Cysteine cathepsins and autoimmune diseases: A bidirectional Mendelian randomization

Abstract

Cysteine cathepsins are proteolytic enzymes crucial in various physiological and pathological processes, primarily operating within lysosomes. Their functions include protein degradation, immune system regulation, and involvement in various diseases. While some cysteine cathepsins play important roles in the immune system, their connection to autoimmune diseases remains unclear. This study proposes using Mendelian randomization to explore the causal relationship between cysteine cathepsins and autoimmune diseases. Single nucleotide polymorphisms (SNPs) for cysteine cathepsins were obtained from a publicly available genome-wide association study (GWAS) dataset, while outcome SNP data were sourced from 10 separate GWAS datasets. Mendelian randomization (MR) analysis employed the Wald ratio (WR) and inverse variance weighted (IVW) approach as primary methods, supplemented by the weighted median and MR-Egger methods. Heterogeneity was assessed using Cochran Q test, and sensitivity analysis was conducted using the MR-PRESSO method. The association strength between exposure and outcome was evaluated using odds ratios (OR) with 95% confidence intervals (CI). The study identified a potential positive correlation between elevated cathepsin B and psoriasis (Wald ratio OR = 1.449, 95% CI: 1.053–1.993, P = .0227). Elevated cathepsin F was potentially linked to ulcerative colitis (WR OR = 1.073, 95% CI: 1.021–1.127, P = .0056), ankylosing spondylitis (WR OR = 1.258, 95% CI: 1.082–1.463, P = .0029), and primary biliary cholangitis(PBC) (WR OR = 1.958, 95% CI: 1.326–2.889, P = .0007). Conversely, cathepsin H appeared protective against celiac disease (WR OR = 0.881, 95% CI: 0.838–0.926, P = 6.5e‐7), though elevated levels may increase the risk of type 1 diabetes (IVW OR = 1.121, 95% CI: 1.053–1.194, P = .0003) and PBC (WR OR = 1.792, 95% CI: 1.062–3.024, P = .0288). Cathepsin Z was also associated with an increased risk of type 1 diabetes (IVW OR = 1.090, 95% CI: 1.006–1.181, P = .0349). The MR analysis suggests potential risks of cathepsin B with psoriasis, cathepsin F with ulcerative colitis, ankylosing spondylitis, and PBC, and cathepsin Z with type 1 diabetes. Conversely, cathepsin H may protect against celiac disease but could increase the risk of type 1 diabetes and PBC.

1. Introduction

The immune system plays a crucial role in safeguarding the host against infections, exhibiting a wide range of functions that can, in certain instances, contribute to the development of diseases. These diseases primarily manifest through 2 principal pathogenic mechanisms: immunodeficiency, characterized by the immune system’s inability to mount a protective response against pathogens, and autoimmune disorders, characterized by the immune system’s failure to differentiate between self and nonself entities.^[1] Recent epidemiological research indicates that immune system disorders are now impacting 3 % to 5% of the population. The most prevalent among these are autoimmune thyroid diseases and type 1 diabetes (T1D). Additionally, close to 100 distinct autoimmune diseases have been recognized. Some of these diseases target specific organs, like primary biliary cirrhosis (PBC), while others, such as systemic lupus erythematosus (SLE), involve multiple immune dysfunctions affecting several organs.^[2]

Cysteine cathepsins are a group of proteolytic enzymes that play a role in various cellular processes, including protein degradation. In the context of immune diseases, cysteine cathepsins have been implicated in several ways.^[3] They are involved in antigen processing and presentation, a crucial step in immune response. Dysregulation or abnormal activity of cysteine cathepsins can contribute to pathological processes in autoimmune diseases, where the immune system mistakenly attacks the body’s own cells.^[4] Additionally, cysteine cathepsins may participate in the degradation of extracellular matrix components, influencing inflammatory processes.^[5] However, the relationship between autoimmune diseases and cathepsin remains unclear and needs further investigation.

