
==== Front
Medicine (Baltimore)
Medicine (Baltimore)
MD
Medicine
0025-7974
1536-5964
Lippincott Williams & Wilkins Hagerstown, MD

MD-D-24-03446
00034
10.1097/MD.0000000000039666
3
3600
Research Article
Observational Study
Causal links between 13 autoimmune diseases and graft dysfunction: A Mendelian randomization study
Pan Ziwen MD, PhD a
https://orcid.org/0009-0004-5068-3943
Zhong Lin MM a*
a Department of Organ Transplantation, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
* Correspondence: Lin Zhong, Department of Organ Transplantation, The Second Affiliated Hospital of Nanchang University, Nanchang 330038, Jiangxi, China (e-mail: zhonglinteam@163.com).
13 9 2024
13 9 2024
103 37 e3966631 3 2024
17 8 2024
22 8 2024
Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal.

Previous studies have suggested a possible link between autoimmune diseases and graft dysfunction; however, a causal link remains unclear. Exposure factors were set as 13 autoimmune diseases, and outcomes were set as graft dysfunction. Mendelian randomization was used to analyze the causal link between exposure and outcome. Alopecia areata and asthma were linked to graft dysfunction (odds ratio 0.828; 95% confidence interval 0.699–0.980; P = .029; odds ratio 1.79; 95% confidence interval 1.069–2.996; P = .027). At the same time, primary sclerosing cholangitis was found to be heterogeneous as an exposure factor (P = .009), but no heterogeneity or pleiotropy was found in other exposure factors. Our preliminary findings show 2 autoimmune diseases as risk factors for graft dysfunction, 1 autoimmune disease as a protective factor for graft dysfunction and the mechanisms remain to be understood.

autoimmune disease
graft dysfunction
Mendelian randomization
OPEN-ACCESSTRUE
==== Body
pmc1. Introduction

In the early days of organ transplantation, graft failure often occurred due to acute rejection. With the advent of immunosuppressants, the incidence of rejection has significantly decreased and the survival time of grafts has also been greatly improved.

With the application of new immunosuppressants, graft survival has been greatly improved, but the occurrence of rejection and the recurrence of autoimmune diseases were still 1 of the main reasons affecting graft survival.[1] Autoimmune diseases represent a family of at least 80 diseases that share a common feature: an immune-mediated attack on the body‘s own organs.[2] When autoimmune diseases target solid organs, causing dysfunction of these organs or further organ failure, these patients undergo organ transplantation.[3–5]

For patients with autoimmune diseases, a large proportion of them relapse after organ transplantation, leading to graft dysfunction and ultimately graft failure, which poses a great challenge to transplantation physicians.[6] Autoimmune liver diseases include primary sclerosing cholangitis (PSC), primary biliary cholangitis (PBC), and autoimmune hepatitis. Although these patients have a relatively high graft survival rate within 10 years after liver transplantation, recurrence of the primary disease is not uncommon in these patients. Tanaka et al[7]summarized the recurrence of autoimmune liver diseases after transplantation and found that the recurrence rate was 10.9% to 53% for PBC, 8.2% to 44.7% for PSC, and 7% to 42% for autoimmune hepatitis. Some studies have also found an association between PSC recurrence and acute cellular rejection (ACR). Kugelmas et al[8] retrospectively analyzed 71 patients with PSC who underwent liver transplantation, and 21 patients relapsed, in which they also found that ACR was associated with a higher risk of PSC recurrence. Alexander et al[9] found that ACR predicts increased risk of PSC recurrence. Kidney transplant patients also suffer from recurrence of autoimmune diseases, such as IgA nephropathy and lupus nephritis (a subtype of systemic lupus erythematosus). Lionaki et al[10] analyzed the recurrence rate of IgA nephropathy after renal transplantation in different centers and found that the recurrence rate of patients who underwent graft biopsy according to clinical indications was 13 to 50%, and the graft loss was 1.3% to 16%. Nijim et al[11]studied 114 patients with IgA nephropathy in this center, of whom 23 (19%) had recurrence of IgA nephropathy. Tanaka et al[7] found that in patients with lupus nephritis who underwent kidney transplantation, the probability of biopsy-proven lupus nephritis recurrence was 30 to 44%. Uffing et al[12] conducted a multicenter retrospective analysis of recurrence after renal transplantation in adults with IgA nephropathy from 2005 to 2015. They found that 82 patients had relapsed IgA nephropathy, and that patients with relapsed IgA nephropathy had poorer graft survival than those without relapsed IgA nephropathy. After transplantation, the prognosis of patients with these autoimmune diseases was still poor, which brought a huge economic burden to the patients. Therefore, it is of great interest to study the link between autoimmune diseases and graft dysfunction.

