Association Between Inflammatory Bowel Disease and Both Psoriasis and Psoriatic Arthritis: A Bidirectional 2-Sample Mendelian Randomization Study

Dennis Freuer; Jakob Linseisen; Christa Meisinger

doi:10.1001/jamadermatol.2022.3682

. 2022 Sep 14;158(11):1262–1268. doi: 10.1001/jamadermatol.2022.3682

Association Between Inflammatory Bowel Disease and Both Psoriasis and Psoriatic Arthritis

A Bidirectional 2-Sample Mendelian Randomization Study

Dennis Freuer ^1,^✉, Jakob Linseisen ^1,², Christa Meisinger ¹

PMCID: PMC9475439 PMID: 36103169

This mendelian randomization study investigates the associations between inflammatory bowel disease, particularly Crohn disease and ulcerative colitis, and psoriasis and psoriatic arthritis.

Key Points

Question

Is there evidence for a potential relationship between inflammatory bowel disease (IBD) and psoriasis or psoriatic arthritis?

Findings

This mendelian randomization study based on genome-wide association studies including up to 463 372 European individuals found a positive association of IBD (particularly Crohn disease) with both psoriasis and psoriatic arthritis.

Meaning

Findings suggest that IBD seems to be a causal risk factor for psoriasis and psoriatic arthritis, but not vice versa.

Abstract

Importance

Psoriasis, psoriatic arthritis, and inflammatory bowel disease, ie, Crohn disease and ulcerative colitis, are chronic systemic immune-mediated disorders affecting an increasing proportion of adults and children worldwide. Observational studies have suggested an association between inflammatory bowel disease and psoriasis and vice versa. So far, however, it remains unclear whether and in which direction causal relationships exist.

Objective

To investigate the association between inflammatory bowel disease, particularly Crohn disease and ulcerative colitis, and psoriasis or psoriatic arthritis.

Design, Setting, and Participants

A bidirectional 2-sample mendelian randomization study was conducted using summary statistics from genome-wide association studies including up to 463 372 European individuals. Total and direct effects were derived performing an iterative radial and robust inverse-variance weighted method within the univariable and multivariable mendelian randomization setting, respectively. Causal estimates were verified using a validation inflammatory bowel disease sample, a series of pleiotropy-robust mendelian randomization methods, and sensitivity analyses based on a PhenoScanner search in conjunction with network analysis. Data analysis was performed from April to May 2022.

Main Outcomes and Measures

Inflammatory bowel disease, Crohn disease, ulcerative colitis, psoriasis, and psoriatic arthritis were used as both exposures and outcomes.

Results

The European samples included 12 882 cases of inflammatory bowel disease and 5621 cases of psoriasis. The proportion of women ranged between 48% and 56%. Genetically predicted inflammatory bowel disease was associated with higher risk of psoriasis (pooled odds ratio [OR], 1.10; 95% CI, 1.05-1.15; P < .001) and psoriatic arthritis (pooled OR, 1.10; 95% CI, 1.04-1.18; P = .003). In contrast with ulcerative colitis, the Crohn disease subentity was associated with psoriasis (OR, 1.16; 95% CI, 1.12-1.20; P < .001) and psoriatic arthritis (OR, 1.13; 95% CI, 1.06-1.20; P < .001). Regarding the reverse directions, no notable associations could be found.

Conclusions and Relevance

Findings of this mendelian randomization study support a causal effect between inflammatory bowel disease and psoriasis as well as psoriatic arthritis, but not vice versa. It seems that especially Crohn disease and not ulcerative colitis is responsible for the causal effect of inflammatory bowel disease on both psoriasis outcomes. These findings have implications for the management of inflammatory bowel disease and psoriasis in clinical practice.

Introduction

Psoriasis is a chronic relapsing immune-mediated disease of the skin affecting approximately 2% to 3% of people worldwide.¹ The prevalence ranges from 0.5% to 11.4% in adults and approximately 1.4% in children.² In 2019, there were approximately 4.5 million new cases and approximately 40 million prevalent cases of psoriasis worldwide. Compared with 1990, the incidence and prevalence, which are similar in men and women, decreased by 20.0% and 23.7%, respectively. Both prevalence and incidence rates are highest in high-income countries, and the burden of the disease is greatest in the 60- to 69-year-old age group.¹Psoriasis is caused by a constellation of environmental, immunogenic, and genetic factors³ and is chronic, incurable, and physically and emotionally debilitating.^4,5,6 It is not only a disease of the skin, but a systemic disease that also affects other parts of the body, such as the joints, the cardiovascular system, and the central nervous system.⁷ About 30% of patients with psoriasis experience psoriatic arthritis, a systemic inflammatory arthritis sharing common pathogenetic and immunologic features with psoriasis.^8,9,10,11 Furthermore, it is now recognized that psoriasis is associated with other immune-mediated inflammatory conditions; in particular, inflammatory bowel disease (IBD), including Crohn disease (CD) and ulcerative colitis (UC) as the main subtypes, appears to frequently co-occur with the disease.^12,13,14 Worldwide, approximately nearly 3.9 million women and about 3.0 million men experience IBD, and the number of prevalent cases is increasing. As psoriasis, IBD is also considered a condition of high-income countries.¹⁵ Evidence is accumulating that psoriasis and IBD share several genetic susceptibility loci and that the pathogenetic mechanisms underlying both diseases partially overlap.^16,17,18

