was not associated with high heterogeneity (S2 Table); however, mean BMI was significantly associated with high heterogeneity (S3 Table).
Discussion
Three studies were included in a meta-analysis by Panarese et al. (2020), Campana et al. (2007), and Alonso et al. (2007), reported no significant difference in mean total serum ghrelin levels between patients with autoimmune gastritis and healthy controls [23–25]. Of the five studies included in the meta-analysis, only two (Panarese et al. [2020] and Alonso et al. [2007]) reported increased total serum ghrelin levels in the AIG group. Overall, the meta-analysis showed no significant difference in total serum ghrelin levels between patients with AIG and healthy controls, with a pooled mean difference of −65.28 pmol/L (five studies, 311 subjects; 95% CI: −146.05 to 15.48) (Fig 3). However, the heterogeneity among the studies was very high (I² = 98.76%, H² = 80.65, Q (df = 4) = 80.65, P < 0.0001). Despite the overall non-significant finding, subgroup analyses based on histological grades of gastric atrophy (mild, moderate, and severe) revealed a potential severity-related trend, with significantly lower serum ghrelin levels observed in patients with moderate to severe atrophy (Fig 4).
The decrease in total serum ghrelin between AIG patients and healthy controls was supported by two of the included studies (Checchi et al. and Gao et al.) [26,27]. In addition, a report by Kalkan Ç, et al. (2016) found that total serum ghrelin was decreased in patients with AIG, especially those who had delayed gastric emptying [17]. These findings are consistent with the pathogenesis of AIG. Ghrelin is a peptide hormone produced by ghrelin-producing cells that acts as a ligand for the growth hormone secretagogue receptor and plays a key role in gastrointestinal regulation—stimulating gastric acid secretion, enhancing gut motility, and increasing appetite and food intake [28,29]. A key feature of AIG is the destruction of parietal cells via the recognition of proton-pump H+/K+-ATPase by APCA, which leads to gastric mucosal atrophy [3,6,5]. Ghrelin-producing cells showed close linkage by immunohistochemical analysis [30], and close proximity to parietal cells (with some cells being in full contact) [31–33]. The inflammation and gastric atrophy resulting from the destruction of parietal cells also causes the loss of ghrelin-producing cells [34], predominantly those located in the corpus (predilection of autoimmune gastritis lesions by the corpus of the stomach) [1,35] compared with other regions of the gastrointestinal tract [31].
Several included studies were not excluding the patient with H. pylori infection. However, because the AIG occurrence may be associated with H. pylori infection (concurrently or post-eradication period), the result is still valid for interpretation. In addition, this result showed that the serum ghrelin level may also associate with the condition of AIG and H. pylori infection that occurred concurrently. In the concurrent condition, the AIG was developed by molecular mimicry between H. pylori antigens and the H+/K+-ATPase with the involvement of TLR-dependent pathway [36]. This was supported by recent finding in Indonesia that showed that the positivity of parietal cell antibody (PCA) is significantly correlated to the positivity of H. pylori infection [20]. If the inflammation process persist after H. pylori eradication, the progression of AIG may occurred based on the gastric mucosal condition. However, the report of this condition is still limited to case reports [36].
Subgroup analysis findings suggest that total serum ghrelin may serve as a potential diagnostic marker for AIG, particularly in patients with moderate-to-severe gastric atrophy. However, these results were influenced by two studies with a high risk of bias and were accompanied by substantial heterogeneity. The ROBINS-E tool identified two studies, Panarese et al. (2020) and Checchi et al. (2007), as having a high risk of bias, primarily due to inadequate control of confounding variables, possible misclassification of exposure, and incomplete reporting of the outcome data. Alonso et al. (2007) were assessed as having some concerns, whereas the remaining two studies were judged to have a low risk of bias. Sensitivity analysis excluding high-risk studies was conducted to evaluate the robustness of the findings (S1 Fig). The pooled mean difference in total serum ghrelin based on the remaining three studies was −52.51 pmol/L (95% CI: −126.34 to 21.30), which remained statistically non-significant and consistent with the primary meta-analysis. This finding suggests that the main findings were not solely driven by the inclusion of studies with a high risk of bias.