Mendelian randomization (MR) is a methodology employed to evaluate causal associations between exposures and outcomes by utilizing genetic variations linked to these exposures.^[6] As human genetic variation is randomly determined at conception, this method can circumvent confounding factors. Moreover, since genetic variants are established prior to the onset of disease, they are not influenced by the disease, thus reducing the likelihood of reverse causality.^[7] Therefore, current studies using MR methods can explore the correlation between cysteine cathepsins and autoimmune diseases, thereby providing valuable insights into the potential mechanisms of autoimmune diseases.

2. Methods

2.1. Mendelian randomization data and process

To investigate the causal link between cysteine cathepsins and autoimmune diseases, we used a two-sample MR research. Figure 1 depicts the research procedure.

Figure 1.

We used the TSMR method and the Reverse MR method to study the relationship between cysteine cathepsins and autoimmune diseases. The flowchart is shown as illustrated. This study adheres to the 3 core assumptions of MR: Assumption 1: Indicated by the solid line, the instrumental variants directly influence the incidence of cysteine cathepsins. Assumption 2: Represented by dashed lines, the instrumental variables are not associated with any potential confounders. Assumption 3: The instrumental variables affect the outcome solely through the exposure, without any involvement in other causal pathways. TSMR = two-sample Mendelian randomization.

2.2. Instrumental variables selection

The SNPs chosen for this investigation must adhere to the 3 fundamental hypotheses of MR: the correlation hypothesis, which necessitates a robust association between genetic variation and exposure; the independence hypothesis, which requires genetic variation to be unaffected by both known and unknown confounding factors; and the exclusion hypothesis, which mandates that genetic variation solely influences the outcome through exposure. To adhere to these assumptions, we established the following inclusion criteria: The SNPs incorporated into the study were chosen based on a high correlation with a significance threshold (P < 5 × 10⁻⁶) across the whole genome. All included SNPs must be in linkage equilibrium (kb = 10,000, r² < 0.001).

The significance of regression analysis results was tested using the F-statistic, calculated as follows: $F=\frac{R^2\times \left(N-k-1\right)}{\left(1-R^2\right)\times k}$, where N is the sample size of GWAS for the cysteine cathepsins, k represents the number of SNPs, and R² is the proportion of cysteine cathepsins status explained by each SNP. R² is specifically calculated as $R^2=2\times bet{a}^2 \times \left(1 - EAF\right) \times EAF,$ where beta² is the estimate of the genetic effect of each SNP on cysteine cathepsins, and EAF is the frequency of the effect allele. An F-value >10 indicates that the included instrumental variables are strongly correlated with exposure.

2.3. SNPs associated with cysteine cathepsins

Cathepsin-related SNPs were sourced from the INTERVAL study, which encompassed 3301 European individuals. All participants provided trial consent, and the INTERVAL study received approval from the National Research Ethics Service (11/EE/0538). Summary data from the study are accessible at https://gwas.mrcieu.ac.uk.^[8] All included cathepsins-related SNPs had a P-value < 5 × 10^‐6, and there was no linkage disequilibrium between them (kb = 10,000, r² < 0.001). Details of the included studies are detailed in Supplementary Material 2, Supplemental Digital Content, http://links.lww.com/MD/N820. We conducted a detailed search of the included SNPs and related phenotypes, and uploaded the findings as Supplementary Material 3, Supplemental Digital Content, http://links.lww.com/MD/N820.

2.4. SNPs associated with autoimmune diseases

The autoimmune diseases included in our study were Crohn disease, ulcerative colitis (UC), PBC, SLE, celiac disease, psoriasis, ankylosing spondylitis (AS), multiple sclerosis (MS), T1D, and rheumatoid arthritis (RA). Detailed outcome data are presented in Table 1.

Table 1.

The basic characteristics of outcomes.

