Startseite Acute pancreatitis risk in the diagnosis and management of inflammatory bowel disease: A critical focus
Artikel Open Access

Acute pancreatitis risk in the diagnosis and management of inflammatory bowel disease: A critical focus

  • Feibo Zheng , Jinan Li , Lina Ma , Yu Zhang , Zhengwei Tu und Yunfeng Cui EMAIL logo
Veröffentlicht/Copyright: 22. Mai 2025

Abstract

Objective

We explored the causal relationship between pancreatitis and various autoimmune diseases using bidirectional Mendelian randomization (MR).

Methods

We collected genome-wide association study summary data for four pancreatitis types and five autoimmune diseases to conduct our bidirectional MR analysis. The primary analysis was performed using the inverse variance weighted (IVW) method, complemented by MR Egger, weighted median, and weighted mode methods. Sensitivity analyses included Cochran’s Q test for heterogeneity, MR-Egger regression for pleiotropy, and MR-PRESSO and leave-one-out analyses for outliers.

Results

The result of IVW revealed a significant association between genetically predicted inflammatory bowel disease (IBD) and an increased risk of acute pancreatitis (AP) (odds ratio [OR] = 1.07, 95% confidence interval [CI] = 1.03–1.12, P = 0.0015). Subsequent analyses further confirmed this association in IBD subtypes, with genetically predicted ulcerative colitis (UC) and Crohn’s disease (CD) also showing increased risks of AP (UC: OR = 1.07, 95% CI = 1.02–1.13, P = 0.01; CD: OR = 1.05, 95% CI = 1–1.09, P = 0.03), affirming IBD as a risk factor for pancreatitis. Reverse analysis ruled out reverse causality and did not find a causal relationship between other immune diseases and pancreatitis.

Conclusion

These findings suggest that pancreatitis in IBD patients may arise from the disease itself, necessitating increased vigilance for AP during diagnosis and treatment.

1 Introduction

Pancreatitis is a common digestive disease worldwide and a leading cause of emergency gastrointestinal hospitalizations [1]. According to epidemiological data, in 2019, there were 2,814,972 cases of pancreatitis worldwide, resulting in 115,053 deaths [2]. In recent years, the incidence of pancreatitis has been steadily increasing, with a high mortality rate among severe cases and significant consumption of medical resources, becoming one of the major diseases that endanger people’s health and lives [2,3].

Retrospective clinical research has revealed that the onset and development of pancreatitis are strongly correlated with immunological factors and the immune system. Gastrointestinal lesions of autoimmune diseases can present as pancreatitis, and patients with this type often have a more severe condition. For example, acute pancreatitis (AP) more commonly occurs during the active phase of systemic lupus erythematosus (SLE) (89%) and the incidence of ascites, sepsis, and hypocalcemia in SLE-associated AP increases, with a mortality rate reaching over 30% [4,5]. Rheumatoid arthritis (RA) can increase the risk of acute/chronic pancreatitis (CP) [6]. Inflammatory bowel disease (IBD) patients often exhibit symptoms of pancreatitis, such as exocrine dysfunction, abnormal pancreatic ducts, and hyperamylasemia. Pancreatitis, especially type 2 autoimmune pancreatitis, is common among IBD patients [7]. Moreover, the incidence of AP has been reported to be higher in IBD patients than in the non-IBD population, with Crohn’s disease (CD) patients and ulcerative colitis (UC) patients, having a 4.1 and 2.6 times higher incidence of AP, respectively [8]. Type 1 diabetes (T1D) is an autoimmune disease where the immune system attacks the insulin-producing β cells, possibly accompanied by pancreatitis [9]. Studies indicated that autoimmune diseases could initiate or exacerbate pancreatitis by modulating immune-inflammatory responses, cytokines, lymphocyte function, and intestinal barrier function, leading to pancreatic tissue damage [10]. These clinical observational studies suggest a potential correlation between autoimmune diseases and pancreatitis. However, it is challenging to avoid confounders such as treatment approaches and medication use, which hinder the ability to establish a clear causal relationship between these diseases. In addition, reverse causality and the inability to establish a clear temporal relationship also affect the establishment of causality.

Mendelian randomization (MR) is a method for detecting potential causal relationships between exposure factors and disease outcomes, which has become increasingly popular in recent years [11]. Compared to traditional observational studies, MR utilizes genetic variations as instrumental variables (IVs). These genetic markers are randomly assorted at conception and remain largely unaffected by the environmental or lifestyle factors that typically confound observational research. By leveraging these genetic variations, MR can more reliably infer causality, avoiding the pitfalls of reverse causality. This aspect makes MR particularly valuable in providing robust evidence for the pathogenesis of diseases.

The present study focused on the potential causal relationships between various types of pancreatitis – including AP, CP, alcohol-induced AP, and alcohol-induced CP – and autoimmune diseases such as RA, SLE, IBD, CD, UC, and T1D. To clarify the directionality of the relationship between autoimmune diseases and pancreatitis, we hypothesize that autoimmune diseases may causally increase the risk of pancreatitis, while pancreatitis does not influence the risk of developing autoimmune diseases. This research aims to provide new biological diagnostic markers, treatment strategies, and a theoretical basis for further investigations into the mechanisms underlying the interaction between autoimmune diseases and pancreatitis.

2 Methods

2.1 Study design

Considering the findings above and the MR method, we downloaded genome-wide association study (GWAS) data for pancreatitis and autoimmune diseases. As shown in Figure 1, a bidirectional two-sample MR analysis was chosen to determine the causal association between pancreatitis and autoimmune diseases. Employing bidirectional MR strengthens the findings by ruling out reverse causality, thus providing robust insights into the nature of these interactions. MR operates under three critical assumptions: (1) the selected genetic IVs have a strong association with the exposure; (2) these genetic IVs are independent of any confounders that might influence both the exposure and the outcome; and (3) the effect of the genetic IVs on the outcome is exclusively mediated through the exposure, with no alternative biological pathways.

Figure 1 
                  The experimental study design: Schematic representation of MR hypothesis.
Figure 1

The experimental study design: Schematic representation of MR hypothesis.

2.2 Data sources

GWAS summary data for four types of pancreatitis were obtained from the FINNGEN database (https://www.finngen.fi/en), with 16,380,428 single-nucleotide polymorphisms (SNPs). The FINNGEN project aims to study the genetic basis and risk factors of human diseases by utilizing nationwide health records and genetic data in Finland. Precisely, the samples for AP included 3,022 cases and 195,144 controls; CP contained 1,737 cases and 195,144 controls; AP induced by alcohol comprised 457 cases and 218,335 controls; and CP induced by alcohol included 977 cases and 217,815 controls. Autoimmune diseases included six diseases, with RA GWAS data obtained from 18 European studies [12], SLE [13] GWAS data from a cohort of Europeans in 2015, IBD (including CD and UC) [14] GWAS data from a European cohort in the UK IBD Genetics Consortium and UK10K Consortium, and T1D [15] GWAS data from a meta-analysis of studies on individuals from the UK and Sardinia. Details of the GWASs included in the MR are shown in Table S1.

2.3 IV selection

The IVs incorporated in the present study were required to meet the following criteria: (1) SNPs with a robust association to the exposure were identified from the exposure GWAS. Due to the stringent P-value threshold of 5 × 10−8 not yielding a sufficient number of IVs, a P-value of <5 × 10−6 was utilized to ensure adequate coverage and strength of the genetic instruments; (2) SNPs exhibiting a minor allele frequency >0.01 were chosen; (3) to mitigate the impact of linkage disequilibrium among SNPs, SNPs were selected based on the criteria of R 2 < 0.001, window size = 10,000 kb; if the selected IV was not present in the outcome summary data, an SNP with high LD (R 2 > 0.8) with the IV was sought as a proxy SNP for replacement; and (4) the F statistics for each SNP in the IV was calculated to assess the strength of the IV, to exclude the possibility of weak IV bias between the IV and the exposure factor, with the formula for F statistics being F = R 2 × (N – 2)/(1 – R 2), requiring F statistics >10.