The high heterogeneity observed in the meta-analysis may be attributed to the small sample size and variations in participant demographics that may affect the effect size. A report by Levine T, et al. (2009) showed that the negative correlation between the sample size and effect size which lead to overestimation [37]. To explore potential sources of heterogeneity, a meta-regression analysis was conducted to the available possible confounding data: (1) age and (2) body mass index (BMI). The results indicated that mean BMI, but not mean age, was significantly associated with heterogeneity in pooled effect size (S2 and S3 Tables). However, the other possible confounding factors may also be contributed. Several reports in Japan showed that plasma ghrelin level was inversely correlated with metabolic syndrome and or insulin resistance [38–40]. Female gender and high-density lipoprotein level were associated independently to the ghrelin level. [40] Another report showed that plasma ghrelin was positively correlated with serum albumin level [41]. In addition, the demographic status may also contribute. Matsunaga-Irie S, et al. (2007) reported that the serum ghrelin levels were significantly higher in Caucasian than Japanese that may cause by the higher prevalence of obesity among Caucasian than Japanese [42]. Unfortunately, the limitation of provided data was limiting the exploration of other confounding factors that cause the high heterogeneity.
This study had several limitations. First, most of the included studies were conducted in Europe, with only one study from Asia (China) having a relatively small sample size, which reduces its generalizability. Second, substantial heterogeneity was observed, largely owing to differences in patient BMI. Based on these limitations, recommendations for future research include: (1) investigating serum ghrelin levels in populations from diverse geographic regions; (2) stratifying study participants based on H. pylori infection status to better evaluate its impact on serum ghrelin; and (3) controlling for BMI as part of the study inclusion criteria. Another potential limitation is the co-occurrence of AIG and H. pylori infections. However, recent publications have suggested a possible relationship between H. pylori infection and the progression of autoimmune gastritis [20]. Alonso et al. (2007) includes the patients with co-occurrence of H. pylori infection and AIG in their analysis [25]. Several previous studies have shown that 20%–30% of the H. pylori-infected population possess autoantibodies against parietal cells [43,44]. The fundamental mechanism is thought to involve molecular mimicry. [45] A previous study proposed that autoreactive antibodies, through the activity of H+/K+ ATPase, and H. pylori antigen were important contributors. This also supported by Borén et al. [46], who reported that anti-LeX monoclonal antibodies (antibody to Lewis antigens found in the LPS of H. pylori and human cells such as gastric epithelial cells, endothelial cells, and polymorphonuclear cells) are induced by H. pylori infection [47]. The β-subunit of urease in H. pylori is homologous to the β-subunit of ATPase in parietal cells, which also indicates a mechanism of molecular mimicry [48,49]. Therefore, H. pylori infection may be related to AIG in this manner.
Conclusion
The total serum ghrelin levels in patients with AIG were not significantly different from those in healthy controls. However, patients with AIG and moderate-to-severe gastric atrophy exhibited notably lower ghrelin levels. These findings suggest that total serum ghrelin level may serve as a potential diagnostic marker for AIG in patients with advanced gastric atrophy. However, given the limited number of subjects and included studies, the applicability of these findings in clinical practice remains restricted. Given the high heterogeneity, risk of bias, and other limitations among the included studies, further well-designed research is needed to validate the diagnostic utility of serum ghrelin for AIG.