Outcomes	Consortium	Sample size (cases/controls)	Population	ID
Crohn disease	Liu JZ et al	5956/14,927	European	ebi-a-GCST003044
Ulcerative colitis	Liu JZ et al	6968/20,464	European	ebi-a-GCST003045
Primary biliary cholangitis	Cordell HJ et al	2764/10,475	European	ebi-a-GCST003129
Systemic lupus erythematosus	Bentham J et al	5201/9066	European	ebi-a-GCST003156
Celiac disease	Trynka G et al	11,812/229	European	ebi-a-GCST005523
Psoriasis	Tsoi LC et al	10,588/22,806	European	ebi-a-GCST005527
Ankylosing spondylitis	Cortes A et al	9069/1550	European	ebi-a-GCST005529
Multiple sclerosis	Beecham AH et al	14,498/24,091	European	ebi-a-GCST005531
Type 1 diabetes	Forgetta V et al	9266/15,574	European	ebi-a-GCST010681
Rheumatoid arthritis	Ha E et al	14,361/43,923	European	ebi-a-GCST90013534

For Crohn disease, the SNPs were obtained from a study by Liu JZ et al, which included 5917 Crohn disease patients and 14,927 controls.^[9] UC-related SNPs were sourced from a study by Liu JZ et al, which included 6968 UC patients and 20,464 controls.^[9] PBC-related SNPs came from a study by Cordell HJ et al, encompassing 2764 PBC patients and 10,475 controls.^[10] Systemic lupus erythematosus-related SNPs were also obtained from Bentham J et al, involving 5210 SLE patients and 9066 controls.^[11] For celiac disease, the SNPs were sourced from a study by Trynka G et al, including 11,812 celiac disease patients and 229 controls.^[12] Psoriasis-related SNPs were obtained from a study by Tsoi LC et al, which included 10,588 psoriasis patients and 22,806 controls.^[13] AS-related SNPs were obtained from a study by Cortes A et al, which included 9069 psoriasis patients and 1550 controls.^[14] MS-related SNPs were obtained from a study by Beecham AH et al, which included 14,498 MS patients and 24,091 controls.^[15] T1D-related SNPs were obtained from a study by Forgetta V et al, which included 9266 MS patients and 15,574 controls.^[16] Lastly, RA-related SNPs came from another study by Ha E et al, involving 14,361 RA patients and 43,923 controls.^[17]

2.5. Mendelian randomization analysis

To ascertain if there is a causal link between cysteine cathepsins and autoimmune diseases, we primarily utilized the inverse variance weighted (IVW) and Wald ratio (WR) approach for MR analysis. The WR method is the effect estimate of the exposure variable on the outcome variable, which calculates the causal effect of the exposure variable through the relationship between the genetic variance and the exposure variable and the outcome variable, which is calculated as the ratio of the estimate of the effect of the outcome variable on the genetic variance to the estimate of the effect of the exposure variable on the genetic variance, which is applicable to the case of single instrumental variables. The IVW estimate represents the aggregate effect size of individual SNP WR estimates. This method is particularly effective and reliable when all SNPs in the analysis are valid and uncorrelated.^[18]

Additionally, we employed 4 other methods for MR analysis: the weighted median, MR-Egger, the simple mode, and the weighted mode. The weighted median estimator is highly effective in aggregating SNP effects when over 50% of SNPs are valid.^[19] MR-Egger regression was used to explore potential genetic pleiotropy.^[20] All data analyses were conducted using the TwosampleMR package in R software. The initial MR analysis uses beta values to represent the results. In MR analysis, the beta value indicates the degree of linear influence of the exposure variable on the outcome variable, with the beta value representing the number of units of change in the outcome variable for each unit increase in the exposure variable. Normally, MR analyses will show the causal relationship between exposure and outcome in terms of beta values, and at the same time, beta and odds ratios (OR) values can be logarithmically transformed, and we logarithmically transformed the beta values in the forest plots and in the final results, and converted them to OR values to visualize the potential causal relationship between the exposure and the outcome. The strength of the association was evaluated using OR, where exposure was a risk factor for the outcome when the OR value was >1, exposure was a protective factor for the outcome when the OR was <1, and exposure had no effect when the OR value was 0. We also conducted a reverse Mendelian analysis on positive results to check for reverse causation.