Some previous cross-sectional and prospective epidemiological studies as well as meta-analyses have reported an increased risk of IBD in patients with psoriasis and vice versa.^{19,20,21,22,23} However, so far, it remains unclear whether there is a causal relationship between these 2 inflammatory diseases because in observational studies, bias owing to confounding and reverse causation cannot be excluded. Therefore, in the present study, we performed a 2-sample summary data mendelian randomization (MR) analysis to investigate the causal effects of IBD, including its subentities CD and UC, on the risk of both psoriasis and psoriatic arthritis and vice versa.

Methods

Study Design

To investigate the associations between IBD and psoriasis as well as psoriatic arthritis, we performed iteratively bidirectional 2-sample MR analyses based on summary statistics of genome-wide association studies (GWASs). In an instrumental variable setting, MR uses genetic variants as proxies for a specific modifiable risk factor to estimate and test for a causal effect with an outcome. The random allocation of genetic variants at conception based on Mendel’s laws ensures the independency from any confounding factors and in this way mimics a randomized controlled trial. Moreover, if the core assumptions (relevance, independence, and exclusion restriction assumptions) are met, this study design overcomes reverse causation, which may be an issue in observational studies. Details about the MR design can be found elsewhere.^24,25 Ethics approval was not required because the study is based on summary-level data. In all original studies, ethical approval and participant consent to participate had been obtained. Strengthening the Reporting of Observational Studies in Epidemiology Using Mendelian Randomization (STROBE) reporting guideline.

Study Samples and Measures

With regard to the evidence, we used 2 different GWAS data sets for IBD. The discovery sample included 12 882 clinically diagnosed IBD cases (21 770 controls) based on up to 15 studies considering the European population.²⁶ Additionally, 5956 diagnosed CD cases (14 927 controls) and 6968 diagnosed UC cases (20 464 controls) were available from this cohort (Table). Diagnosis was made by radiological, endoscopic, and histopathological examinations. The validation sample consisted of 7045 self-reported IBD cases (456 327 controls) from the UK Biobank cohort.²⁷ A total of 5621 psoriasis and 2063 psoriatic arthritis cases were obtained from the FINNGEN Consortium and compared with 252 323 controls of European ancestry.²⁸

Table. Description of Samples.

Characteristic	IBD	IBD (val)	CD	UC	PsO	PsA
Sample size	34 652	456 327	20 883	27 432	257 944	254 386
Cases, abs (rel)	12 882 (0.372)	7045 (0.015)	5956 (0.285)	6968 (0.254)	5621 (0.022)	2063 (0.008)
SNVs not in LD	62	28	52	37	19	9

Open in a new tab

Abbreviations: abs, absolute; CD, Crohn disease; IBD, inflammatory bowel disease; LD, linkage disequilibrium; PsA, psoriatic arthritis; PsO, psoriasis; rel, relative; SNV, single-nucleotide variation; UC, ulcerative colitis; val, validation.

Instruments Selection

For each analysis, we selected single-nucleotide variations (SNVs; formerly single-nucleotide polymorphisms or SNPs) that were associated with the respective exposure at the genome-wide significance threshold P = 5 × 10⁻⁸. Where possible, we restricted the SNVs to an imputation score of 0.8 or higher. To ensure independency, the genetic instruments underwent a PLINK clumping process. Regarding the European 1000 genomes reference panel, SNVs in linkage disequilibrium were pruned within a 10 000-kb window considering a minor allele frequency greater than 0.01 and a clumping cutoff r² of 0.001. Within the harmonization step, we removed palindromic SNVs with a minor allele frequency greater than 0.42 and searched, if necessary, for proxy SNVs in the outcome data set using an r² greater than 0.8.

Thus, starting with the number of independent SNVs reported in the Table, 26 to 61 potential instruments for IBD and its subentities and 4 to 15 instrumental SNVs for the psoriasis phenotypes remained after the harmonization process (eTables 1 and 2 in the Supplement).