Supporting information
S2 Table. Meta-regression analysis of mean age between studies.
https://doi.org/10.1371/journal.pone.0344129.s002
(DOCX)
S3 Table. Meta-regression Analysis of Mean BMI between studies.
https://doi.org/10.1371/journal.pone.0344129.s003
(DOCX)
References
- 1. Castellana C, Eusebi LH, Dajti E, Iascone V, Vestito A, Fusaroli P, et al. Autoimmune atrophic gastritis: a clinical review. Cancers (Basel). 2024;16(7):1310. pmid:38610988
- 2. Kamada T, Maruyama Y, Monobe Y, Haruma K. Endoscopic features and clinical importance of autoimmune gastritis. Dig Endosc. 2022;34(4):700–13. pmid:34674318
- 3. Orgler E, Dabsch S, Malfertheiner P, Schulz C. Autoimmune gastritis: update and new perspectives in therapeutic management. Curr Treat Options Gastro. 2023;21(1):64–77.
- 4. Singh S, Chakole S, Agrawal S, Shetty N, Prasad R, Lohakare T, et al. A Comprehensive review of upper gastrointestinal symptom management in autoimmune gastritis: current insights and future directions. Cureus. 2023;15(8):e43418. pmid:37706145
- 5. Neumann WL, Coss E, Rugge M, Genta RM. Autoimmune atrophic gastritis--pathogenesis, pathology and management. Nat Rev Gastroenterol Hepatol. 2013;10(9):529–41. pmid:23774773
- 6. Lenti MV, Rugge M, Lahner E, Miceli E, Toh B-H, Genta RM, et al. Autoimmune gastritis. Nat Rev Dis Primers. 2020;6(1):56. pmid:32647173
- 7. Miceli E, Lenti MV, Padula D, Luinetti O, Vattiato C, Monti CM, et al. Common features of patients with autoimmune atrophic gastritis. Clin Gastroenterol Hepatol. 2012;10(7):812–4. pmid:22387252
- 8. Rusak E, Chobot A, Krzywicka A, Wenzlau J. Anti-parietal cell antibodies - diagnostic significance. Adv Med Sci. 2016;61(2):175–9. pmid:26918709
- 9. Notsu T, Adachi K, Mishiro T. Prevalence of autoimmune gastritis in individuals undergoing medical checkups in Japan. Intern Med. 2019;58:1817–23.
- 10. Park JY, Cornish TC, Lam-Himlin D, Shi C, Montgomery E. Gastric lesions in patients with autoimmune metaplastic atrophic gastritis (AMAG) in a tertiary care setting. Am J Surg Pathol. 2010;34(11):1591–8. pmid:20975338
- 11. Li M, Huang Y, Liang X, Lu H. Prevalence of Autoimmune Gastritis Worldwide: A Systematic Review and Meta-Analysis. Helicobacter. 2025;30(4):e70065. pmid:40831008
- 12. Ihara T, Ihara N, Kushima R, Haruma K. Rapid Progression of Autoimmune Gastritis after Helicobacter pylori Eradication Therapy. Intern Med. 2023;62(11):1603–9. pmid:36261377
- 13. Massironi S, Zilli A, Elvevi A, Invernizzi P. The changing face of chronic autoimmune atrophic gastritis: an updated comprehensive perspective. Autoimmun Rev. 2019;18(3):215–22. pmid:30639639
- 14. Rugge M, Bricca L, Guzzinati S, Sacchi D, Pizzi M, Savarino E, et al. Autoimmune gastritis: long-term natural history in naïve Helicobacter pylori-negative patients. Gut. 2023;72(1):30–8. pmid:35772926
- 15. Nishizawa T, Yoshida S, Watanabe H, Toyoshima A, Kataoka Y, Takahashi Y, et al. Clue of Diagnosis for Autoimmune Gastritis. Digestion. 2021;102(6):903–10. pmid:34198294
- 16. Rusak E, Chobot A, Krzywicka A, Wenzlau J. Anti-parietal cell antibodies - diagnostic significance. Adv Med Sci. 2016;61(2):175–9. pmid:26918709
- 17. Kalkan Ç, Soykan I. The relations among serum ghrelin, motilin and gastric emptying and autonomic function in autoimmune Gastritis. Am J Med Sci. 2018;355(5):428–33. pmid:29753372
- 18. Wu W, Zhu L, Dou Z, Hou Q, Wang S, Yuan Z, et al. Ghrelin in focus: dissecting its critical roles in gastrointestinal pathologies and therapies. Curr Issues Mol Biol. 2024;46(1):948–64. pmid:38275675
- 19. Page MJ, McKenzie JE, Bossuyt PM. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;n71.