2.6. Sensitivity analysis

To assess horizontal pleiotropy, we employed the MR-Egger analysis intercept. A significant intercept (P > .05) indicates the absence of horizontal pleiotropy. To further investigate horizontal pleiotropy, we utilized the MR-PRESSO method, which involves the removal of outliers from the data.^[21]

Additionally, we conducted Cochran Q test to detect heterogeneity. A P-value > .05 indicated the absence of heterogeneity in our study’s results. Our findings suggest that the exclusion of any individual SNP did not significantly alter the overall results.

We also reviewed the phenotypes database for secondary phenotypes of SNPs included in our study, excluding those associated with the outcome data.

3. Results

3.1. Results of the two-sample Mendelian randomization analysis

Our study included 7 subtypes of cysteine cathepsins: B, F, H, V, O, S, and Z, with the MR Analysis results presented in Figure 2. The primary method used was the IVW and WR approach. Our results indicate that cathepsin B is a potential risk factor for psoriasis, while cathepsin F is a potential risk factor for UC, AS, and PBC. Cathepsin H is identified as a potential protective factor for celiac disease, but a potential risk factor for T1D and PBC. Cathepsin Z is identified as a potential risk factor for T1D. Detailed data are presented in Table 2 and Figure 3A, and the visualization in the form of a forest plot can be found in Figure 3B. The other cathepsin subtypes did not show statistically significant effects on autoimmune diseases. All detailed results have been uploaded as Supplementary Material 1, Supplemental Digital Content, http://links.lww.com/MD/N820. In sensitivity analyses, the MR-PRESSO test detected no outliers. We applied both MR-Egger and MR-PRESSO tests to assess horizontal pleiotropy, and the results from both tests suggested the absence of horizontal pleiotropy in our study findings (P > .05 for both tests). No heterogeneity was seen in the MR effect estimates according to the Cochran Q test (P > .05). The specific results of the sensitivity analysis are shown in Table 3. We used the leave-one-out method to evaluate the stability of the results. The leave-one-out analysis indicated that the overall effect values of all SNPs were on the right side of zero, suggesting that the effects of Cathepsin H and Cathepsin Z on T1D are stable (Fig. 3C).

Figure 2.

A annular heat map of the effects of cysteine cathepsins on autoimmune diseases with 5 MR methods. The results marked in red indicate statistically significant outcomes. The color gradient from blue to red represents changes in Beta values, and the asterisks denote the corresponding P-values. Cathepsin B is potentially associated with the pathogenesis of psoriasis. Cathepsin F is potentially associated with the development of UC, AS, and PBC. Cathepsin H poses a potential risk for the development of T1D and PBC. Cathepsin Z also presents a potential risk for the development of T1D. Cathepsin H acts as a potential protective factor against celiac disease. UC = ulcerative colitis, AS = ankylosing spondylitis, PBC = primary biliary cholangitis, T1D = type 1 diabetes, Beta = beta values represent the linear effects of genetic instrumental variables on the outcome variables.

Table 2.

The results of MR analysis.

Cathepsin	Disease	Effect	OR	95% CI	P-value
B	Psoriasis	Positive correlation	1.449	1.053–1.993	.02274
F	Ulcerative colitis	Positive correlation	1.073	1.021–1.127	.005551
F	Ankylosing spondylitis	Positive correlation	1.258	1.082–1.463	.002901
F	Primary biliary cholangitis	Positive correlation	1.958	1.326–2.889	.0007171
H	Celiac disease	Negative correlation	0.881	0.838–0.926	6.50E‐07
H	Type 1 diabetes	Positive correlation	1.121	1.053–1.194	.0003482

Figure 3.