Mendelian randomization (MR) analysis is a method that uses genetic data as instrumental variables to infer the causal link between exposure factors and outcomes.[13] Compared with traditional observational studies, MR studies can avoid confounding factors, reverse causality or other forms of inter-slice problems.[14] There have been many MR studies in the direction of autoimmune diseases, such as autoimmune diseases and Alzheimer disease,[15] autoimmune diseases and COVID-19,[16] autoimmune diseases with the occurrence and 28-day mortality of sepsis.[17] However, to our knowledge, there has been no MR analysis exploring the causal link between autoimmune disease and graft dysfunction.

This study mainly used MR analysis to explore the causal link between autoimmune diseases and graft dysfunction. Through MR analysis, we found a causal link between asthma and alopecia areata (AA) and graft dysfunction.

2. Methods

We use MR to analyze causal links between autoimmune diseases and graft dysfunction. Our study is based on data published by our predecessors, all of which have obtained appropriate ethics documentation, any further ethical reviews were not needed.

2.1. Study design

MR analysis was based on 3 assumptions[18]: (1) instrumental variables must be closely related to exposure factors; (2) instrumental variables should not be correlated with exposure-outcome confounders; (3) instrumental variables affect the outcome only through exposure. Figure 1 shows the experimental flow chart of the results of this MR study.

Figure 1. Schematic of the study process.

2.2. Data source

Detailed information on exposure and outcome data can be found in Table 1. The included population of 13 autoimmune diseases mainly consists of 1,279,101 mostly European populations. The included population of graft dysfunction mainly consists of 199,385 all European populations. Single-nucleotide polymorphisms (SNPs) associated with 13 autoimmune diseases and failure and rejection after organ or tissue transplantation, respectively, through the GWAS database (https://gwas.mrcieu.ac.uk/). Ethical approvals were obtained for all the data sources that were used in this study.

Table 1 GWAS information.

Disease	Cases	Controls	Sample size	Datasets in the GWAS	
 RA	14,361	43,923	58,284	ebi-a-GCST90013534	
 SLE	5201	9066	14,267	ebi-a-GCST003156	
 CD	14,763	15,977	30,740	ieu-a-10	
 MS	14,498	24,091	38,589	ieu-a-1025	
 PSC	2871	12,019	14,890	ieu-a-1112	
 PBC	2861	8514	11,375	ebi-a-GCST005581	
 T1D	9266	15,574	24,840	ebi-a-GCST010681	
 UC	13,768	33,977	47,745	ieu-a-970	
Eczema	180,129	180,709	360,838	ebi-a-GCST005038	
Asthma	56,167	352,255	408,442	ebi-a-GCST90014325	
 CeD	12,041	12,228	24,269	ieu-a-1058	
 PsO	10,588	22,806	33,394	ebi-a-GCST005527	
 AA	289	211,139	211,428	finn-b-L12_ALOPECAREATA	
 Graft dysfunction	124	199,271	199,395	finn-b-ST19_FAILU_REJEC_TRANSPLANTED_ORGANS_TISSU	
AA = Alopecia areata, CD = Crohn disease, CeD = celiac disease, MS = multiple sclerosis, PBC = primary biliary cirrhosis, PSC = primary sclerosing cholangitis, PsO = psoriasis, RA = rheumatoid arthritis, SLE = systemic lupus erythematosus, T1D = type 1 diabetes, UC = ulcerative colitis.