2.4 MR analysis

The two-sample MR analysis between exposure and outcomes was conducted via the “TwoSampleMR” R package [16]. The primary method used for analysis was the inverse variance weighted (IVW) method, which assessed the causal link between exposure and outcome risks by calculating the odds ratios (OR) and their 95% confidence interval (CI). The IVW method was used as the primary tool for interpreting MR results, calculating the weighted average of effect sizes using the inverse variance of each SNP as weights. This analysis also employed the MR-Egger, weighted median, and weighted mode methods to test the robustness of the results. The MR-Egger method provides accurate causal effect estimates in the presence of pleiotropy bias by considering the existence of an intercept term. Based on the assumption that at least half of the IVs are valid, the weighted median method analyzes the causal link between exposure and outcome. Statistical significance is determined by a P of less than 0.05.

2.5 Sensitivity analysis

In MR investigations, sensitivity analysis was used to uncover potential issues with pleiotropy. Cochran’s Q test was employed for evaluating heterogeneity across IVs, with no significant heterogeneity acknowledged if the P-value of >0.05 [17]. Potential pleiotropy was detected via the MR-Egger regression method; an intercept near zero and a P-value of >0.05 were interpreted as indications of negligible pleiotropy bias [18]. Additionally, we harnessed the MR pleiotropy residual sum and outlier (MR-PRESSO) approach to pinpoint potential outlier SNPs (those with a P-value <0.05) and adjusted for pleiotropy bias by recalculating the causal estimate post-outlier removal [19].

3 Results

3.1 Causal effects of autoimmune diseases on pancreatitis

A total of 90 SNPs related to RA, 45 SNPs related to SLE, 117 SNPs related to IBD, 89 SNPs related to CD, 62 SNPs related to UC, and 37 SNPs related to T1D were identified, serving as IVs for autoimmune diseases (Tables S2–S7). The F statistics for IVs of RA, SLE, IBD, CD, UC, and T1D were >10.

The MR analysis was conducted with AP, CP, alcohol-induced AP, and alcohol-induced CP as outcomes (Table 1). The IVW analysis indicated that IBD was a risk factor for the incidence of AP (OR = 1.07, 95% CI = 1.03–1.12, P = 0.0015). In addition, subgroup analysis showed that UC and CD were potential risk factors for the incidence of AP (UC: OR = 1.07, 95% CI = 1.02–1.13, P = 0.01; CD: OR = 1.05, 95% CI = 1–1.09, P = 0.03). The other three methods, including MR-Egger, weighted median, and weighted mode methods, showed no statistical significance (Table 1 and Figure 2). The effect size of SNPs is shown in the scatter plot and forest plot (Figures 2 and 3). In addition, no genetically causal association of RA, SLE, IBD, CD, UC, and T1D on CP, alcohol-induced AP, or alcohol-induced CP was found.

Table 1

The causal relationship between four pancreatitis exposures and six autoimmune diseases as outcomes using MR