Statistical Analyses

The statistical analysis consists of 3 parts. First, univariable MR analyses were performed to investigate total effects. Second, multivariable MR analyses were conducted to distinguish the effects of either the IBD subentities or psoriasis and psoriatic arthritis and, in doing so, to calculate direct effects. Third, a series of sensitivity analyses were applied to assess the consistency of estimates and thus the plausibility of the MR core assumptions. This was done by applying pleiotropy-robust MR methods as well as by excluding instruments that are likely to be associated with confounding factors of the respective exposure-outcome association.

Univariable MR

In detail, within the radial regression framework, we used iteratively the inverse variance-weighted (IVW) method with modified second order weights as the main analysis. In each iteration step, outlier SNVs were detected and removed based on the SNV-specific Cochran Q and Rucker Q′ statistics based on a type I error of α_Q = .01 (eTable 3 in the Supplement). In addition, under a fixed-effects model, a pooled causal meta-analysis estimate was derived for both IBD samples.

Multivariable MR

Regarding the overlap of genetic instruments between both IBD subentities CD and UC as well as psoriasis and psoriatic arthritis, we performed bidirectional multivariable MR analyses to calculate the direct effects, that is, the influence on an outcome that can be directly attributed to the exposure of interest and not to another. As the main approach, the robust IVW method with multiplicative random effect was applied, and heterogeneity was assessed using Q statistics.

Sensitivity Analyses

To evaluate possible horizontal pleiotropy in case of invalid instruments, a broad range of methods, which are robust to specific patterns of heterogeneity, were applied to the final models. In the univariable case, these include the MR-Egger, weighted median, and weighted mode methods.²⁹ Additionally, a many weak instruments analysis was done using the Robust Adjusted Profile Score (RAPS) with a robust loss function and consideration of overdispersion.³⁰ The MR-PRESSO framework³¹ was used to test for pleiotropy (global test), if necessary to correct the estimate by removing outliers (outlier test), and test for the distortion between both estimates. Directional pleiotropy in the final models was assessed using the radial MR-Egger intercept test and influential SNVs were investigated within a leave-one-out analysis as well as graphical evaluation of the radial and scatter (SNV-exposure vs SNV-outcome associations) plots. In the multivariable setting, MR-Egger, median, modified IVW, and MR-Lasso³² methods were used as sensitivity analyses, whereas directional pleiotropy was tested with the MR-Egger intercept test.

As a further sensitivity analysis, we accounted for possible confounding factors of the exposure-outcome associations using the following steps in both univariable and multivariable settings. We applied a PhenoScanner search^33,34 to assess all known phenotypes related to the considered genetic instruments in our analyses. We then performed a network analysis to cluster all identified phenotypes into logical groups rather than just looking at individual phenotypes (eg, obesity rather than body mass index or waist-to-hip ratio). Finally, we removed SNVs associated with 1 cluster per analysis and compared them with the causal estimates from the main approaches.

Based on a type I error a = .05 in this study, evidence for a causal relationship was considered sufficient, if and only if all methods used confirmed it with respect to heterogeneity statistics as well as consistent point estimates from sensitivity analyses. Estimates were presented as odds ratios (ORs) with 95% CIs and can be interpreted as the average change in the outcome per 2.72-fold increase in the prevalence of the respective binary exposure.

Analyses were done using the statistical software R (version 4.1.2; R Foundation for Statistical Computing). For the most of the part, the packages TwoSampleMR (version 0.5.6), RadialMR (version 1.0), MRPRESSO (version 1.0), MendelianRandomization (version 0.6.0), mr.raps (version 0.2), MVMR (version 0.3), data.table (version 1.14.2), dplyr (version 1.0.8), and ggplot2 (version 3.3.5) were used. Gephi (version 0.9) was used for the network analysis.

Results

Main Results

Univariable MR

In the univariable case, main results were derived from the radial IVW method with modified second-order weights after the last iteration and presented as ORs with 95% CIs. Genetically predicted IBD was positively associated with both psoriasis (OR, 1.09; CI, 1.04-1.15; P = .001) and psoriatic arthritis (OR, 1.09; CI, 1.01-1.17; P = .03), which was confirmed by the validation sample (Figure 1). The pooled meta-analysis estimates were as follows: OR, 1.10; CI, 1.05-1.15; P < .001 for psoriasis, and OR, 1.11; CI, 1.04-1.18; P = .003 for psoriatic arthritis (Figure 2). Subgroup analyses revealed that these associations could be attributed to CD (ORs between 1.13 and 1.16) but not UC (ORs between 1.01 and 1.03) (Figure 1). There was no indication of causal effects in the reverse directions (Figure 1).