(A) Heat map of the effects of cysteine cathepsins on autoimmune diseases with IVW and WR methods. The deepening color gradient from blue to red in the tiles represents changes in Beta values, and the asterisks indicate the corresponding P-values. Cathepsin B is potentially positively correlated with an increased incidence of psoriasis. Cathepsin F is potentially positively correlated with an increased incidence of UC, AS, and PBC. Cathepsin H is potentially positively correlated with an increased incidence of PBC. Cathepsin H is potentially negatively correlated with the incidence of celiac disease. Cathepsin Z and cathepsin H are potentially positively correlated with an increased T1D. (B) Forest plot of the effects of cathepsin B, cathepsin F, cathepsin H, and cathepsin Z on autoimmune diseases. The OR values, converted from Beta, represent the risk relationship between cysteine cathepsins and autoimmune diseases. Red indicates an increased risk of autoimmune diseases, while blue indicates a decreased risk. (C) Using the leave-one-out method for sensitivity analysis, after combining the results of individual SNPs, the effect value remains on the right side of zero, indicating that the overall results are stable. AS = ankylosing spondylitis, IVW = inverse variance weighted, OR = odds ratio, PBC = primary biliary cholangitis, SNPs = single nucleotide polymorphisms, T1D = type 1 diabetes, UC = ulcerative colitis, WR = Wald ratio.

Table 3.

The results of the MR sensitivity analysis.

Exposures	Outcomes	Cochran Q statistic	P-value for Cochran Q	P-value for intercept	MR-PRESSO global test
Cathepsin H	T1D	5.268	.627	.953	0.475
Cathepsin Z	T1D	7.407	.686	.907	0.680

T1D = type 1 diabetes.

3.2. Reverse Mendelian randomization analysis

We used reverse MR to explore whether there is reverse causality between cysteine cathepsins and autoimmune diseases. Reverse MR analysis is a methodology used in genetic epidemiology and causal inference research. In traditional MR analysis, genetic variants are used as instrumental variables to investigate the causal effect of an exposure on an outcome. In reverse Mendelian randomization analysis, the directionality is reversed. We performed reverse analysis on autoimmune diseases as exposure and cysteine cathepsins as outcome to explore whether there was reverse causality between them.

Among them, there was an inverse causal relationship between cathepsin B and Psoriasis, and no inverse causal relationship between the remaining positive results (Fig. 4A). We plotted all the results in a forest plot, as shown in Figure 4B.

Figure 4.

(A) Heat map of the effects of autoimmune diseases on cysteine cathepsins. The deepening color gradient from blue to red in the tiles represents changes in Beta values, and the asterisks indicate the corresponding P-values. Cathepsin B has a reverse causal relationship with Psoriasis, while other cysteine cathepsins and autoimmune diseases do not exhibit reverse causal relationships. (B) We converted the Beta values to OR values and plotted a forest plot for all the results of the reverse MR analysis. Beta = beta values represent the linear effects of genetic instrumental variables on the outcome variables, OR = odds ratio.