2.3. SNP selection

In this study, SNPs that were strong (P < 5 × 10‐8) and independent (Kb > 10,000 and r2 < 0.001) were screened that harmonize the exposure and outcome data. Next, we calculate the F value according to the following formula: F = R2(n − k − 1)/k(1 − R2), R2 = β2 × 2 × MAF × (1 − MAF). Here, n = sample size; and k = number of instrumental variables, β represents the estimated effect and MAF indicates the minor allele frequency and finally select instrumental variables with F value >10 for MR analysis. Among the exposure factors, AA failed to screen out SNP according to the original conditions, so it was set to P < 5 × 10‐6. The original data of systemic lupus erythematosus, PBC, and psoriasis lack the data to calculate the F value, and the standard of F value >10 cannot be implemented.

2.4. Statistical analysis

IVW as the primary method to analyze causal links between exposures and outcomes. Pleiotropy was tested through MR-Egger regression. Heterogeneity was tested through MR-Egger and IVW methods. Cochran Q test was used to assess heterogeneity. Leave-one-out sensitivity analysis was performed. MR results were presented as odds ratio (OR) and corresponding 95% confidence interval (CI). R (version 4.3.1) and TwoSampleMR package (version 0.5.7; R Foundation for Statistical Computing, Vienna, Austria) were used for data analysis and visualization.

3. Results

3.1. Impact of 13 autoimmune diseases on graft dysfunction

After rigorous screening, the number of SNPs for 13 autoimmune diseases ranged from 11 to 120. The causal relationship between 13 autoimmune diseases and graft dysfunction is presented in Figure 2; asthma (OR 1.79; 95% CI 1.069–2.996; P = .027), and AA (OR 0.828; 95% CI 0.699–0.980; P = .029). Our results showed heterogeneity only when PBC was used as an exposure factor (P = .009). There was no pleiotropic effect among all exposure factors (P > .05). The heterogeneity and pleiotropy results of all analyzed results can be seen in Table 2.

Table 2 Sensitivity and polymorphism analysis results of MR.

Disease	Heterogeneity	Pleiotropy	
MR-Egger	IVW	
  RA	0.307	0.303	0.294	
  SLE	0.272	0.231	0.157	
  CD	0.220	0.238	0.703	
  MS	0.089	0.098	0.538	
  PSC	0.195	0.243	0.849	
  PBC	0.009	0.010	0.474	
  T1D	0.643	0.637	0.306	
  UC	0.606	0.615	0.412	
 Eczema	0.466	0.471	0.365	
 Asthma	0.521	0.553	0.997	
  CeD	0.968	0.981	0.880	
Alopecia areata	0.383	0.475	0.942	
  PsO	0.172	0.197	0.828	

Figure 2. Mendelian randomization analysis of 13 autoimmune diseases and graft dysfunction.

4. Discussion

As far as we know, this is the first MR analysis to explore causal links between autoimmune disease and graft dysfunction using large-scale data. Using two-sample MR analysis, we found that 2 autoimmune diseases (asthma and AA) are causally linked to graft dysfunction, thus inferring that asthma may be risk factor for graft dysfunction and AA may be protective factor for graft dysfunction. However, we were unable to find a causal link between other autoimmune diseases and graft dysfunction.

Asthma is a complex chronic inflammatory disease of the lower respiratory tract and one of the most common respiratory diseases affecting adults and children worldwide.[19] The pathogenesis of asthma is complex and currently unclear. Some risk factors for asthma that have been identified include: air pollutants, allergens, exposure to microorganisms, acetaminophen, oral supplement intake, and obesity.[19] After allergen exposure, allergen-specific Th2 cells produce type 2 cytokines leading to the accumulation of massive eosinophils in the airway walls.[20] Th2 cells were traditionally thought to be involved in suppressing inflammatory responses and promoting tolerance. However, some studies have found that eosinophils are also involved in graft rejection.[21] Some studies have found that serum IL-33 levels in asthma patients are increased compared with normal controls. And compared with non-allergic and non-eosinophilic patients, patients with allergic eosinophilic asthma have elevated serum IL-33 levels.[21] IL-33 is a member of the IL-1 cytokine family, which can be secreted by a variety of cells and produce pro-inflammatory or anti-inflammatory effects depending on the environment.[22] Yin et al[23] found that IL-33 can be used as an effective inducer of Th2 immune response and can significantly prolong the survival time of mouse allogeneic heart transplantation. However, recent findings appeared to contradict this, showing a role for IL-33 in lung allograft tolerance and acceleration of chronic rejection.[24] Our MR results show that asthma promotes graft dysfunction, there are no reports related to asthma and graft dysfunction. Asthma may promote graft dysfunction by promoting the release of IL-33 from eosinophils during asthma attacks, thereby causing graft damage. The specific mechanism still needs further experimental confirmation.