Figure 1. — Causal estimates for the effect of inflammatory bowel disease (IBD) and its subentities Crohn disease (CD) and ulcerative colitis (UC) on psoriasis (PsO) and psoriatic arthritis (PsA) (forward direction) (A) and vice versa (reverse direction) (B). For IBD, a discovery sample of clinically diagnosed cases from 15 European studies and a validation sample (IBD [val]) of self-reported cases from UK Biobank were used. Estimates are presented as odds ratios (ORs) and 95% CIs from bidirectional mendelian randomization analyses.

Figure 2. — Pooled causal estimates for the effect of inflammatory bowel disease (IBD) on psoriasis and psoriatic arthritis (forward direction) (A) and vice versa (reverse direction) (B). Estimates were calculated applying a meta-analysis fixed-effect model on the discovery and validation samples. Results are presented as odds ratios (ORs) and 95% CIs from bidirectional mendelian randomization analyses.

Multivariable MR

The estimates presented for the main results in this section originated from the multivariable robust IVW model with multiplicative random effects. After reciprocal adjustment, CD was associated with psoriasis (OR, 1.16; CI, 1.10-1.23; P < .001) and psoriatic arthritis (OR, 1.12; CI, 1.04-1.21; P = .002) while UC was not associated with both psoriasis outcomes (psoriasis: OR, 0.98; CI, 0.92-1.04; P = .41; psoriatic arthritis: OR, 0.98; CI, 0.91-1.07; P = .70) (Figure 3). Consequently, the direct effects were even stronger than the total effects from the univariable analyses. Again, no notable genetically predicted associations were observed in the reverse directions (Figure 3).

Figure 3. — Direct effect estimates obtained from bidirectional multivariable mendelian randomization analyses. Crohn disease (CD) and ulcerative colitis (UC) were mutually adjusted in the forward direction (A) and psoriasis (PsO) and psoriatic arthritis (PsA) in the reverse direction (B), respectively. For IBD, a discovery sample of clinically diagnosed cases from 15 European studies and a validation sample (IBD [val]) of self-reported cases from UK Biobank were used. Estimates are presented as odds ratios (ORs) and 95% CIs.

Sensitivity Analyses

In the univariable setting, estimates representing the effect of IBD and its subentities on psoriasis as well as psoriatic arthritis were basically supported by the results of the pleiotropy-robust methods with similar and thus consistent point estimates, indicating reliable results (eFigures 1 and 2 in the Supplement). However, the MR-Egger point estimates were somewhat more heterogeneous compared with the other methods. In the reverse directions, there was a comparable situation with estimates around the null hypothesis. Apart from that, the MR-RAPS and PRESSO approaches could not be calculated for the effect of CD on psoriatic arthritis regarding numerical issues in consequence of the small number of instruments. No directional pleiotropy could be observed due to the radial MR-Egger intercept test (eTable 4 in the Supplement). However, some heterogeneity was revealed by the PRESSO global test and the heterogeneity statistics, especially in the models with psoriatic arthritis as exposure.

In sensitivity analyses of the multivariable setting, all pleiotropy-robust approaches supported the main results (eFigures 3 and 4 in the Supplement). Although there was no evidence for directional pleiotropy, heterogeneity between the particular causal estimates could be observed in the models (eTable 5 in the Supplement).

Using the results from PhenoScanner search based on genetic instruments for IBD and its subentities (eTable 6 in the Supplement), the network analysis revealed, among others, 3 clusters that were considered as potential confounding factors (Figure 4). An obesity-related cluster consisting of 6 SNVs (red colored), an allergic disease–related cluster (16 SNVs; pink, orange, and light blue colored), and an autoimmune disease related cluster (7 SNVs; blue-green colored). Successive removal of the cluster-specific instruments did not substantially change the estimates and thus supported the findings of the univariable as well as multivariable analyses (eFigures 5 and 6 in the Supplement). The illustration summarizing the results of this study can be found in eFigure 7 in the Supplement.

Figure 4. — Result from a network analysis showing the associations between genetic instruments and all known phenotypes obtained from a PhenoScanner search (see eTable 6 in the Supplement). The following clusters of interest were detected: obesity (red), allergic diseases (pink, orange, light blue), and autoimmune diseases (blue-green).

Discussion

Based on the findings of the present study, there is evidence to support a causal link between IBD and psoriasis and psoriatic arthritis but not vice versa. In particular, there was an association between CD and both psoriasis outcomes. The results were supported by a series of sensitivity analyses.