4. Discussion

The relationship between cysteine cathepsins and autoimmune diseases is an area of growing interest and importance in biomedical research. Cysteine cathepsins have been recognized for their significant impact on inflammation and immune reactions, playing a pivotal role in the pathogenesis of some autoimmune diseases.^[22] These proteases, found predominantly in acidic endo/lysosomal compartments, are integral to various cellular functions, including intracellular protein degradation, energy metabolism, and immune responses.^[23] Cysteine cathepsins, primarily functioning as intracellular enzymes, are responsible for nonspecific bulk proteolysis within the endosomal/lysosomal system, affecting both intracellular and extracellular proteins, this broad range of activity underscores their potential influence on immune system dynamics, particularly in the context of autoimmune disorders.^[24] Specifically, cysteine cathepsins are a group of lysosomal proteases whose proteolytic function is intricately linked to various aspects of immune system function, which in turn supports their potential impact on the onset and progression of autoimmune diseases. Cysteine cathepsins are primarily involved in protein degradation, antigen processing, and immune cell activation.^[25,26] They play a critical role in processing and presenting antigens to immune cells, particularly antigen-presenting cells (APCs) such as dendritic cells and macrophages. Through their proteolytic activity, cathepsins contribute to the cleavage of antigenic peptides from proteins, which are then presented by major histocompatibility complex molecules to T cells. This process is essential for the activation and regulation of T cell-mediated immune responses, including the differentiation of naive T cells into effector and regulatory T cell subsets.^[27] Furthermore, cysteine cathepsins participate in the regulation of inflammatory responses by cleaving cytokines, chemokines, and other immune signaling molecules.^[28] Additionally, cysteine cathepsins can modulate the activity of chemokines, which regulate the recruitment and trafficking of immune cells to sites of inflammation and the dysregulation of chemokine activity is related to the pathogenesis of many immune diseases.^[29] In these conditions, abnormal cathepsin expression or activity may contribute to aberrant antigen presentation, dysregulated immune cell activation, and excessive inflammation, leading to tissue damage and autoimmune pathology.^[30]

In our investigation, cathepsin B was determined to be a potential risk factor in the pathogenesis of psoriasis, potentially attributable to several underlying mechanisms. Previous studies have indicated that the downregulation of cathepsin B can effectively attenuate the proliferation and inflammatory response of human HaCaT keratinocytes. Moreover, this regulatory process promotes cellular differentiation, thereby ameliorating the inflammation associated with psoriasis-like lesions induced by IL-17A and serum amyloid A (SAA).^[31] Additionally, several studies have observed an elevation in the presence of cathepsin B-positive cells within psoriasis-affected skin. Furthermore, the abundance of these mast cells expressing cathepsin B displayed a positive correlation with the severity of the condition, implying that cathepsin B may potentially serve as a reliable marker for the mast cell-mediated pruritus characteristic of psoriasis.^[32] These suggest that cathepsin B may be a risk factor for the development of psoriasis. Meanwhile, our study suggests an inverse causal relationship between cathepsin B and psoriasis, which suggests that they may be risk factors for each other. This is consistent with some previous studies, which suggest that SAA strongly expressed and known to exacerbate psoriasis through the induction of IL-17 secretion, can stimulate the release of cathepsin B. This indicates a potential interaction between SAA and cathepsin B in the progression and exacerbation of psoriasis.^[31] The relevant SNP we included is rs7249773, located in the vicinity of the cathepsin B gene. The specific mechanism by which rs7249773 regulates cathepsin B has not been fully elucidated. However, one possible mechanism is that it influences the binding of transcription factors to the GC-rich region, thereby regulating the expression level of cathepsin B.^[32]

Our study suggests that cathepsin F is a risk factor for UC, AS, and PBC. Cathepsin F is one of the cysteine cathepsins, and cysteine cathepsins are known to play a role in the development and progression of numerous inflammation-associated diseases, including autoimmune disorders.^[33] The mechanism by which cysteine cathepsins affect the progression of autoimmune diseases is likely multifaceted, involving their roles in protein degradation, cell signaling, cell morphology, migration, proliferation, and energy metabolism.^[34] Cathepsin F can process inflammatory cytokines such as IL-1β and TNF-α, thereby regulating the inflammatory response. In UC and other inflammatory diseases, elevated levels of these cytokines typically lead to tissue damage and disease progression.^[35] Additionally, cathepsin F can degrade extracellular matrix (ECM) components such as collagen and elastin. In UC, this can lead to the disruption of the intestinal barrier, increased intestinal permeability, and exacerbated inflammation. In PBC, excessive ECM degradation and subsequent fibrosis can lead to the progressive destruction of bile ducts. Similarly, in AS, ECM remodeling can affect spinal and joint structures, leading to characteristic stiffness and pain. Furthermore, dysregulation of cathepsin F activity can promote the presentation of self-antigens and subsequent autoimmune responses, which is particularly relevant in diseases like AS and PBC.^[36] The SNP we included as a proxy for the exposure cathepsin F is SNP rs1260326. SNP rs1260326 is located in the regulatory region of the cathepsin F gene. From a genetic perspective, it may regulate the expression level of cathepsin F by influencing promoter activity. Variations in the regulatory region can alter transcription factor binding sites, thereby enhancing gene expression. cathepsin F plays a role in the immune system, including regulating inflammatory responses and antigen presentation. Changes in expression levels may lead to excessive inflammatory responses, thereby promoting the development of UC, AS, and PBC.

Our MR analysis suggests that cathepsin H is a potential protective factor for celiac disease. Cathepsin H may help degrade gliadin peptides, which are responsible for triggering the autoimmune response in celiac disease. By breaking down these peptides, cathepsin H reduces their immunogenicity, thereby lowering the inflammatory response in the gut. Additionally, increased expression of cathepsin H can play a role in maintaining the integrity of the intestinal barrier, which is crucial for preventing harmful antigens from entering the lamina propria and triggering an immune response.^[37] And consistent with previous studies, our study reveals that cathepsin H is a risk factor for T1D. Extensive genetic and epidemiological studies have found that the genetic risk of T1D correlates with high expression of cathepsin H, which is linked to the rapid decline of beta-cell function and early onset of T1D, it has been shown that the transcriptional downregulation of cathepsin H induced by proinflammatory cytokines can promote beta-cell apoptosis.^[38] Cathepsin H is present in pancreatic beta cells and antigen-presenting cells.^[39] Some researches has shown that when cathepsin H is downregulated in the presence of proinflammatory cytokines, there is an increase in beta-cell apoptosis, which occurs through the pathways of the small GTPase Rac2, the process of cathepsin H downregulation is triggered by the DNA hypermethylation of 3 crucial cytosine–phosphate–guanine dinucleotide sites within an open chromatin region, which occurs upon treatment with inflammatory cytokines.^[40] This suggests that genetic risk for cathepsin H is associated with impaired beta-cell function and early onset of T1D.^[41] Besides this abnormal expression of cathepsin H may affect the function of immune cells and the inflammatory response of bile duct epithelial cells, thereby playing a role in the pathogenesis of PBC.^[42] We searched the relevant SNPS in detail, and the SNP associated with celiac disease was rs34593439. This SNP is located in the regulatory region of the cathepsin H gene. Research suggests that rs34593439 can influence the activity of the promoter region and may regulate the transcription level of the cathepsin H gene. The specific mechanism might involve enhancing the binding of certain transcription factors, thereby change cathepsin H expression levels.^[43] However, it is not yet confirmed whether this effect can provide protection against celiac disease. And the SNPS related to T1D were rs12911554, rs146037740, rs147991203, rs34593439, rs35628511, rs60018174, rs62013235, and rs77977134. These SNPs are distributed in the regulatory and coding regions of the cathepsin H gene. They may affect the function and expression of cathepsin H through the following mechanisms: 1. SNPs in the regulatory region: For example, rs34593439, by influencing promoter activity, alters the expression level of cathepsin H. High expression of cathepsin H might play a promoting role in the pathophysiology of T1D.^[44] 2. SNPs in the coding region: for instance, rs146037740 and rs147991203 cause structural changes in the cathepsin H protein, affecting its stability or activity. The altered function of the cathepsin H protein due to these variations might contribute to the development of T1D.^[45,46] We are the first to investigate the relationship between cathepsin H and both celiac disease and T1D at the genetic level. Our study results suggest that an increase in cathepsin H may reduce the risk of celiac disease while exacerbating the risk of T1D. However, additional fundamental experiments are necessary to validate these associated conclusions.