- 20. Amalia R, Miftahussurur M, Syam AF, Uchida T, Alfaray RI, Fauzia KA, et al. Parietal cell antibody levels among chronic gastritis patients in a country with low helicobacter pylori infection: epidemiology, histopathological features, and H. pylori Infection. Helicobacter. 2025;30(2):e70035. pmid:40249164
- 21. Higgins JPT, Morgan RL, Rooney AA, Taylor KW, Thayer KA, Silva RA, et al. A tool to assess risk of bias in non-randomized follow-up studies of exposure effects (ROBINS-E). Environ Int. 2024;186:108602. pmid:38555664
- 22. Aukan MI, Nymo S, Haagensli Ollestad K, Akersveen Boyesen G, DeBenedictis JN, Rehfeld JF, et al. Differences in gastrointestinal hormones and appetite ratings among obesity classes. Appetite. 2022;171:105940. pmid:35063622
- 23. Panarese A, Romiti A, Iacovazzi PA, Leone CM, Pesole PL, Correale M, et al. Relationship between atrophic gastritis, serum ghrelin and body mass index. Eur J Gastroenterol Hepatol. 2020;32(10):1335–40. pmid:32773508
- 24. Campana D, Nori F, Pagotto U, De Iasio R, Morselli-Labate AM, Pasquali R, et al. Plasma acylated ghrelin levels are higher in patients with chronic atrophic gastritis. Clin Endocrinol (Oxf). 2007;67(5):761–6. pmid:17614968
- 25. Alonso N, Granada ML, Salinas I, Reverter JL, Flores L, Ojanguren I, et al. Plasma ghrelin concentrations in type 1 diabetic patients with autoimmune atrophic gastritis. Eur J Endocrinol. 2007;157(6):763–9. pmid:18057384
- 26. Checchi S, Montanaro A, Pasqui L, Ciuoli C, Cevenini G, Sestini F, et al. Serum ghrelin as a marker of atrophic body gastritis in patients with parietal cell antibodies. J Clin Endocrinol Metab. 2007;92(11):4346–51. pmid:17711921
- 27. Gao X-Y, Kuang H-Y, Liu X-M, Ma Z-B, Nie H-J, Guo H. Plasma obestatin levels in men with chronic atrophic gastritis. Peptides. 2008;29(10):1749–54. pmid:18588931
- 28. Müller TD, Nogueiras R, Andermann ML. Ghrelin. Mol Metab. 2015;4:437–60.
- 29. Mantero P, Olid L, Giacomantone C. Decreased serum ghrelin following Helicobacter pylori eradication. Microb Health Dis. 2023;5:e950.
- 30. Tanaka-Shintani M, Watanabe M. Distribution of ghrelin-immunoreactive cells in human gastric mucosa: comparison with that of parietal cells. J Gastroenterol. 2005;40(4):345–9. pmid:15870970
- 31. Sakata I, Sakai T. Ghrelin cells in the gastrointestinal tract. Int J Pept. 2010;2010:1–7.