Some previous epidemiological cohort studies^19,20,21 and meta-analyses^22,23 postulated an association between psoriasis and IBD. For example, in a nationwide cohort study from Denmark (n = 5 554 100 individuals aged >18 years; 75 209 incident cases of psoriasis, 11 309 incident cases of CD, and 30 310 cases of UC) significant associations between psoriasis and CD and UC were observed.¹⁹ Another nationwide population-based matched cohort study from Korea reported a more than 2-fold increased risk of psoriasis and psoriatic arthritis in individuals with IBD.²¹ In a systematic review and meta-analysis including 5 case-control or cross-sectional studies and 4 cohort studies with a total of 7 794 087 participants, an increased risk and odds of IBD, CD, and UC in patients with psoriasis was found.²² The meta-analysis based on the 4 cohort studies revealed a 2.53-fold increased risk of CD and a 1.71-fold increased risk of UC in patients with psoriasis in comparison with controls. An increased risk of CD and UC was also observed in patients with psoriatic arthritis.²² Another systematic review and meta-analysis including 93 studies found a significant association between psoriasis and IBD and vice versa.²³ While less than 1% of patients with psoriasis had CD or UC, the proportion of patients with CD or UC and psoriasis was 3.6% and 2.8%, respectively.²³ The prevalence of psoriasis was highest among children and adolescents with IBD, in particular in patients with CD. However, heterogeneity between the studies was high (I² > 98%), and a risk of publication bias was likely.

The present study extends previous research by demonstrating a causal effect of IBD, in particular the subtype CD, on psoriasis, but no causal link in the other direction. The pathophysiologic mechanisms underlying this relationship are not fully understood, but there is little doubt that IBD and psoriasis likely share a common pathogenesis. Explanations for the association between the 2 diseases include shared genetic susceptibility loci,¹⁷ immune dysfunction,^16,18 gut microbiota dysregulation,^35,36,37 and environmental factors.³⁸ Some GWASs confirmed previously known shared risk loci and identified a number of non–human leukocyte antigen susceptibility loci common to psoriasis and CD.³⁹ Gut dysbiosis, a state of microbial imbalance, is frequently observed in both IBD and psoriasis.⁴⁰ It is well known that diseases of the gastrointestinal tract are often associated with skin manifestations, and the gut microbiome appears to be involved in the pathophysiology of many inflammatory diseases.^41,42 One reason for this might be that gut microbiota influences epidermal differentiation signaling pathways, thereby affecting skin homeostasis.^35,37 Furthermore, owing to intestinal dysbiosis, intestinal permeability may be increased, allowing intestinal bacteria or their metabolites to enter the bloodstream and skin, triggering psoriasis pathogenesis.^35,36 Also, IBD and psoriasis share similar immunologic mechanisms. Inflammatory bowel disease has been shown to lead to an overproduction of Th1 cytokines, with a central role attributed to a class of memory T cells characterized by the presence of cutaneous lymphocyte antigen on their surface, which are responsible for settling in the skin and involved in the initiation of psoriasis.^43,44 In addition, the cytokine tumor necrosis factor-α produced by Th17 cells plays an important role in the pathogenesis of IBD and psoriasis.¹⁶

As mentioned earlier, psoriasis is a complex, heterogeneous disease that can affect different parts of the body. In recent years, substantial research progress has been made in the pathogenesis of psoriasis/psoriatic arthritis and the treatment of its various manifestations. However, it is still largely unclear which treatment option is effective for which patient.⁴⁵ A new approach is precision medicine, ie, personalized medicine, which is expected to improve clinical outcomes in psoriasis and reduce the risk of adverse events.⁴⁶ Therefore, current research focuses on discovering predictive and prognostic biomarkers for psoriasis/psoriatic arthritis. Biomarkers are a step toward precision medicine. These allow clinicians to identify subgroups of patients who require the use of more targeted therapies or close monitoring.⁴⁶

Strengths and Limitations

A strength of this study is that it is, to our knowledge, the first to examine the causal bidirectional association between IBD including both CD and UC subgroups and psoriasis as well as psoriatic arthritis using a 2-sample MR analysis. In contrast to observational studies, this method of analysis is less prone to confounding, reverse causality, and nondifferentially measured exposures with error.⁴⁷ Using a more conservative, iterative approach, we were able to minimize heterogeneity, confirm consistency of point estimates before and after removal of outliers, and thus strengthen the evidence. A series of sensitivity analyses confirmed the present results. The findings do not appear to be affected by pleiotropy, as consistent results were obtained in the sensitivity analyses and few outliers were identified using both the iterative IVW and MR-PRESSO methods. The results of this study are based on data from patients of European descent, and therefore generalizability to other ethnicities is limited.

Conclusions

In this MR study, findings suggest a causal association between IBD and psoriasis as well as psoriatic arthritis. In particular, the subentity CD seems to be associated with the development of both psoriasis and psoriatic arthritis. The results of the study are critical because raising awareness among clinicians and primary care physicians about the potential risk of psoriasis in patients with IBD will contribute to systematic diagnosis and interdisciplinary and early personalized treatment of patients. The investigation of pathophysiologic pathways associated with the development of psoriasis in patients with IBD should be the subject of further basic research.