Based on the available information, there isn’t a direct or specific study highlighting the relationship between cathepsin Z and T1D. While cathepsins, in general, have been acknowledged for their role in various physiological and pathological processes, including those related to inflammation and autoimmune responses, the specific involvement of cathepsin Z in T1D is not explicitly detailed in the sources accessed. The known roles of cysteine cathepsins, including cathepsin Z, in inflammasome activation and immune response modulation suggest a potential link to autoimmune diseases like T1D.^[23] In our study, we discussed for the first time the relationship between cathepsin Z and T1D at the genetic level. We included a total of 11 SNPs as instrumental variables, with detailed data provided in Supplementary Material 1, Supplemental Digital Content, http://links.lww.com/MD/N820. Among these, rs1135945, located in the coding region of the cathepsin Z gene, may lead to amino acid changes, thereby affecting the structure and function of the cathepsin Z protein. Abnormal functioning of cathepsin Z may play a detrimental role in antigen presentation and T-cell activation, promoting autoimmune responses and increasing susceptibility to T1D. Additionally, rs116920068, located in the promoter region of the cathepsin Z gene, may alter the transcriptional activity of the gene, affecting the expression levels of cathepsin Z. Changes in cathepsin Z expression may regulate immune cell function, leading to abnormal immune responses and destruction of pancreatic islet cells.^[44]

There were several significant limitations to our study. Firstly, our study currently lacks experimental validation, thus it is crucial to underscore the necessity of confirming the association between cathepsin and autoimmune diseases through subsequent functional investigations. Secondly, our two-sample MR analyses predominantly employed populations of European descent, which implies that the generalizability of our findings to non-European populations and diverse ethnicities may be constrained. Lastly, the amount of SNPs included in some studies was low, <3, so we used the WR model, resulting in a final conclusion that may not be solid and needs to be further supported by more studies. Thirdly, our analysis focused specifically on cysteine cathepsins and their association with autoimmune diseases, neglecting the potential contribution of other genetic variations or environmental factors. Therefore, our findings should be interpreted cautiously, and further research incorporating a broader range of genetic variations and considering environmental factors is warranted to validate and extend our results.

5. Conclusion

In summary, the objective of our study was to examine the causal association between cysteine cathepsins and autoimmune diseases using the MR method. Our study revealed that cathepsin B is positively associated with the susceptibility to psoriasis, cathepsin F is positively associated with the susceptibility to UC, AS, and PBC, cathepsin H is inversely associated with the susceptibility to celiac disease but positively associated with the susceptibility to T1D and PBC, and cathepsin Z is positively associated with the susceptibility to T1D.

Acknowledgments

We thank researchers such as Mbatchou J et al, Sakaue S et al, Nielsen JB, and Sun BB, for providing the publicly available GWAS data for this study.

Author contributions

Conceptualization: Yetong Wu, Qiaoqiao Li, Zhongzheng Zhou, Jing Huang.

Data curation: Yetong Wu, Qiaoqiao Li, Yake Lou.

Formal analysis: Yetong Wu, Qiaoqiao Li, Yake Lou, Zhongzheng Zhou.

Funding acquisition: Zhongzheng Zhou, Jing Huang.

Investigation: Yetong Wu, Qiaoqiao Li, Yake Lou, Jing Huang.

Methodology: Yetong Wu, Qiaoqiao Li, Zhongzheng Zhou, Jing Huang.

Project administration: Jing Huang.

Resources: Qiaoqiao Li, Jing Huang.

Software: Yetong Wu, Qiaoqiao Li.

Supervision: Yetong Wu, Qiaoqiao Li, Yake Lou, Zhongzheng Zhou, Jing Huang.

Validation: Yetong Wu, Qiaoqiao Li, Jing Huang.

Visualization: Yetong Wu, Qiaoqiao Li, Yake Lou.

Writing – original draft: Yetong Wu.

Writing – review & editing: Yetong Wu, Qiaoqiao Li, Yake Lou, Zhongzheng Zhou, Jing Huang.