AA is an autoimmune disease and a common form of hair loss characterized by non-scarring loss of hair on the scalp or any hair surface.[25] The pathogenesis of AA is relatively complex, and current hypotheses include infectious diseases, toxic substances, neurological and endocrine disorders, and loss of hair follicle immune privilege.[26] As an immune-privileged (IP) site, the hair follicle promotes the formation of a local immunosuppressive environment.[27] IP refers to a phenomenon in which an organ or tissue is protected from host immune system. The IP of hair follicles is usually maintained during the anagen phase by downregulating the expression of major histocompatibility complex class I molecules and the expression of NK and CD8 + T cell inhibitors.[28] Our MR analysis results showed that AA could inhibit the formation of graft dysfunction, we speculated that the potential reason why AA patients were less susceptible to graft dysfunction after transplantation was the immune privilege of AA. However, further experiments are still needed to confirm our analysis results.

The strength of our study is that we are the first to use the largest and most comprehensive GWAS data to analyze the causal link between autoimmune diseases and graft dysfunction. Secondly, we have used strict criteria to screen IVs to reduce bias in results. However, the current study has certain limitations. First, in our data source, most of the 13 autoimmune diseases are from European populations, and graft dysfunction is all from European populations, which limits the generalizability of the analysis results to other populations. Second, the number of cases of graft dysfunction is small, and there is no clinical information on these patients, including transplant type, preoperative immunological matching results, etc. Third, some autoimmune diseases preferentially occur in patients of a specific gender. For example, systemic lupus erythematosus is more likely to occur in female patients, and PSC is more likely to occur in male patients. There is no GWAS data for the corresponding gender. Finally, MR analysis can only explain the causal link between exposure factors and outcomes from a genetic perspective. More comprehensive experiments are needed to confirm the causal link between autoimmune diseases and graft dysfunction.

5. Conclusion

In summary, our study initially explored the causal link between 13 autoimmune diseases and graft dysfunction. Through MR analysis, we found that 2 autoimmune diseases (Asthma and AA) may be causally related to graft dysfunction. However, more research is needed in the future to establish the link between 13 autoimmune diseases and graft dysfunction.

Acknowledgments

We thank the participants and staff of these open GWAS data.

Author contributions

Conceptualization: Ziwen Pan, Lin Zhong.

Data curation: Ziwen Pan, Lin Zhong.

Formal analysis: Ziwen Pan, Lin Zhong.

Writing – original draft: Ziwen Pan.

Writing – review & editing: Lin Zhong.

Abbreviations:

AA alopecia areata

ACR acute cellular rejection

CI confidence interval

IP immune-privileged

MR Mendelian randomization

OR odds ratio

PBC primary biliary cholangitis

PSC primary sclerosing cholangitis

SNPs single-nucleotide polymorphisms

The authors have no funding and conflicts of interest to disclose.

The datasets generated during and/or analyzed during the current study are publicly available.

How to cite this article: Pan Z, Zhong L. Causal links between 13 autoimmune diseases and graft dysfunction: A Mendelian randomization study. Medicine 2024;103:37(e39666).
==== Refs
References