Supplement.

eTable 1. Number of potential instruments for the bidirectional MR analyses

eTable 2. Genetic variants used as potential instruments in the Mendelian randomization analyses

eTable 3. Identified pleiotropic SNPs by the iterative univariable Mendelian randomization approach

eTable 4. Heterogeneity statistics from univariable Mendelian randomization analyses

eTable 5. Heterogeneity statistics from multivariable Mendelian randomization analyses

eTable 6. Phenotypes associated with genetic variants used as potential instruments for IBD, CD, and UC

eFigure 1. Sensitivity analyses of univariable Mendelian randomization (forward)

eFigure 2. Sensitivity analyses of univariable Mendelian randomization (backward)

eFigure 3. Sensitivity analyses of multivariable Mendelian randomization (forward)

eFigure 4. Sensitivity analyses of multivariable Mendelian randomization (backward)

eFigure 5. Sensitivity analyses (SNPs exclusion) of univariable Mendelian randomization (forward)

eFigure 6. Sensitivity analyses (SNPs exclusion) of multivariable Mendelian randomization (forward)

eFigure 7. Summary of the Mendelian randomization study

Click here for additional data file.^{(1.1MB, pdf)}

References

1.Damiani G, Bragazzi NL, Karimkhani Aksut C, et al. The global, regional, and national burden of psoriasis: results and insights from the Global Burden of Disease 2019 Study. Front Med (Lausanne). 2021;8:743180. doi: 10.3389/fmed.2021.743180 [DOI] [PMC free article] [PubMed] [Google Scholar]
2.Michalek IM, Loring B, John SM. A systematic review of worldwide epidemiology of psoriasis. J Eur Acad Dermatol Venereol. 2017;31(2):205-212. doi: 10.1111/jdv.13854 [DOI] [PubMed] [Google Scholar]
3.Chekol Abebe E, Tilahun Muche Z, Behaile T/Mariam A, et al. Role of fetuin-A in the pathogenesis of psoriasis and its potential clinical applications. Clin Cosmet Investig Dermatol. 2022;15:595-607. doi: 10.2147/CCID.S356801 [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Boehncke WH, Schön MP. Psoriasis. Lancet. 2015;386(9997):983-994. doi: 10.1016/S0140-6736(14)61909-7 [DOI] [PubMed] [Google Scholar]
5.Feldman SR, Tian H, Gilloteau I, Mollon P, Shu M. Economic burden of comorbidities in psoriasis patients in the United States: results from a retrospective US database. BMC Health Serv Res. 2017;17(1):337. doi: 10.1186/s12913-017-2278-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Yeung H, Takeshita J, Mehta NN, et al. Psoriasis severity and the prevalence of major medical comorbidity: a population-based study. JAMA Dermatol. 2013;149(10):1173-1179. doi: 10.1001/jamadermatol.2013.5015 [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Langley RG, Krueger GG, Griffiths CE. Psoriasis: epidemiology, clinical features, and quality of life. Ann Rheum Dis. 2005;64(suppl 2):ii18-ii23. doi: 10.1136/ard.2004.033217 [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Husni ME, Merola JF, Davin S. The psychosocial burden of psoriatic arthritis. Semin Arthritis Rheum. 2017;47(3):351-360. doi: 10.1016/j.semarthrit.2017.05.010 [DOI] [PubMed] [Google Scholar]
9.Lande R, Botti E, Jandus C, et al. The antimicrobial peptide LL37 is a T-cell autoantigen in psoriasis. Nat Commun. 2014;5:5621. doi: 10.1038/ncomms6621 [DOI] [PubMed] [Google Scholar]
10.Pietrzak A, Chabros P, Grywalska E, et al. Serum lipid metabolism in psoriasis and psoriatic arthritis—an update. Arch Med Sci. 2019;15(2):369-375. doi: 10.5114/aoms.2018.74021 [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Yuan Y, Qiu J, Lin ZT, et al. Identification of novel autoantibodies associated with psoriatic arthritis. Arthritis Rheumatol. 2019;71(6):941-951. doi: 10.1002/art.40830 [DOI] [PubMed] [Google Scholar]
12.Attauabi M, Wewer MD, Bendtsen F, Seidelin JB, Burisch J. Inflammatory bowel diseases affect the phenotype and disease course of coexisting immune-mediated inflammatory diseases: a systematic review with meta-analysis. Inflamm Bowel Dis. 2022;izac003. doi: 10.1093/ibd/izac003 [DOI] [PubMed] [Google Scholar]
13.Ellinghaus D, Bethune J, Petersen BS, Franke A. The genetics of Crohn’s disease and ulcerative colitis—status quo and beyond. Scand J Gastroenterol. 2015;50(1):13-23. doi: 10.3109/00365521.2014.990507 [DOI] [PubMed] [Google Scholar]