Outcome Exposure N. SNPs Methods OR (95% CI) P
Acute pancreatitis RA 85 IVW 1 (0.95–1.04) 0.90
MR Egger 0.95 (0.89–1.01) 0.13
Weighted median 1.01 (0.94–1.08) 0.77
Weighted mode 0.97 (0.91–1.02) 0.24
SLE 44 IVW 1 (0.97–1.03) 0.98
MR Egger 0.98 (0.91–1.05) 0.54
Weighted median 1 (0.95–1.04) 0.90
Weighted mode 1.01 (0.95–1.08) 0.71
IBD 113 IVW 1.07 (1.03–1.12) 0.0015
MR Egger 1.04 (0.96–1.12) 0.32
Weighted median 1.05 (0.97–1.14) 0.22
Weighted mode 1.04 (0.98–1.12) 0.22
CD 84 IVW 1.05 (1–1.09) 0.03
MR Egger 1.08 (0.96–1.21) 0.19
Weighted median 1.03 (0.96–1.09) 0.43
Weighted mode 0.98 (0.87–1.1) 0.71
UC 58 IVW 1.07 (1.02–1.13) 0.01
MR Egger 1.16 (0.99–1.36) 0.08
Weighted median 1.07 (0.99–1.16) 0.08
Weighted mode 1.05 (0.93–1.18) 0.46
T1D 34 IVW 1.01 (0.99–1.03) 0.37
MR Egger 1.01 (0.98–1.05) 0.39
Weighted median 1.02 (0.99–1.06) 0.15
Weighted mode 1.02 (0.99–1.04) 0.24
Chronic pancreatitis RA 85 IVW 1.02 (0.96–1.08) 0.48
MR Egger 1.03 (0.94–1.12) 0.58
Weighted median 1.08 (0.99–1.18) 0.07
Weighted mode 1.07 (0.99–1.16) 0.09
SLE 44 IVW 0.99 (0.95–1.03) 0.53
MR Egger 0.97 (0.89–1.07) 0.57
Weighted median 0.98 (0.93–1.04) 0.60
Weighted mode 0.97 (0.91–1.04) 0.38
IBD 113 IVW 1.01 (0.96–1.07) 0.63
MR Egger 0.89 (0.81–0.98) 0.02
Weighted median 0.93 (0.84–1.01) 0.10
Weighted mode 0.94 (0.85–1.04) 0.21
CD 84 IVW 1.06 (1–1.11) 0.05
MR Egger 0.98 (0.85–1.14) 0.80
Weighted median 1.03 (0.95–1.13) 0.43
Weighted mode 1.03 (0.92–1.16) 0.59
UC 58 IVW 1.01 (0.94–1.08) 0.76
MR Egger 0.8 (0.65–0.99) 0.04
Weighted median 0.94 (0.85–1.05) 0.28
Weighted mode 0.92 (0.78–1.1) 0.38
T1D 34 IVW 1.01 (0.97–1.04) 0.68
MR Egger 1.01 (0.96–1.06) 0.79
Weighted median 1.04 (1–1.08) 0.07
Weighted mode 1.03 (1–1.07) 0.10
Alcohol-induced acute pancreatitis RA 85 IVW 0.99 (0.89–1.09) 0.78
MR Egger 0.91 (0.77–1.06) 0.23
Weighted median 0.93 (0.78–1.1) 0.40
Weighted mode 0.9 (0.78–1.04) 0.15
SLE 44 IVW 0.95 (0.88–1.02) 0.17
MR Egger 0.97 (0.82–1.15) 0.73
Weighted median 0.92 (0.82–1.03) 0.16
Weighted mode 0.91 (0.78–1.06) 0.22
IBD 113 IVW 1.02 (0.91–1.13) 0.76
MR Egger 1.02 (0.85–1.23) 0.81
Weighted median 1 (0.82–1.22) 0.99
Weighted mode 1.02 (0.85–1.22) 0.86
CD 84 IVW 1 (0.9–1.11) 0.94
MR Egger 1.15 (0.86–1.52) 0.35
Weighted median 0.99 (0.84–1.15) 0.85
Weighted mode 0.99 (0.79–1.25) 0.94
UC 58 IVW 1.11 (0.97–1.26) 0.14
MR Egger 1.29 (0.86–1.93) 0.22
Weighted median 1.15 (0.94–1.4) 0.18
Weighted mode 1.2 (0.87–1.64) 0.27
T1D 34 IVW 0.96 (0.91–1.02) 0.20
MR Egger 0.96 (0.89–1.04) 0.31
Weighted median 0.98 (0.91–1.06) 0.67
Weighted mode 0.97 (0.91–1.03) 0.31
RA 85 IVW 0.98 (0.91–1.05) 0.59
MR Egger 0.97 (0.87–1.08) 0.59
Weighted median 1 (0.89–1.11) 0.94
Weighted mode 0.98 (0.89–1.08) 0.73
SLE 44 IVW 0.97 (0.92–1.02) 0.25
MR Egger 0.97 (0.86–1.08) 0.56
Weighted median 1 (0.92–1.08) 0.97
Weighted mode 1.02 (0.92–1.13) 0.71
IBD 113 IVW 0.99 (0.92–1.07) 0.81
MR Egger 0.9 (0.79–1.03) 0.13
Weighted median 1 (0.88–1.15) 0.94
Weighted mode 0.96 (0.85–1.08) 0.49
CD 84 IVW 1.03 (0.95–1.12) 0.43
MR Egger 0.9 (0.73–1.12) 0.36
Weighted median 1 (0.9–1.11) 0.99
Weighted mode 0.96 (0.81–1.12) 0.59
UC 58 IVW 0.95 (0.86–1.04) 0.23
MR Egger 0.7 (0.53–0.92) 0.01
Weighted median 0.87 (0.75–0.99) 0.04
Weighted mode 0.85 (0.69–1.05) 0.15
T1D 34 IVW 0.96 (0.92–1.01) 0.09
MR Egger 0.97 (0.91–1.03) 0.38
Weighted median 1 (0.94–1.05) 0.91
Weighted mode 0.98 (0.93–1.03) 0.49
RA Acute pancreatitis 6 IVW 1.1 (0.98–1.24) 0.10
MR Egger 1.24 (1–1.53) 0.12
Weighted median 1.09 (0.95–1.26) 0.23
Weighted mode 1.1 (0.9–1.34) 0.40
Chronic pancreatitis 12 IVW 1 (0.95–1.05) 0.98
MR Egger 0.94 (0.82–1.08) 0.43
Weighted median 0.98 (0.92–1.05) 0.52
Weighted mode 0.96 (0.87–1.06) 0.45
Alcohol-induced acute pancreatitis 7 IVW 1.02 (0.99–1.05) 0.23
MR Egger 1 (0.96–1.05) 0.97
Weighted median 1.01 (0.97–1.04) 0.76
Weighted mode 1 (0.97–1.04) 0.80
Alcohol-induced chronic pancreatitis 9 IVW 1.01 (0.95–1.07) 0.83
MR Egger 1.15 (0.99–1.33) 0.12
Weighted median 0.98 (0.92–1.05) 0.58
Weighted mode 0.97 (0.89–1.07) 0.57
SLE Acute pancreatitis 6 IVW 1.06 (0.89–1.25) 0.53
MR Egger 1.05 (0.76–1.45) 0.77
Weighted median 1.04 (0.84–1.3) 0.72
Weighted mode 1.05 (0.77–1.44) 0.75
Chronic pancreatitis 7 IVW 1.11 (0.95–1.3) 0.19
MR Egger 1.34 (0.83–2.16) 0.28
Weighted median 1.17 (0.98–1.39) 0.08
Weighted mode 1.18 (0.92–1.51) 0.23
Alcohol-induced acute pancreatitis 7 IVW 1 (0.94–1.06) 0.97
MR Egger 1 (0.9–1.1) 0.97
Weighted median 1 (0.93–1.08) 0.94
Weighted mode 1 (0.93–1.08) 0.91
Alcohol-induced chronic pancreatitis 6 IVW 0.96 (0.86–1.07) 0.47
MR Egger 1.05 (0.84–1.3) 0.70
Weighted median 0.91 (0.78–1.06) 0.22
Weighted mode 0.89 (0.71–1.12) 0.35
IBD Acute pancreatitis 8 IVW 0.98 (0.92–1.04) 0.51
MR Egger 0.94 (0.85–1.04) 0.25
Weighted median 0.97 (0.9–1.06) 0.55
Weighted mode 0.92 (0.82–1.03) 0.18
Chronic pancreatitis 10 IVW 1.01 (0.96–1.05) 0.78
MR Egger 1.11 (0.98–1.26) 0.15
Weighted median 1.03 (0.97–1.09) 0.35
Weighted mode 1.05 (0.95–1.16) 0.38
Alcohol-induced acute pancreatitis 8 IVW 0.97 (0.95–1) 0.09
MR Egger 0.99 (0.95–1.04) 0.72
Weighted median 0.98 (0.95–1.01) 0.12
Weighted mode 0.98 (0.96–1.01) 0.22
Alcohol-induced chronic pancreatitis 6 IVW 1.03 (0.99–1.07) 0.20
MR Egger 1.08 (0.99–1.18) 0.15
Weighted median 1.01 (0.96–1.07) 0.67
Weighted mode 1 (0.94–1.08) 0.93
CD Acute pancreatitis 8 IVW 0.96 (0.89–1.04) 0.31
MR Egger 0.96 (0.85–1.09) 0.57
Weighted median 0.98 (0.89–1.08) 0.63
Weighted mode 0.97 (0.87–1.09) 0.66
Chronic pancreatitis 10 IVW 1 (0.94–1.06) 0.96
MR Egger 1.05 (0.89–1.23) 0.60
Weighted median 1.01 (0.93–1.09) 0.89
Weighted mode 1.04 (0.93–1.17) 0.52
Alcohol-induced acute pancreatitis 8 IVW 0.97 (0.94–1) 0.05
MR Egger 0.99 (0.95–1.04) 0.76
Weighted median 0.98 (0.95–1.01) 0.29
Weighted mode 0.99 (0.96–1.02) 0.49
Alcohol-induced chronic pancreatitis 6 IVW 1.03 (0.96–1.1) 0.43
MR Egger 1.1 (0.96–1.25) 0.25
Weighted median 1 (0.93–1.08) 0.99
Weighted mode 0.99 (0.92–1.08) 0.90
UC Acute pancreatitis 8 IVW 0.98 (0.9–1.07) 0.61
MR Egger 0.92 (0.8–1.06) 0.28
Weighted median 0.94 (0.85–1.05) 0.29
Weighted mode 0.91 (0.78–1.05) 0.22
Chronic pancreatitis 10 IVW 0.99 (0.94–1.05) 0.77
MR Egger 1.1 (0.93–1.29) 0.29
Weighted median 1.02 (0.95–1.11) 0.55
Weighted mode 1.04 (0.92–1.18) 0.51
Alcohol-induced acute pancreatitis 8 IVW 0.98 (0.95–1.01) 0.21
MR Egger 0.98 (0.93–1.04) 0.56
Weighted median 0.97 (0.94–1) 0.09
Weighted mode 0.97 (0.93–1) 0.10
Alcohol-induced chronic pancreatitis 6 IVW 1.02 (0.97–1.08) 0.45
MR Egger 1.06 (0.95–1.19) 0.33
Weighted median 1.04 (0.97–1.11) 0.33
Weighted mode 1.05 (0.96–1.16) 0.34
T1D Acute pancreatitis 8 IVW 1.02 (0.89–1.18) 0.74
MR Egger 1.12 (0.83–1.51) 0.51
Weighted median 1.06 (0.88–1.26) 0.56
Weighted mode 1.07 (0.86–1.33) 0.58
Chronic pancreatitis 10 IVW 1.01 (0.93–1.09) 0.90
MR Egger 1.04 (0.83–1.31) 0.71
Weighted median 1.01 (0.91–1.12) 0.82
Weighted mode 1.02 (0.87–1.18) 0.85
Alcohol-induced acute pancreatitis 8 IVW 0.97 (0.94–1.01) 0.15
MR Egger 1 (0.95–1.05) 0.94
Weighted median 0.98 (0.94–1.03) 0.48
Weighted mode 0.98 (0.94–1.03) 0.45
Alcohol-induced chronic pancreatitis 6 IVW 1.04 (0.97–1.13) 0.27
MR Egger 1.03 (0.87–1.21) 0.75
Weighted median 1.03 (0.93–1.14) 0.57
Weighted mode 1.04 (0.91–1.19) 0.62

Note: RA: rheumatoid arthritis; SLE: systemic lupus erythematosus; IBD: inflammatory bowel disease; CD: Crohn’s disease; UC: ulcerative colitis; T1D: type 1 diabetes.

Figure 2 
                  Scatter plots of MR analysis: (a) IBD on acute pancreatitis; (b) UC on acute pancreatitis; (c) CD on acute pancreatitis. The slope of each line represents the causal effect estimated by IVW, MR Egger, weighted median, weight mode, and simple mode methods. MR, Mendelian randomization; SNPs, single-nucleotide polymorphisms.
Figure 2

Scatter plots of MR analysis: (a) IBD on acute pancreatitis; (b) UC on acute pancreatitis; (c) CD on acute pancreatitis. The slope of each line represents the causal effect estimated by IVW, MR Egger, weighted median, weight mode, and simple mode methods. MR, Mendelian randomization; SNPs, single-nucleotide polymorphisms.