- 32. Sakata I, Tanaka T, Yamazaki M, Tanizaki T, Zheng Z, Sakai T. Gastric estrogen directly induces ghrelin expression and production in the rat stomach. J Endocrinol. 2006;190(3):749–57. pmid:17003276
- 33. Zhao Z, Sakata I, Okubo Y, Koike K, Kangawa K, Sakai T. Gastric leptin, but not estrogen and somatostatin, contributes to the elevation of ghrelin mRNA expression level in fasted rats. J Endocrinol. 2008;196(3):529–38. pmid:18310448
- 34. Suzuki H, Masaoka T, Hosoda H, Nomura S, Ohara T, Kangawa K, et al. Plasma ghrelin concentration correlates with the levels of serum pepsinogen I and pepsinogen I/II ratio--a possible novel and non-invasive marker for gastric atrophy. Hepatogastroenterology. 2004;51(59):1249–54. pmid:15362725
- 35. Lahner E, Conti L, Annibale B, Corleto VD. Current Perspectives in Atrophic Gastritis. Curr Gastroenterol Rep. 2020;22(8):38. pmid:32542467
- 36. Bordin DS, Livzan MA, Mozgovoi SI, Gaus OV. Autoimmune Gastritis and Helicobacter pylori Infection: Molecular Mechanisms of Relationship. Int J Mol Sci. 2025;26(16):7737. pmid:40869058
- 37. Levine TR, Asada KJ, Carpenter C. Sample sizes and effect sizes are negatively correlated in meta-analyses: evidence and implications of a publication bias against nonsignificant findings. Commun Monogr. 2009;76:286–302.
- 38. Ikezaki A, Hosoda H, Ito K, Iwama S, Miura N, Matsuoka H, et al. Fasting plasma ghrelin levels are negatively correlated with insulin resistance and PAI-1, but not with leptin, in obese children and adolescents. Diabetes. 2002;51(12):3408–11. pmid:12453893
- 39. Kotani K, Sakane N, Saiga K, Adachi S, Mu H, Kurozawa Y, et al. Serum ghrelin and carotid atherosclerosis in older Japanese people with metabolic syndrome. Arch Med Res. 2006;37(7):903–6. pmid:16971234
- 40. Nanjo Y, Adachi H, Hirai Y, Enomoto M, Fukami A, Otsuka M, et al. Factors associated with plasma ghrelin level in Japanese general population. Clin Endocrinol (Oxf). 2011;74(4):453–8. pmid:21092051
- 41. Kawaguchi T, Nagao Y, Sata M. Independent factors associated with altered plasma active ghrelin levels in HCV-infected patients. Liver Int. 2013;33(10):1510–6. pmid:23809581
- 42. Matsunaga-Irie S, Ueshima H, Zaky WR, Kadowaki T, Evans RW, Okamura T, et al. Serum ghrelin levels are higher in Caucasian men than Japanese men aged 40-49 years. Diabetes Obes Metab. 2007;9(4):591–3. pmid:17587401
- 43. Faller G, Kirchner T. Immunological and morphogenic basis of gastric mucosa atrophy and metaplasia. Virchows Arch. 2005;446(1):1–9. pmid:15583929
- 44. D’Elios MM, Appelmelk BJ, Amedei A, Bergman MP, Del Prete G. Gastric autoimmunity: the role of Helicobacter pylori and molecular mimicry. Trends Mol Med. 2004;10(7):316–23. pmid:15242679
- 45. Toh BH, Sentry JW, Alderuccio F. The causative gastric H/K ATPase autoantigen. Immunol Today.
- 46. Borén T, Falk P, Roth KA, Larson G, Normark S. Attachment of Helicobacter pylori to human gastric epithelium mediated by blood group antigens. Science. 1993;262(5141):1892–5. pmid:8018146
- 47. Chmiela M, Gonciarz W. Molecular mimicry in Helicobacter pylori infections. World J Gastroenterol. 2017;23(22):3964–77. pmid:28652651
- 48. Wang L, Cao Z-M, Zhang L-L, Dai X-C, Liu Z-J, Zeng Y-X, et al. Helicobacter Pylori and Autoimmune Diseases: Involving Multiple Systems. Front Immunol. 2022;13:833424. pmid:35222423
- 49. Amedei A, Bergman MP, Appelmelk BJ, Azzurri A, Benagiano M, Tamburini C, et al. Molecular mimicry between Helicobacter pylori antigens and H+, K+ --adenosine triphosphatase in human gastric autoimmunity. J Exp Med. 2003;198(8):1147–56. pmid:14568977