14.Kaser A, Zeissig S, Blumberg RS. Inflammatory bowel disease. Annu Rev Immunol. 2010;28:573-621. doi: 10.1146/annurev-immunol-030409-101225 [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Collaborators GBDIBD; GBD 2017 Inflammatory Bowel Disease Collaborators . The global, regional, and national burden of inflammatory bowel disease in 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet Gastroenterol Hepatol. 2020;5(1):17-30. doi: 10.1016/S2468-1253(19)30333-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
16.Brand S. Crohn’s disease: Th1, Th17 or both? the change of a paradigm: new immunological and genetic insights implicate Th17 cells in the pathogenesis of Crohn’s disease. Gut. 2009;58(8):1152-1167. doi: 10.1136/gut.2008.163667 [DOI] [PubMed] [Google Scholar]
17.Ellinghaus D, Ellinghaus E, Nair RP, et al. Combined analysis of genome-wide association studies for Crohn disease and psoriasis identifies seven shared susceptibility loci. Am J Hum Genet. 2012;90(4):636-647. doi: 10.1016/j.ajhg.2012.02.020 [DOI] [PMC free article] [PubMed] [Google Scholar]
18.Furiati SC, Catarino JS, Silva MV, et al. Th1, Th17, and Treg responses are differently modulated by TNF-α inhibitors and methotrexate in psoriasis patients. Sci Rep. 2019;9(1):7526. doi: 10.1038/s41598-019-43899-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Egeberg A, Mallbris L, Warren RB, et al. Association between psoriasis and inflammatory bowel disease: a Danish nationwide cohort study. Br J Dermatol. 2016;175(3):487-492. doi: 10.1111/bjd.14528 [DOI] [PubMed] [Google Scholar]
20.Lee JY, Kang S, Bae JM, Jo SJ, Koh SJ, Park HS. Psoriasis increases the risk of concurrent inflammatory bowel disease: a population-based nationwide study in Korea. Indian J Dermatol Venereol Leprol. 2019;85(2):145-152. doi: 10.4103/ijdvl.IJDVL_875_17 [DOI] [PubMed] [Google Scholar]
21.Moon JM, Lee JY, Koh SJ, et al. Incidence of psoriasis in patients with inflammatory bowel disease: a nationwide population-based matched cohort study. Dermatology. 2021;237(3):330-337. doi: 10.1159/000514030 [DOI] [PubMed] [Google Scholar]
22.Fu Y, Lee CH, Chi CC. Association of psoriasis with inflammatory bowel disease: a systematic review and meta-analysis. JAMA Dermatol. 2018;154(12):1417-1423. doi: 10.1001/jamadermatol.2018.3631 [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Alinaghi F, Tekin HG, Burisch J, Wu JJ, Thyssen JP, Egeberg A. Global prevalence and bidirectional association between psoriasis and inflammatory bowel disease—a systematic review and meta-analysis. J Crohns Colitis. 2020;14(3):351-360. doi: 10.1093/ecco-jcc/jjz152 [DOI] [PubMed] [Google Scholar]
24.Davies NM, Holmes MV, Davey Smith G. Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians. BMJ. 2018;362:k601. doi: 10.1136/bmj.k601 [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Sanderson E, Glymour MM, Holmes MV, et al. Mendelian randomization. Nature Reviews Methods Primers. 2022;2(1):6. doi: 10.1038/s43586-021-00092-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
26.Liu JZ, van Sommeren S, Huang H, et al. ; International Multiple Sclerosis Genetics Consortium; International IBD Genetics Consortium . Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations. Nat Genet. 2015;47(9):979-986. doi: 10.1038/ng.3359 [DOI] [PMC free article] [PubMed] [Google Scholar]
27.Wu Y, Murray GK, Byrne EM, Sidorenko J, Visscher PM, Wray NR. GWAS of peptic ulcer disease implicates Helicobacter pylori infection, other gastrointestinal disorders and depression. Nat Commun. 2021;12(1):1146. doi: 10.1038/s41467-021-21280-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
28.FinnGen . Documentation of R6 release. Accessed March 18, 2022. https://finngen.gitbook.io/documentation/
29.Burgess S, Bowden J, Fall T, Ingelsson E, Thompson SG. Sensitivity analyses for robust causal inference from Mendelian randomization analyses with multiple genetic variants. Epidemiology. 2017;28(1):30-42. doi: 10.1097/EDE.0000000000000559 [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Zhao Q, Wang J, Hemani G, Bowden J, Small DS. Statistical inference in two-sample summary-data Mendelian randomization using robust adjusted profile score. Ann Stat. 2020;48(3):1742-1769. doi: 10.1214/19-AOS1866 [DOI] [Google Scholar]