Figure 3 
                  Funnel of MR analysis: (a) IBD on acute pancreatitis; (b) UC on acute pancreatitis; and (c) CD on acute pancreatitis. The symmetry of the funnel plots indicates the absence of heterogeneity among the SNPs.
Figure 3

Funnel of MR analysis: (a) IBD on acute pancreatitis; (b) UC on acute pancreatitis; and (c) CD on acute pancreatitis. The symmetry of the funnel plots indicates the absence of heterogeneity among the SNPs.

Cochran’s Q test and MR-Egger regression revealed no heterogeneity and horizontal pleiotropy for IBD, UC, and CD in CP (P > 0.05). Leave-one-out analysis indicated that the causal estimates of IBD, UC, and CD and subtypes were not driven by any single SNP. The leave-one-out analysis plots, forest plots, and funnel plots are shown in Figures 35. Moreover, there was no heterogeneity between the individual SNP in most other autoimmune diseases but heterogeneity for T1D in CP (Q = 49.67; P = 0.03). The MR-Egger regression results indicated that the analyses of CP and IBD (P = 0.002), alcohol-induced AP and UC (P = 0.028), and alcohol-induced CP and UC (P = 0.03) were affected by horizontal pleiotropy (Table 2). However, the leave-one-out and MR-PRESSO did not show any outliers for these three pairs of exposure and outcome (Table 3). MR-PRESSO verification of the causal effect of IBD, UC, and CD on AP (IBD: OR = 1.07 95% CI = 1.03–1.11, P = 0.002; UC: OR = 1.07 95% CI = 1.02–1.11, P = 0.005; CD: OR = 1.04 95% CI = 1.00–1.09, P = 0.04) (Table 3).

Figure 4 
                  Forest of MR analysis: (a) IBD on acute pancreatitis; (b) UC on acute pancreatitis; and (c) CD on acute pancreatitis. The forest plots show each SNP MR estimate and 95% CI values (gray line segment). CI, confidence interval; IVW, inverse variance weighted; MR, Mendelian randomization; SNPs, single-nucleotide polymorphisms.
Figure 4

Forest of MR analysis: (a) IBD on acute pancreatitis; (b) UC on acute pancreatitis; and (c) CD on acute pancreatitis. The forest plots show each SNP MR estimate and 95% CI values (gray line segment). CI, confidence interval; IVW, inverse variance weighted; MR, Mendelian randomization; SNPs, single-nucleotide polymorphisms.

Figure 5 
                  Leave-one-out analysis of MR analysis. The leave-one-out plots show the MR estimate and 95% CI values after removing the corresponding single SNP. (a) IBD on acute pancreatitis; (b) UC on acute pancreatitis; and (c) CD on acute pancreatitis.
Figure 5

Leave-one-out analysis of MR analysis. The leave-one-out plots show the MR estimate and 95% CI values after removing the corresponding single SNP. (a) IBD on acute pancreatitis; (b) UC on acute pancreatitis; and (c) CD on acute pancreatitis.

Table 2

Heterogeneity and pleiotropy between four pancreatitis and six autoimmune diseases

Outcome Exposure Heterogeneity Pleiotropy
Q statistic (IVW) P value MR-Egger intercept P value
Acute pancreatitis RA 102.38 0.08 0.01 0.06
SLE 44.95 0.39 0.01 0.48
IBD 113.06 0.45 0.01 0.33
CD 76.56 0.68 −0.01 0.58
UC 40.85 0.95 −0.01 0.34
T1D 36.17 0.32 −0.002 0.77
Chronic pancreatitis RA 105.21 0.06 0.008 0.90
SLE 44.55 0.41 0.005 0.75
IBD 112.25 0.48 0.021 0.002
CD 67.79 0.89 0.01 0.30
UC 45.50 0.86 0.04 0.03
T1D 49.67 0.03 0.0007 0.96
Alcohol-induced acute pancreatitis RA 90.58 0.29 0.019 0.18
SLE 35.87 0.77 −0.009 0.76
IBD 114.92 0.41 −0.001 0.93
CD 79.69 0.58 −0.022 0.33
UC 44.34 0.89 −0.025 0.43
T1D 26.84 0.77 0.002 0.92
Alcohol-induced chronic pancreatitis RA 85.13 0.46 0.002 0.80
SLE 39.18 0.64 0.002 0.94
IBD 127.28 0.15 0.016 0.09
CD 101.73 0.08 0.023 0.20
UC 49.72 0.74 0.049 0.028
T1D 46.53 0.06 −0.009 0.57
RA Acute pancreatitis 6.38 0.27 −0.025 0.28
Chronic pancreatitis 10.78 0.46 0.012 0.40
Alcohol-induced acute pancreatitis 2.17 0.91 0.010 0.44
Alcohol-induced chronic pancreatitis 11.17 0.19 −0.038 0.12
SLE Acute pancreatitis 4.19 0.52 8.72 × 10−4 0.97
Chronic pancreatitis 9.48 0.15 −0.04 0.45
Alcohol-induced acute pancreatitis 6.95 0.33 3.71 × 10−4 0.99
Alcohol-induced chronic pancreatitis 4.13 0.53 −0.033 0.41
IBD Acute pancreatitis 7.60 0.37 0.013 0.32
Chronic pancreatitis 6.32 0.71 −0.02 0.15
Alcohol-induced acute pancreatitis 16.53 0.02 −0.017 0.37
Alcohol-induced chronic pancreatitis 5.06 0.41 −0.02 0.27
CD Acute pancreatitis 2.96 0.89 −4.31 × 10−4 0.98
Chronic pancreatitis 5.69 0.77 −0.009 0.59
Alcohol-induced acute pancreatitis 11.09 0.13 −0.024 0.18
Alcohol-induced chronic pancreatitis 7.44 0.19 −0.027 0.34
UC Acute pancreatitis 8.83 0.27 0.02 0.31
Chronic pancreatitis 6.17 0.72 −0.02 0.22
Alcohol-induced acute pancreatitis 12.32 0.09 −0.004 0.82
Alcohol-induced chronic pancreatitis 3.07 0.69 −0.017 0.45
T1D Acute pancreatitis 1.83 0.77 −0.02 0.55
Chronic pancreatitis 3.96 0.91 −0.008 0.73
Alcohol-induced acute pancreatitis 7.76 0.35 −0.028 0.18
Alcohol-induced chronic pancreatitis 4.62 0.46 0.006 0.85

Note: RA: rheumatoid arthritis; SLE: systemic lupus erythematosus; IBD: inflammatory bowel disease; CD: Crohn’s disease; UC: ulcerative colitis; T1D: type 1 diabetes.

Table 3

Testing Pleiotropy of four pancreatitis and six autoimmune diseases using MRPRESSO

Exposure Outcome Raw Outlier corrected Global P Number of outliers Distortion P
OR (CI%) P OR (CI%) P
RA Acute pancreatitis 1 (0.95–1.04) 0.91 NA NA 0.09 NA NA
SLE Acute pancreatitis 1 (0.97–1.03) 0.94 NA NA 0.38 NA NA
IBD Acute pancreatitis 1.07 (1.03–1.11) 0.002 NA NA 0.50 NA NA
CD Acute pancreatitis 1.04 (1.00–1.09) 0.04 NA NA 0.65 NA NA
UC Acute pancreatitis 1.07 (1.02–1.11) 0.005 NA NA 0.97 NA NA
T1D Acute pancreatitis 1.01 (0.99–1.04) 0.28 NA NA 0.19 NA NA
RA Chronic pancreatitis 1.02 (0.96–1.08) 0.58 NA NA 0.04 NA NA
SLE Chronic pancreatitis 0.99 (0.95–1.03) 0.54 NA NA 0.45 NA NA
IBD Chronic pancreatitis 1.01 (0.96–1.07) 0.68 NA NA 0.45 NA NA
CD Chronic pancreatitis 1.05 (1–1.11) 0.03 NA NA 0.92 NA NA
UC Chronic pancreatitis 1 (0.94–1.06) 0.91 NA NA 0.89 NA NA
T1D Chronic pancreatitis 1.01 (0.97–1.05) 0.61 NA NA 0.05 NA NA
RA Alcohol-induced acute pancreatitis 0.98 (0.88–1.09) 0.71 NA NA 0.29 NA NA
SLE Alcohol-induced acute pancreatitis 0.95 (0.88–1.02) 0.13 NA NA 0.80 NA NA
IBD Alcohol-induced acute pancreatitis 1.01 (0.91–1.12) 0.86 NA NA 0.39 NA NA
CD Alcohol-induced acute pancreatitis 1.01 (0.91–1.11) 0.90 NA NA 0.64 NA NA
UC Alcohol-induced acute pancreatitis 1.09 (0.97–1.22) 0.16 NA NA 0.87 NA NA
T1D Alcohol-induced acute pancreatitis 0.97 (0.92–1.01) 0.17 NA NA 0.78 NA NA
RA Alcohol-induced chronic pancreatitis 0.98 (0.91–1.05) 0.56 NA NA 0.47 NA NA
SLE Alcohol-induced chronic pancreatitis 0.97 (0.92–1.02) 0.25 NA NA 0.65 NA NA
IBD Alcohol-induced chronic pancreatitis 0.99 (0.92–1.07) 0.79 NA NA 0.19 NA NA
CD Alcohol-induced chronic pancreatitis 1.04 (0.96–1.12) 0.36 NA NA 0.084 NA NA
UC Alcohol-induced chronic pancreatitis 0.94 (0.87–1.02) 0.15 NA NA 0.81 NA NA
T1D Alcohol-induced chronic pancreatitis 0.96 (0.92–1.01) 0.12 NA NA 0.08 NA NA
Acute pancreatitis RA 1.08 (0.98–1.20) 0.17 NA NA 0.36 NA NA
Chronic pancreatitis RA 1 (0.95–1.05) 0.98 NA NA 0.46 NA NA
Alcohol-induced acute pancreatitis RA 1.01 (1–1.03) 0.13 NA NA 0.92 NA NA
Alcohol-induced chronic pancreatitis RA 1.01 (0.95–1.07) 0.83 NA NA 0.22 NA NA
Acute pancreatitis SLE 1 (0.86–1.15) 0.96 NA NA 0.36 NA NA
Chronic pancreatitis SLE 1.11 (0.99–1.25) 0.12 NA NA 0.32 NA NA
Alcohol-induced acute pancreatitis SLE 1 (0.94–1.06) 0.99 NA NA 0.29 NA NA
Alcohol-induced chronic pancreatitis SLE 1.01 (0.92–1.09) 0.91 NA NA 0.49 NA NA
Acute pancreatitis IBD 0.97 (0.91–1.03) 0.34 NA NA 0.33 NA NA
Chronic pancreatitis IBD 1.02 (0.98–1.05) 0.32 NA NA 0.74 NA NA
Alcohol-induced acute pancreatitis IBD 0.98 (0.95–1.01) 0.18 NA NA 0.06 NA NA
Alcohol-induced chronic pancreatitis IBD 1.03 (1–1.06) 0.13 NA NA 0.62 NA NA
Acute pancreatitis CD 0.95 (0.91–0.99) 0.05 NA NA 0.96 NA NA
Chronic pancreatitis CD 1.02 (0.97–1.08) 0.40 NA NA 0.49 NA NA
Alcohol-induced acute pancreatitis CD 0.98 (0.95–1.01) 0.16 NA NA 0.19 NA NA
Alcohol-induced chronic pancreatitis CD 1.03 (0.98–1.08) 0.25 NA NA 0.46 NA NA
Acute pancreatitis UC 0.97 (0.88–1.06) 0.52 NA NA 0.07 NA NA
Chronic pancreatitis UC 0.99 (0.96–1.04) 0.80 NA NA 0.81 NA NA
Alcohol-induced acute pancreatitis UC 0.98 (0.95–1.01) 0.19 NA NA 0.29 NA NA
Alcohol-induced chronic pancreatitis UC 1.02 (0.99–1.06) 0.29 NA NA 0.81 NA NA
Acute pancreatitis T1D 1.01 (0.94–1.1) 0.76 NA NA 0.85 NA NA
Chronic pancreatitis T1D 1.01 (0.97–1.05) 0.63 NA NA 0.99 NA NA
Alcohol-induced acute pancreatitis T1D 0.97 (0.94–1.01) 0.15 NA NA 0.47 NA NA
Alcohol-induced chronic pancreatitis T1D 1.02 (0.96–1.08) 0.59 NA NA 0.56 NA NA

3.2 Causal effects of pancreatitis on autoimmune diseases

A total of 11 SNPs related to AP, 14 SNPs related to CP, 11 SNPs related to alcohol-induced AP, and 10 SNPs related to alcohol-induced CP were identified. All the F-statistic values were >10 (Tables S8–S11).

The MR analysis was conducted with RA, SLE, IBD, CD, UC, and T1D as outcomes (Table 1). The IVW analysis showed no significant association causal relationship between these six types of autoimmune disease risks and AP, CP, alcohol-induced AP, or alcohol-induced CP. Further MR analyses, including MR-Egger analysis, weighted median analysis, and weighted mode analysis, also detected no significant association between autoimmune disease risks and pancreatitis (all P > 0.05).

The Cochrane Q statistics in IVW and MR-Egger methods disclosed no marked heterogeneity (P > 0.05), and the MR-Egger regression showed an absence of pleiotropy (P > 0.05) (Table 2). To affirm the reliability of these conclusions, a “leave-one-out” sensitivity test was conducted, revealing that the causal association was not reliant on any single SNP. The MR-PRESSO test uncovered no evidence of horizontal pleiotropy (Table 3).

4 Discussion

The present study used a two-sample MR analysis to evaluate the potential causal relationships between AP/CP and six autoimmune diseases. Our findings revealed a significant genetic correlation between IBD and the risk of developing AP, as well as UC and AP, CD, and AP, However, no genetically causal relationships were found between other autoimmune diseases (RA, SLE, and T1D) and pancreatitis. The reverse MR analysis did not identify any causal links from pancreatitis to these autoimmune diseases. Sensitivity analyses further solidified the robustness of these discoveries.

Furthermore, a study based on 4,223 patients with IBD-associated AP suggested a strong association between IBD medications such as thiopurines, 6-mercaptopurine, and 5-aminosalicylic acid with the incidence of AP [20]. Notably, the increased risk of AP associated with thiopurine use was notably higher than that in UC. Thiopurine has also been recognized as a key trigger for AP, with approximately 5% of IBD patients developing AP [21]. These findings highlight that medications used in the treatment of IBD can also elevate the risk of AP. These effects may affect the effect of IBD on pancreatitis in observational studies. A recent meta-analysis reported that patients with IBD have an increased risk of developing AP (hazard ratio [HR]: 2.78, 95% CI: 2.40–3.22), with CD (HR: 3.62, 95% CI: 2.99–4.38) having a higher risk than UC (HR: 2.24, 95% CI: 1.85–2.71) [22]. Our study identified a similar trend; however, we did not observe a significantly higher risk of CD compared to UC. This discrepancy may be due to differences in common treatment approaches for these conditions. Moreover, a cohort time analysis indicates that within the first year following an IBD diagnosis, 85% of pediatric IBD patients and 69% of adult IBD patients develop pancreatitis and pancreatitis occurs most commonly at the time of the initial IBD diagnosis, with an incidence rate ranging from 9.3 to 16.2% across all IBD cohorts [23]. These findings suggest that pancreatitis in IBD patients may not solely be a consequence of medication side effects but might also be directly influenced by the adverse effects of intestinal inflammation on the pancreas. Integrating these insights with our results suggests that there should be a heightened vigilance for AP from the onset of IBD diagnosis, with careful use of medications to mitigate the increased risk.

The association between IBD and AP is multifaceted, involving shared inflammatory pathways, the gut–pancreas axis, medication-related impacts, and gut microbiome dysbiosis. Both conditions may share pro-inflammatory cytokines, such as IL-33 and TNF-α, which intensify inflammation and predispose individuals to pancreatitis [24]. The anatomical and functional relationship known as the gut–pancreas axis further facilitates the spread of inflammation from the gastrointestinal tract to the pancreas, enhancing localized immune responses [25]. Additionally, medications used in IBD treatment, like immunosuppressants and anti-inflammatory drugs including thiopurines and 5-aminosalicylic acid, can increase pancreatitis risk due to adverse effects [26]. Alterations in the gut microbiome, a common occurrence in IBD, also contribute to pancreatitis by disrupting immune regulation and increasing intestinal permeability [27]. Our research emphasizes that these interactions predominantly increase the risk of AP, triggered by rapid shifts in gut microbiota or acute cytokine release, distinguishing it from chronic forms of the disease. Although our study identifies a genetic causal relationship between IBD and pancreatitis, it is important to note that in clinical practice, pancreatitis may be drug-induced. Clinicians must differentiate whether pancreatitis is caused by medications or is a direct manifestation of IBD itself, to implement personalized medical treatment. This complex interplay underscores the critical need for careful management and monitoring of IBD to mitigate the risk of developing acute pancreatitis.

Although we did not detect a causal relationship between acute/CP and RA, SLE, or T1D, multiple studies have suggested a high correlation between the diseases. A cohort study analyzing 29,755 RA patients in Taiwan found that RA patients had a higher risk of AP with an HR of 1.62 (95% CI: 1.43–1.83). Oral corticosteroids were found to reduce the risk of AP (HR: 0.83, 95% CI: 0.73–0.94), whereas antirheumatic drugs or tumor necrosis factor blockers did not reduce the risk [28]. A recent study based on a multicenter database in the United States (including 518,280 RA patients) found that RA patients were more likely to develop AP (OR: 2.51; 95% CI: 2.41–2.60) and CP (OR: 2.97; 95% CI: 2.70–3.26) [6]. Observational cohorts have confirmed that SLE patients can develop AP, which is closely related to the activity level of SLE [29]. An independent cohort study found that children with T1D had increased lipopolysaccharide production by intestinal microbiota, exacerbating pancreatic inflammatory responses [30]. Conversely, a meta-analysis showed that T1D could be induced several years after the occurrence of acute or CP [31], suggesting a potential relationship between pancreatitis and T1D.

Previous observational studies have suggested a close linkage between autoimmune disorders such as RA, SLE, CD, UC, IBD, and T1D with the onset of pancreatitis. However, these diseases employ distinct immune pathways which may not impact the pancreas directly in the same manner. Genetic factors associated with these autoimmune diseases might not significantly overlap with those influencing the development of pancreatitis, explaining the absence of observed causal relationships in our findings. Furthermore, we engaged genetic instruments specifically tied to AP, CP, and their alcohol-induced counterparts for MR analysis. The outcomes divulged no causal correlation between autoimmune maladies and alcohol-driven pancreatitis manifestations. Existing studies suggest that while alcohol exacerbates systemic inflammation, thereby aggravating both acute and chronic forms of pancreatitis and acting as a risk element for autoimmune diseases [32], its impact on pancreatitis may not be mediated directly through autoimmune pathways. Furthermore, alcohol consumption has been flagged as a protective agent against autoimmune conditions like RA and SLE, with animal models demonstrating the capacity of alcohol exposure to modulate helper T cell functionality, leading to induced immune tolerance [33,34]. Although our findings did not detect a genetically causal association between the six autoimmune diseases and alcohol-induced pancreatitis, the extent to which alcohol exposure through autoimmune disease-mediated disruption in immune activity exacerbates pancreatitis severity remains an avenue for future experimental inquiry.

The present study has several advantages. First, it is the first study to utilize MR to explore the genetic causal relationships between pancreatitis and autoimmune diseases. We procured statistical data on four subtypes of pancreatitis and six autoimmune diseases, facilitating a comprehensive evaluation of the causal relationships between them. Furthermore, using bidirectional MR analysis ensures the inference of bidirectional causal relationships between pancreatitis and autoimmune diseases. However, this study also has some limitations. Primarily, the study population consisted of individuals of European descent, leaving the applicability of these findings to other races open for validation. Additionally, the P-value of the screening is 5 × 10−6, which may bias the results, but in the present study, the IV F-statistics were all >10, minimizing bias as much as possible. Third, there might be an overlap between the populations studied for exposure and outcomes could also somewhat impact the MR analysis.

5 Conclusions

Our findings demonstrated a genetically causal effect of IBD on AP. This that pancreatitis in clinical IBD patients may solely be a direct consequence of the inflammatory disease itself. These findings emphasize the need for clinical vigilance regarding pancreatitis in the diagnosis and management of IBD patients, beyond the scope of medication effects alone. The results of this study should be further validated based on larger-scale GWAS summary data, more advanced MR analysis methods, and more genetic instruments.


# These authors contributed equally to this work.

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Acknowledgments

The authors would like to thank all researchers for sharing the GWAS meta-analysis data related to exposures and outcomes.

  1. Funding information: This project was supported by China Medical and Health Development Foundation, Young and Middle-aged Doctors Excellent Talent, Pei Ying Program, Clinical study on prevention and treatment of exocrine pancreatic insufficiency associated with severe acute pancreatitis (BJ2023YCPYJH003); Tianjin Nankai Hospital integrated Traditional Chinese and Western medicine prevention and treatment key technology and program optimization 2022 key project, A multi-omics study of the microenvironment of abdominal inflammation in acute pancreatitis based on minimally invasive individualized integrated traditional Chinese and Western Medicine surgical treatment system (NKYY-IIT-2022-009-2); Tianjin key areas of traditional Chinese medicine science and technology project, Clinical study of combined treatment of TCM and Western medicine with pancreato-intestinal therapy based on peritoneal microecology in the treatment of acute pancreatitis (2022005); Tianjin Natural Science Foundation key project, Establishment of individualized surgical treatment system for severe acute pancreatitis and intelligent evaluation of multimodal imaging (21JCZDJC00550); and Hebei Province Administration of Traditional Chinese Medicine fund of Science Research, Study on the mechanism of remodeling the microenvironment of abdominal inflammation in acute pancreatitis by the effective components of Qingyi Decoction based on the regulation of apoptotic EVs derived from MSCs in adipose (T2025036) and Tianjin 131 innovative talent team, innovation team for Diagnosis and treatment of acute abdomen related to biliary and pancreatic diseases (201938).

  2. Author contributions: Yunfeng Cui conceived, designed, and supervised the project. Feibo Zheng, Jinan Li, and Lina Ma carried out the studies, participated in collecting data, and drafted the manuscript. Yu Zhang and Zhengwei Tu performed the statistical analysis and participated in its design. Feibo Zheng, Jinan Li, and Lina Ma participated in the acquisition, analysis, or interpretation of data and drafted the manuscript. All authors read and approved the final manuscript.

  3. Conflict of interest: The authors state no conflict of interest.

  4. Data availability statement: All data generated or analyzed during this study are included in this published article.

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Received: 2024-09-29
Revised: 2025-01-02
Accepted: 2025-03-27
Published Online: 2025-05-22

© 2025 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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  35. Impact of Kolb’s experiential learning theory-based nursing on caregiver burden and psychological state of caregivers of dementia patients
  36. Analysis of serum NLR combined with intraoperative margin condition to predict the prognosis of cervical HSIL patients undergoing LEEP surgery
  37. Commiphora gileadensis ameliorate infertility and erectile dysfunction in diabetic male mice
  38. The correlation between epithelial–mesenchymal transition classification and MMP2 expression of circulating tumor cells and prognosis of advanced or metastatic nasopharyngeal carcinoma
  39. Tetrahydropalmatine improves mitochondrial function in vascular smooth muscle cells of atherosclerosis in vitro by inhibiting Ras homolog gene family A/Rho-associated protein kinase-1 signaling pathway
  40. A cross-sectional study: Relationship between serum oxidative stress levels and arteriovenous fistula maturation in maintenance dialysis patients
  41. A comparative analysis of the impact of repeated administration of flavan 3-ol on brown, subcutaneous, and visceral adipose tissue
  42. Identifying early screening factors for depression in middle-aged and older adults: A cohort study
  43. Perform tumor-specific survival analysis for Merkel cell carcinoma patients undergoing surgical resection based on the SEER database by constructing a nomogram chart
  44. Unveiling the role of CXCL10 in pancreatic cancer progression: A novel prognostic indicator
  45. High-dose preoperative intraperitoneal erythropoietin and intravenous methylprednisolone in acute traumatic spinal cord injuries following decompression surgeries
  46. RAB39B: A novel biomarker for acute myeloid leukemia identified via multi-omics and functional validation
  47. Impact of peripheral conditioning on reperfusion injury following primary percutaneous coronary intervention in diabetic and non-diabetic STEMI patients
  48. Clinical efficacy of azacitidine in the treatment of middle- and high-risk myelodysplastic syndrome in middle-aged and elderly patients: A retrospective study
  49. The effect of ambulatory blood pressure load on mitral regurgitation in continuous ambulatory peritoneal dialysis patients
  50. Expression and clinical significance of ITGA3 in breast cancer
  51. Single-nucleus RNA sequencing reveals ARHGAP28 expression of podocytes as a biomarker in human diabetic nephropathy
  52. rSIG combined with NLR in the prognostic assessment of patients with multiple injuries
  53. Toxic metals and metalloids in collagen supplements of fish and jellyfish origin: Risk assessment for daily intake
  54. Exploring causal relationship between 41 inflammatory cytokines and marginal zone lymphoma: A bidirectional Mendelian randomization study
  55. Gender beliefs and legitimization of dating violence in adolescents
  56. Effect of serum IL-6, CRP, and MMP-9 levels on the efficacy of modified preperitoneal Kugel repair in patients with inguinal hernia
  57. Effect of smoking and smoking cessation on hematological parameters in polycythemic patients
  58. Pathogen surveillance and risk factors for pulmonary infection in patients with lung cancer: A retrospective single-center study
  59. Necroptosis of hippocampal neurons in paclitaxel chemotherapy-induced cognitive impairment mediates microglial activation via TLR4/MyD88 signaling pathway
  60. Celastrol suppresses neovascularization in rat aortic vascular endothelial cells stimulated by inflammatory tenocytes via modulating the NLRP3 pathway
  61. Cord-lamina angle and foraminal diameter as key predictors of C5 palsy after anterior cervical decompression and fusion surgery
  62. GATA1: A key biomarker for predicting the prognosis of patients with diffuse large B-cell lymphoma
  63. Influencing factors of false lumen thrombosis in type B aortic dissection: A single-center retrospective study
  64. MZB1 regulates the immune microenvironment and inhibits ovarian cancer cell migration
  65. Integrating experimental and network pharmacology to explore the pharmacological mechanisms of Dioscin against glioblastoma
  66. Trends in research on preterm birth in twin pregnancy based on bibliometrics
  67. Four-week IgE/baseline IgE ratio combined with tryptase predicts clinical outcome in omalizumab-treated children with moderate-to-severe asthma
  68. Single-cell transcriptomic analysis identifies a stress response Schwann cell subtype
  69. Acute pancreatitis risk in the diagnosis and management of inflammatory bowel disease: A critical focus
  70. Effect of subclinical esketamine on NLRP3 and cognitive dysfunction in elderly ischemic stroke patients
  71. Interleukin-37 mediates the anti-oral tumor activity in oral cancer through STAT3
  72. CA199 and CEA expression levels, and minimally invasive postoperative prognosis analysis in esophageal squamous carcinoma patients
  73. Efficacy of a novel drainage catheter in the treatment of CSF leak after posterior spine surgery: A retrospective cohort study
  74. Comprehensive biomedicine assessment of Apteranthes tuberculata extracts: Phytochemical analysis and multifaceted pharmacological evaluation in animal models
  75. Relation of time in range to severity of coronary artery disease in patients with type 2 diabetes: A cross-sectional study
  76. Dopamine attenuates ethanol-induced neuronal apoptosis by stimulating electrical activity in the developing rat retina
  77. Correlation between albumin levels during the third trimester and the risk of postpartum levator ani muscle rupture
  78. Factors associated with maternal attention and distraction during breastfeeding and childcare: A cross-sectional study in the west of Iran
  79. Mechanisms of hesperetin in treating metabolic dysfunction-associated steatosis liver disease via network pharmacology and in vitro experiments
  80. The law on oncological oblivion in the Italian and European context: How to best uphold the cancer patients’ rights to privacy and self-determination?
  81. The prognostic value of the neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and prognostic nutritional index for survival in patients with colorectal cancer
  82. Factors affecting the measurements of peripheral oxygen saturation values in healthy young adults
  83. Comparison and correlations between findings of hysteroscopy and vaginal color Doppler ultrasonography for detection of uterine abnormalities in patients with recurrent implantation failure
  84. The effects of different types of RAGT on balance function in stroke patients with low levels of independent walking in a convalescent rehabilitation hospital
  85. Causal relationship between asthma and ankylosing spondylitis: A bidirectional two-sample univariable and multivariable Mendelian randomization study
  86. Correlations of health literacy with individuals’ understanding and use of medications in Southern Taiwan
  87. Correlation of serum calprotectin with outcome of acute cerebral infarction
  88. Comparison of computed tomography and guided bronchoscopy in the diagnosis of pulmonary nodules: A systematic review and meta-analysis
  89. Curdione protects vascular endothelial cells and atherosclerosis via the regulation of DNMT1-mediated ERBB4 promoter methylation
  90. The identification of novel missense variant in ChAT gene in a patient with gestational diabetes denotes plausible genetic association
  91. Molecular genotyping of multi-system rare blood types in foreign blood donors based on DNA sequencing and its clinical significance
  92. Exploring the role of succinyl carnitine in the association between CD39⁺ CD4⁺ T cell and ulcerative colitis: A Mendelian randomization study
  93. Dexmedetomidine suppresses microglial activation in postoperative cognitive dysfunction via the mmu-miRNA-125/TRAF6 signaling axis
  94. Analysis of serum metabolomics in patients with different types of chronic heart failure
  95. Diagnostic value of hematological parameters in the early diagnosis of acute cholecystitis
  96. Pachymaran alleviates fat accumulation, hepatocyte degeneration, and injury in mice with nonalcoholic fatty liver disease
  97. Decrease in CD4 and CD8 lymphocytes are predictors of severe clinical picture and unfavorable outcome of the disease in patients with COVID-19
  98. METTL3 blocked the progression of diabetic retinopathy through m6A-modified SOX2
  99. The predictive significance of anti-RO-52 antibody in patients with interstitial pneumonia after treatment of malignant tumors
  100. Exploring cerebrospinal fluid metabolites, cognitive function, and brain atrophy: Insights from Mendelian randomization
  101. Development and validation of potential molecular subtypes and signatures of ocular sarcoidosis based on autophagy-related gene analysis
  102. Widespread venous thrombosis: Unveiling a complex case of Behçet’s disease with a literature perspective
  103. Uterine fibroid embolization: An analysis of clinical outcomes and impact on patients’ quality of life
  104. Discovery of lipid metabolism-related diagnostic biomarkers and construction of diagnostic model in steroid-induced osteonecrosis of femoral head
  105. Serum-derived exomiR-188-3p is a promising novel biomarker for early-stage ovarian cancer
  106. Enhancing chronic back pain management: A comparative study of ultrasound–MRI fusion guidance for paravertebral nerve block
  107. Peptide CCAT1-70aa promotes hepatocellular carcinoma proliferation and invasion via the MAPK/ERK pathway
  108. Electroacupuncture-induced reduction of myocardial ischemia–reperfusion injury via FTO-dependent m6A methylation modulation
  109. Hemorrhoids and cardiovascular disease: A bidirectional Mendelian randomization study
  110. Cell-free adipose extract inhibits hypertrophic scar formation through collagen remodeling and antiangiogenesis
  111. HALP score in Demodex blepharitis: A case–control study
  112. Assessment of SOX2 performance as a marker for circulating cancer stem-like cells (CCSCs) identification in advanced breast cancer patients using CytoTrack system
  113. Risk and prognosis for brain metastasis in primary metastatic cervical cancer patients: A population-based study
  114. Comparison of the two intestinal anastomosis methods in pediatric patients
  115. Factors influencing hematological toxicity and adverse effects of perioperative hyperthermic intraperitoneal vs intraperitoneal chemotherapy in gastrointestinal cancer
  116. Endotoxin tolerance inhibits NLRP3 inflammasome activation in macrophages of septic mice by restoring autophagic flux through TRIM26
  117. Lateral transperitoneal laparoscopic adrenalectomy: A single-centre experience of 21 procedures
  118. Petunidin attenuates lipopolysaccharide-induced retinal microglia inflammatory response in diabetic retinopathy by targeting OGT/NF-κB/LCN2 axis
  119. Procalcitonin and C-reactive protein as biomarkers for diagnosing and assessing the severity of acute cholecystitis
  120. Factors determining the number of sessions in successful extracorporeal shock wave lithotripsy patients
  121. Development of a nomogram for predicting cancer-specific survival in patients with renal pelvic cancer following surgery
  122. Inhibition of ATG7 promotes orthodontic tooth movement by regulating the RANKL/OPG ratio under compression force
  123. A machine learning-based prognostic model integrating mRNA stemness index, hypoxia, and glycolysis‑related biomarkers for colorectal cancer
  124. Glutathione attenuates sepsis-associated encephalopathy via dual modulation of NF-κB and PKA/CREB pathways
  125. FAHD1 prevents neuronal ferroptosis by modulating R-loop and the cGAS–STING pathway
  126. Association of placenta weight and morphology with term low birth weight: A case–control study
  127. Review Articles
  128. The effects of enhanced external counter-pulsation on post-acute sequelae of COVID-19: A narrative review
  129. Diabetes-related cognitive impairment: Mechanisms, symptoms, and treatments
  130. Microscopic changes and gross morphology of placenta in women affected by gestational diabetes mellitus in dietary treatment: A systematic review
  131. Review of mechanisms and frontier applications in IL-17A-induced hypertension
  132. Research progress on the correlation between islet amyloid peptides and type 2 diabetes mellitus
  133. The safety and efficacy of BCG combined with mitomycin C compared with BCG monotherapy in patients with non-muscle-invasive bladder cancer: A systematic review and meta-analysis
  134. The application of augmented reality in robotic general surgery: A mini-review
  135. The effect of Greek mountain tea extract and wheat germ extract on peripheral blood flow and eicosanoid metabolism in mammals
  136. Neurogasobiology of migraine: Carbon monoxide, hydrogen sulfide, and nitric oxide as emerging pathophysiological trinacrium relevant to nociception regulation
  137. Plant polyphenols, terpenes, and terpenoids in oral health
  138. Laboratory medicine between technological innovation, rights safeguarding, and patient safety: A bioethical perspective
  139. End-of-life in cancer patients: Medicolegal implications and ethical challenges in Europe
  140. The maternal factors during pregnancy for intrauterine growth retardation: An umbrella review
  141. Intra-abdominal hypertension/abdominal compartment syndrome of pediatric patients in critical care settings
  142. PI3K/Akt pathway and neuroinflammation in sepsis-associated encephalopathy
  143. Screening of Group B Streptococcus in pregnancy: A systematic review for the laboratory detection
  144. Giant borderline ovarian tumours – review of the literature
  145. Leveraging artificial intelligence for collaborative care planning: Innovations and impacts in shared decision-making – A systematic review
  146. Cholera epidemiology analysis through the experience of the 1973 Naples epidemic
  147. Risk factors of frailty/sarcopenia in community older adults: Meta-analysis
  148. Supplement strategies for infertility in overweight women: Evidence and legal insights
  149. Scurvy, a not obsolete disorder: Clinical report in eight young children and literature review
  150. Case Reports
  151. Delayed graft function after renal transplantation
  152. Semaglutide treatment for type 2 diabetes in a patient with chronic myeloid leukemia: A case report and review of the literature
  153. Diverse electrophysiological demyelinating features in a late-onset glycogen storage disease type IIIa case
  154. Giant right atrial hemangioma presenting with ascites: A case report
  155. Laser excision of a large granular cell tumor of the vocal cord with subglottic extension: A case report
  156. EsoFLIP-assisted dilation for dysphagia in systemic sclerosis: Highlighting the role of multimodal esophageal evaluation
  157. Rapid Communication
  158. Biological properties of valve materials using RGD and EC
  159. Letter to the Editor
  160. Role of enhanced external counterpulsation in long COVID
  161. Expression of Concern
  162. Expression of concern “A ceRNA network mediated by LINC00475 in papillary thyroid carcinoma”
  163. Expression of concern “Notoginsenoside R1 alleviates spinal cord injury through the miR-301a/KLF7 axis to activate Wnt/β-catenin pathway”
  164. Expression of concern “circ_0020123 promotes cell proliferation and migration in lung adenocarcinoma via PDZD8”
  165. Corrigendum
  166. Corrigendum to “Empagliflozin improves aortic injury in obese mice by regulating fatty acid metabolism”
  167. Corrigendum to “Comparing the therapeutic efficacy of endoscopic minimally invasive surgery and traditional surgery for early-stage breast cancer: A meta-analysis”
  168. Corrigendum to “The progress of autoimmune hepatitis research and future challenges”
  169. Retraction
  170. Retraction of “miR-654-5p promotes gastric cancer progression via the GPRIN1/NF-κB pathway”
  171. Special Issue Advancements in oncology: bridging clinical and experimental research - Part II
  172. Unveiling novel biomarkers for platinum chemoresistance in ovarian cancer
  173. Lathyrol affects the expression of AR and PSA and inhibits the malignant behavior of RCC cells
  174. The era of increasing cancer survivorship: Trends in fertility preservation, medico-legal implications, and ethical challenges
  175. Bone scintigraphy and positron emission tomography in the early diagnosis of MRONJ
  176. Meta-analysis of clinical efficacy and safety of immunotherapy combined with chemotherapy in non-small cell lung cancer
  177. Special Issue Computational Intelligence Methodologies Meets Recurrent Cancers - Part IV
  178. Exploration of mRNA-modifying METTL3 oncogene as momentous prognostic biomarker responsible for colorectal cancer development
  179. Special Issue The evolving saga of RNAs from bench to bedside - Part III
  180. Interaction and verification of ferroptosis-related RNAs Rela and Stat3 in promoting sepsis-associated acute kidney injury
  181. The mRNA MOXD1: Link to oxidative stress and prognostic significance in gastric cancer
  182. Special Issue Exploring the biological mechanism of human diseases based on MultiOmics Technology - Part II
  183. Dynamic changes in lactate-related genes in microglia and their role in immune cell interactions after ischemic stroke
  184. A prognostic model correlated with fatty acid metabolism in Ewing’s sarcoma based on bioinformatics analysis
  185. Special Issue Diabetes
  186. Nutritional risk assessment and nutritional support in children with congenital diabetes during surgery
  187. Correlation of the differential expressions of RANK, RANKL, and OPG with obesity in the elderly population in Xinjiang
  188. A discussion on the application of fluorescence micro-optical sectioning tomography in the research of cognitive dysfunction in diabetes
  189. A review of brain research on T2DM-related cognitive dysfunction
  190. Special Issue Biomarker Discovery and Precision Medicine
  191. CircASH1L-mediated tumor progression in triple-negative breast cancer: PI3K/AKT pathway mechanisms
Heruntergeladen am 1.10.2025 von https://www.degruyterbrill.com/document/doi/10.1515/med-2025-1189/html
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