[1] Bierzynska A Saleem MA . Deriving and understanding the risk of post-transplant recurrence of nephrotic syndrome in the light of current molecular and genetic advances. Pediatr Nephrol. 2018;33 :2027–35.29022104
[2] Rose NR . Prediction and prevention of autoimmune disease in the 21st century: a review and preview. Am J Epidemiol. 2016;183 :403–6.26888748
[3] Lee JC Ahya VN . Lung transplantation in autoimmune diseases. Clin Chest Med. 2010;31 :589–603.20692549
[4] Wong T Goral S . Lupus nephritis and kidney transplantation: where are we today? Adv Chronic Kidney Dis. 2019;26 :313–22.31733715
[5] Carbone M Neuberger JM . Autoimmune liver disease, autoimmunity and liver transplantation. J Hepatol. 2014;60 :210–23.24084655
[6] Couchonnal E Jacquemin E Lachaux A . Long-term results of pediatric liver transplantation for autoimmune liver disease. Clinics Res Hepatol Gastroenterol. 2021;45 :101537.
[7] Tanaka A Kono H Leung PSC Gershwin ME . Recurrence of disease following organ transplantation in autoimmune liver disease and systemic lupus erythematosus. Cell Immunol. 2020;347 :104021.31767117
[8] Kugelmas M Spiegelman P Osgood MJ . Different immunosuppressive regimens and recurrence of primary sclerosing cholangitis after liver transplantation. Liver Transplant. 2003;9 :727–32.
[9] Alexander J Lord JD Yeh MM Cuevas C Bakthavatsalam R Kowdley KV . Risk factors for recurrence of primary sclerosing cholangitis after liver transplantation. Liver Transplant. 2008;14 :245–51.
[10] Lionaki S Panagiotellis K Melexopoulou C Boletis JN . The clinical course of IgA nephropathy after kidney transplantation and its management. Transplantation Rev (Orlando, Fla). 2017;31 :106–14.
[11] Nijim S Vujjini V Alasfar S . Recurrent IgA nephropathy after kidney transplantation. Transplant Proc. 2016;48 :2689–94.27788802
[12] Uffing A Pérez-Saéz MJ Jouve T . Recurrence of IgA nephropathy after kidney transplantation in adults. Clin J Am Soc Nephrol. 2021;16 :1247–55.34362788
[13] Bowden J Holmes MV . Meta-analysis and Mendelian randomization: a review. Res Synthesis Methods. 2019;10 :486–96.
[14] Richmond RC Davey Smith G . Mendelian Randomization: concepts and scope. Cold Spring Harbor Perspectives Med. 2022;12 :a040501.
[15] Yeung CHC Au Yeung SL Schooling CM . Association of autoimmune diseases with Alzheimer’s disease: a mendelian randomization study. J Psychiatr Res. 2022;155 :550–8.36198219
[16] Li S Yuan S Schooling CM Larsson SC . A Mendelian randomization study of genetic predisposition to autoimmune diseases and COVID-19. Sci Rep. 2022;12 :17703.36271292
[17] Li H Pan X Zhang S . Association of autoimmune diseases with the occurrence and 28-day mortality of sepsis: an observational and Mendelian randomization study. Crit Care. 2023;27 :476.38053214
[18] Zheng J Baird D Borges MC . Recent developments in Mendelian Randomization studies. Curr Epidemiol Reports. 2017;4 :330–45.
[19] Alizadeh Z Mortaz E Adcock I Moin M . Role of epigenetics in the pathogenesis of asthma. Iran J Allergy Asthma Immunol. 2017;16 :82–91.28601047
[20] Hammad H Lambrecht BN . The basic immunology of asthma. Cell. 2021;184 :1469–85.33711259
[21] Goldman M Le Moine A Braun M Flamand V Abramowicz D . A role for eosinophils in transplant rejection. Trends Immunol. 2001;22 :247–51.11323281
[22] Chen J He Y Xie Z Wei Y Duan L . The Role of IL-33 in experimental heart transplantation. Cardiol Res Pract. 2020;2020 :6108362.32257426
[23] Yin H Li XY Jin XB . IL-33 prolongs murine cardiac allograft survival through induction of TH2-type immune deviation. Transplantation. 2010;89 :1189–97.20220570
[24] Hassan GF Cohen LS Alexander-Brett J . IL-33: friend or foe in transplantation? J Heart Lung Transplant. 2024;43 :1235–40.38452960
[25] Pratt CH King LE Jr. Messenger AG Christiano AM Sundberg JP . Alopecia areata. Nat Rev Dis Primers. 2017;3 :17011.28300084
[26] Rajabi F Drake LA Senna MM Rezaei N . Alopecia areata: a review of disease pathogenesis. Br J Dermatol. 2018;179 :1033–48.29791718
[27] Zhou C Li X Wang C Zhang J . Alopecia Areata: an update on etiopathogenesis, diagnosis, and management. Clin Rev Allergy Immunol. 2021;61 :403–23.34403083
[28] Simakou T Butcher JP Reid S Henriquez FL . Alopecia areata: a multifactorial autoimmune condition. J Autoimmun. 2019;98 :74–85.30558963