31.Verbanck M, Chen CY, Neale B, Do R. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet. 2018;50(5):693-698. doi: 10.1038/s41588-018-0099-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Rees JMB, Wood AM, Dudbridge F, Burgess S. Robust methods in Mendelian randomization via penalization of heterogeneous causal estimates. PLoS One. 2019;14(9):e0222362. doi: 10.1371/journal.pone.0222362 [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Staley JR, Blackshaw J, Kamat MA, et al. PhenoScanner: a database of human genotype-phenotype associations. Bioinformatics. 2016;32(20):3207-3209. doi: 10.1093/bioinformatics/btw373 [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Kamat MA, Blackshaw JA, Young R, et al. PhenoScanner V2: an expanded tool for searching human genotype-phenotype associations. Bioinformatics. 2019;35(22):4851-4853. doi: 10.1093/bioinformatics/btz469 [DOI] [PMC free article] [PubMed] [Google Scholar]
35.O’Neill CA, Monteleone G, McLaughlin JT, Paus R. The gut-skin axis in health and disease: a paradigm with therapeutic implications. Bioessays. 2016;38(11):1167-1176. doi: 10.1002/bies.201600008 [DOI] [PubMed] [Google Scholar]
36.Maguire M, Maguire G. The role of microbiota, and probiotics and prebiotics in skin health. Arch Dermatol Res. 2017;309(6):411-421. doi: 10.1007/s00403-017-1750-3 [DOI] [PubMed] [Google Scholar]
37.Salem I, Ramser A, Isham N, Ghannoum MA. The gut microbiome as a major regulator of the gut-skin axis. Front Microbiol. 2018;9:1459. doi: 10.3389/fmicb.2018.01459 [DOI] [PMC free article] [PubMed] [Google Scholar]
38.Egeberg A, Thyssen JP, Burisch J, Colombel JF. Incidence and risk of inflammatory bowel disease in patients with psoriasis—a nationwide 20-year cohort study. J Invest Dermatol. 2019;139(2):316-323. doi: 10.1016/j.jid.2018.07.029 [DOI] [PubMed] [Google Scholar]
39.Cottone M, Sapienza C, Macaluso FS, Cannizzaro M. Psoriasis and inflammatory bowel disease. Dig Dis. 2019;37(6):451-457. doi: 10.1159/000500116 [DOI] [PubMed] [Google Scholar]
40.Manos J. The human microbiome in disease and pathology. APMIS. Published online April 8, 2022. doi: 10.1111/apm.13225 [DOI] [PMC free article] [PubMed] [Google Scholar]
41.Shah KR, Boland CR, Patel M, Thrash B, Menter A. Cutaneous manifestations of gastrointestinal disease: part I. J Am Acad Dermatol. 2013;68(2):189.e1-210. doi: 10.1016/j.jaad.2012.10.037 [DOI] [PubMed] [Google Scholar]
42.Thrash B, Patel M, Shah KR, Boland CR, Menter A. Cutaneous manifestations of gastrointestinal disease: part II. J Am Acad Dermatol. 2013;68(2):211.e1-33. doi: 10.1016/j.jaad.2012.10.036 [DOI] [PubMed] [Google Scholar]
43.Nestle FO, Conrad C, Tun-Kyi A, et al. Plasmacytoid predendritic cells initiate psoriasis through interferon-alpha production. J Exp Med. 2005;202(1):135-143. doi: 10.1084/jem.20050500 [DOI] [PMC free article] [PubMed] [Google Scholar]
44.Vojvodic A, Peric-Hajzler Z, Matovic D, et al. Gut microbiota and the alteration of immune balance in skin diseases: from nutraceuticals to fecal transplantation. Open Access Maced J Med Sci. 2019;7(18):3034-3038. doi: 10.3889/oamjms.2019.827 [DOI] [PMC free article] [PubMed] [Google Scholar]
45.Hong J, Mosca M, Hadeler E, Hakimi M, Bhutani T, Liao W. The future of personalized medicine in psoriasis. Dermatol Rev. 2021;2(5):282-288. doi: 10.1002/der2.87 [DOI] [Google Scholar]
46.Conic RR, Damiani G, Schrom KP, et al. Psoriasis and psoriatic arthritis cardiovascular disease endotypes identified by red blood cell distribution width and mean platelet volume. J Clin Med. 2020;9(1):186. doi: 10.3390/jcm9010186 [DOI] [PMC free article] [PubMed] [Google Scholar]
47.Davey Smith G, Holmes MV, Davies NM, Ebrahim S. Mendel’s laws, Mendelian randomization and causal inference in observational data: substantive and nomenclatural issues. Eur J Epidemiol. 2020;35(2):99-111. doi: 10.1007/s10654-020-00622-7 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials