Abstract
Psoriasis is more common in patients with inflammatory bowel disease (IBD) than in the general population. Similarly, patients with psoriasis or psoriatic arthritis (PsA) have a higher incidence of IBD. However, whether this association is causal remains unknown. Therefore, we used a two-sample bidirectional Mendelian randomization (MR) analysis to identify this relationship. According to MR analysis, psoriasis and PsA causally increased the odds of developing Crohn’s disease (OR = 1.350 (1.066–1.709) P = 0.013; OR = 1.319 (1.166–1.492) P < 0.001). In contrast, MR estimates gave little support to a possible causal effect of psoriasis, PsA, on ulcerative colitis (OR = 1.101 (0.905–1.340) P = 0.335; OR = 1.007 (0.941–1.078) P = 0.831). Similarly, the reverse analysis suggested the Crohn’s disease causally increased the odds of psoriasis and PsA (OR = 1.425 (1.174–1.731) P < 0.001; OR = 1.448 (1.156–1.182) P = 0.001), whereas there are no causal association between ulcerative colitis and psoriasis, PsA (OR = 1.192 (0.921–1.542) P = 0.182; OR = 1.166 (0.818–1.664) P = 0.396). In summary, our MR analysis strengthens the evidence for the bidirectional dual causality between psoriasis (including PsA) and Crohn’s disease.
Subject terms: Inflammatory bowel disease, Skin diseases, Psoriasis
Introduction
As an inflammatory skin disorder, psoriasis is characterized by aberrant keratinocyte proliferation and immune cell infiltration into the epidermis1. Approximately 2.5% of Europeans, 0.05–3% of Africans, and 0.1–0.5% of Asians are affected2–5. Up to 30% of people with psoriasis eventually develop psoriatic arthritis (PsA), an inflammatory musculoskeletal condition6. PsA is one of the most severe comorbidities of psoriasis, which is characterized by joint pain, swelling and rigidity, and affects 0.4–1% of the UK population7,8. Psoriasis and PsA both have a significant genetic predisposition. Psoriasis has a heritability of 60–90%9,10, while PsA has a heritability of 80–100% based on twin and family research in European populations11. The disease prevalence is also on the rise12.
Inflammatory bowel disease (IBD), consisting of ulcerative colitis (UC) and Crohn’s disease (CD), is a chronic, recurrent immune-mediated disease of the gastrointestinal system13. The disease affects more than 2.5 million people in Europe, with rising prevalence in Asia and developing countries14. The association between IBD and psoriasis, PsA, has recently gained much attention. Specifically, several observational studies have investigated a strong relationship between psoriasis, PsA, and IBD, involving genetics, immunity, and gut dysbiosis15–17. Furthermore, a cohort study of US women found psoriasis with concomitant the psoriatic arthritis is associated with an increased risk of incident CD16.
In addition, according to a meta-analysis, psoriasis and IBD have been significantly linked in both directions, particularly in children and adolescents with IBD18. However, conclusions about causality cannot be drawn merely based on the presence of an association in an observational design, which was retrospective or cross-sectional in design with limited sample sizes and confounders. For example, patients with IBD treated with anti-TNF-α are susceptible to the side effects of paradoxical psoriasis, making medication a risk factor for psoriasis19. Therefore, it is difficult to determine whether PsA and IBD are causally related because this exaggerates the link between psoriasis and IBD.
Mendelian randomization (MR)20 has been proven to be a reliable method that can overcome observational studies’ limitations and assess causality. Traditional confounding factors are under control because the random allocation of alleles at conception ensures a balanced distribution of confounders across different genotypes. Furthermore, reverse causation is eliminated because a disease cannot alter a person’s genotype20.
In this study, we used the summary statistics from the public available genome-wide association studies (GWAS) data to conduct a bidirectional MR analysis to evaluate the potential causal relationship between psoriasis, PsA, and IBD.
Methods
We used data from published studies or GWAS summaries that were openly available. Since no primary data were used in this study, ethical approval was not required. However, each study’s academic ethics review committees approved all of them, and each participant signed a written informed consent form.
Selection of genetic variants and data sources
Genetic variants of psoriasis and PsA
Summary statistics for psoriasis and PsA were acquired from the MRC IEU OpenGWAS database (https://gwas.mrcieu.ac.uk/), which primarily consists of publicly available GWAS summary data and acts as an input source for many analytical methods, including Mendelian randomization21,22. All genetic variants reaching genome-wide significance (P < 5 × 10e−8) were selected as instruments for the MR analysis. The largest GWAS of psoriasis (N = 4510 cases, 212,242 controls) and PsA (N = 1637 cases, 212,242 controls) consisting of merely European individuals from the FinnGen biobank recovered some novel genetic variants. The corresponding linkage disequilibrium was tested to confirm any SNPs in linkage disequilibrium and whether the SNPs were independent by pruning SNPs within a 10,000 kb window with an r2 < 0.001 threshold. In addition, we examined the relationship between SNPs and potential confounders for the following traits: CD, UC, skin disorders, self-reported psoriasis, PsA, obesity, depression, disease duration, sex, race. SNPs with the abovementioned potential confounders were further eliminated.
Genetic variants of CD and UC
Summary statistics for CD and UC were acquired from the MRC IEU OpenGWAS database. We used a similar selection process to that described above to choose SNPs from the GWAS as the genetic instruments for CD and UC. As a result, several novel genetic variants were reclaimed from the largest GWAS of CD (N = 657 cases, 210,300 controls) and UC (N = 2251 cases, 210,300 controls) consisting of merely European individuals from the FinnGen biobank.
Finally, the F-statistic was calculated to assess the strength of the selected SNPs according to the following equation:
where R2 is the portion of exposure variance explained by the instrument variables (IVs), N is the sample size, and K is the number of IVs. F-statistic ≥ 10 suggests the non-existence of weak instrument bias23.
Mendelian randomization estimates
We conducted eight separate two-sample MR analyses, evaluating the association results, to examine the genetically bidirectional causal effect between psoriasis, PsA, CD, and UC. The three main assumptions of the two-sample MR analysis are as follows20,24 (Supplementary Fig. S1):
Genetic variants are strongly associated with exposure.
The variants must affect the outcome only by exposure.
The variants must be unaffected by any confounding factors related to the exposure or outcome25.
Many robust methods have been proposed since not all genetic variants are valid IVs. The methods that contain inverse variance weighting (IVW), inverse variance weighted (fixed effects), maximum likelihood, penalized weighted median, weighted median, MR-Egger, weighted mode, and simple mode were based on different assumptions for MR analysis. However, the IVW method of each Wald estimate is the primary method for acquiring an MR assessment26.
The IVW method uses a meta-analysis approach to combine Wald estimates for each SNP to get the overall effect estimates27. An unbiased causal estimate can be obtained by IVW linear regression if the second assumption (no horizontal pleiotropy) is not violated or if the horizontal pleiotropy is balanced22. Fixed- and random-effects IVW approaches are available. If significant heterogeneity (P < 0.05) is observed, a random-effect IVW model is applied. Similar to the fixed-effects IVW approach, the maximum likelihood method assumes that there is no heterogeneity or horizontal pleiotropy. The effect of the SNP on the exposure is plotted against the effect of the SNP on the outcome using the MR-Egger method, and if pleiotropy is absent, the plotted points fall along a line that goes through the origin. Values of the intercept terms that are different from zero indicate pleiotropy.
Pleiotropy-corrected causal estimates can be obtained from the MR-Egger regression’s slope. This approach assumes that the horizontal pleiotropic effects are not correlated with the SNP-exposure effects (InSIDE assumption)28. MR-Egger regression places no limitations on the average value of the pleiotropic effects. It only requires the Instrument Strength Independent of Direct Effect (InSIDE) assumption to estimate the causal effect unbiasedly. Under the InSIDE assumption, the pleiotropic effects are independent of the variant–exposure associations28. The weighted median method computes the median and ranks the MR estimates produced by each instrument separately according to the inverse of their variances29. According to this method, only half of the SNPs must be valid instruments (i.e., exhibiting no horizontal pleiotropy, no association with confounders, and robust association with the exposure). This method improves precision compared to the MR-Egger regression method29.
In addition, a penalized weighted median was calculated where outlying variants are penalized. Even when most instrumental variables in the weighted model do not comply with the conditions for MR causal inference, the weighted model still performs well30. The simple mode is a model-based estimation method that provides robustness for pleiotropy, although it is not as powerful as IVW31.
Sensitivity analysis
We used MR-Egger regression to assess potential pleiotropic effects that the SNPs used as IVs might have. The intercept term in MR-Egger regression can be a useful indication of whether directional horizontal pleiotropy is driving the results of an MR analysis32. MR-PRESSO is a method for detecting and correcting outliers in IVW linear regression. MR-PRESSO has three components: detection of horizontal pleiotropy (MR-PRESSO global test), correction for horizontal pleiotropy via outlier removal (MR-PRESSO outlier test), and testing of significant differences in the causal estimates before and after correction for outliers (MR-PRESSO distortion test). In brief, MR-PRESSO identifies horizontal pleiotropic outlier variants and provides an outlier-corrected estimate33. The heterogeneities was quantified by Cochran Q statistic; a P value of < 0.05 would be considered significant heterogeneity25. In addition, we conducted a “leave-one-out” sensitivity analysis, where the MR is left out individually to identify potentially significant SNP.
R version 4.0.5 with the two-sample MR and MR-PRESSO packages was used for all statistical analyses22,33. Statistical significance was defined as P value < 0.05.
Results
Selection of instrumental variables
The data on the LD-independent SNPs (after clumping) for exposures (psoriasis, PsA, CD, UC) are included in Supplementary Tables S1–S4. In the following cases, the listed SNPs will be removed: firstly, SNPs associated with outcomes and confounding factors will be excluded. Secondly, a specific SNP did not exist in the outcome GWAS, and a proxy in LD with the target SNP could not be retrieved from the outcome GWAS during extracting specific SNPs. Thirdly, it was impossible to reverse the impact of non-concordant alleles in ambiguous or palindromic SNPs with ambiguous strands. Finally, the F-statistics of IVs were all greater than 10, indicating little evidence of weak instrument bias (Supplementary Table S5).
The causal effect of psoriasis and PsA on CD and UC
Figure 1 shows the results of estimating the causal effect of psoriasis and PsA on CD and UC. It demonstrated that psoriasis was associated with a 35% increased risk of CD (IVW: OR 1.350 (1.066–1.709), P = 0.013). The association was consistent in the maximum likelihood, penalized weighted median, weighted median, and weighted mode methods. However, no causal effect of psoriasis on UC was found (IVW: OR 1.101 (0.905–1.340), P = 0.335). Since the MR assessment of PsA on CD and UC did not show any heterogeneity (Table 1), IVW with a fixed effect was identified as the main MR analysis. Primary MR analysis by the IVW (fixed effects) method showed that PsA was associated with the 31.9% increased risk of CD (IVW (fixed effects): OR 1.319 (1.166–1.492), P < 0.001). However, there was no causal genetic association between PsA and UC (IVW (fixed effects): OR 1.007 (0.941–1.078), P = 0.831). The estimated effect sizes of the SNPs on both exposure and result were displayed using scatter plots (Fig. 2). Supplementary Figs. S2 and S3 displays the “leave-one-out analysis” plots and funnel plots.
Figure 1.
Forest plot for MR analyses of the causal effect of psoriasis and PsA on CD and UC. CD Crohn’s disease, UC ulcerative colitis, PsA psoriatic arthritis, nSNP number of single nucleotide polymorphism.
Table 1.
Heterogeneity test and horizontal pleiotropy test.
| Exposure | Outcome | Heterogeneity test (IVW) | Heterogeneity test (MR-Egger) | Horizontal pleiotropy test | |||
|---|---|---|---|---|---|---|---|
| Q | P value | Q | P value | Q | P value | ||
| Psoriasis | CD | 40.023 | 0.000 | 39.815 | 0.000 | − 0.017 | 0.815 |
| Psoriasis | UC | 90.941 | 0.000 | 87.875 | 0.000 | 0.040 | 0.548 |
| Psoriasis arthritis | CD | 2.501 | 0.475 | 2.067 | 0.356 | − 0.101 | 0.583 |
| Psoriasis arthritis | UC | 2.264 | 0.453 | 2.192 | 0.334 | − 0.055 | 0.594 |
| CD | Psoriasis | 48.129 | 0.000 | 33.543 | 0.000 | 0.222 | 0.336 |
| CD | Psoriasis arthritis | 24.962 | 0.000 | 23.664 | 0.000 | 0.106 | 0.712 |
| UC | Psoriasis | 46.033 | 0.000 | 26.831 | 0.000 | − 0.134 | 0.166 |
| UC | Psoriasis arthritis | 33.782 | 0.000 | 26.096 | 0.000 | − 0.136 | 0.339 |
IVW inverse variance weighting, MR Mendelian randomization, CD Crohn's disease, UC ulcerative colitis.
Figure 2.
Scatter plots for MR analyses of the causal effect of psoriasis and PsA on CD and UC. (A) Scatter plots for MR analyses of the causal effect of psoriasis on CD; (B) scatter plots for MR analyses of the causal effect of psoriasis on UC; (C) scatter plots for MR analyses of the causal effect of PsA on CD; (D) scatter plots for MR analyses of the causal effect of PsA on UC. MR Mendelian randomization, CD Crohn’s disease, UC ulcerative colitis, PsA psoriatic arthritis, SNP single nucleotide polymorphism.
Estimates of the causal effect of CD and UC on psoriasis and PsA
Figure 3 displays MR estimates from eight different techniques for determining how CD and UC cause psoriasis and PsA. We found that genetically predicted CD was positively associated with the 42.5% increased risk of psoriasis (IVW: OR 1.425 (1.174–1.731), P < 0.001). The association was consistent in maximum likelihood, penalized weighted median, weighted median, simple mode, and weighted mode methods. In addition, the findings showed that CD was linked to a 44.8% higher risk of PsA (IVW: OR 1.448 (1.156–1.812), P = 0.001). The association was consistent in the maximum likelihood, penalized weighted median, weighted median, simple mode, and weighted mode methods. However, no causal effect of UC on psoriasis was found (IVW: OR 1.192 (0.921–1.542), P = 0.182). Similarly, there was no causal genetic association between UC and PsA (IVW: OR 1.166 (0.818–1.664), P = 0.396). Figure 4 and Supplementary Figs. S4 and S5 show the scatter plots, funnel plots, and “leave-one-out analysis” plots.
Figure 3.
Forest plot for MR analyses of the causal effect of CD and UC on psoriasis and PsA. CD Crohn’s disease, UC ulcerative colitis, PsA psoriatic arthritis, nSNP number of single nucleotide polymorphism.
Figure 4.
Scatter plots for MR analyses of the causal effect of CD and UC on psoriasis and PsA. (A) scatter plots for MR analyses of the causal effect of CD on psoriasis; (B) scatter plots for MR analyses of the causal effect of CD on PsA; (C) scatter plots for MR analyses of the causal effect of UC on psoriasis; (D) scatter plots for MR analyses of the causal effect of UC on PsA. MR Mendelian randomization, CD Crohn’s disease, UC ulcerative colitis, PsA psoriatic arthritis, SNP single nucleotide polymorphism.
Sensitivity analysis
In MR analyses, the heterogeneity test indicated the existence of heterogeneity except for assessing PsA on CD and UC (Table 1). In addition, none of the MR analyses’ MR-Egger intercept evidence for horizontal pleiotropy (Table 1). Notably, the raw estimates from MR-PRESSO showed no association between psoriasis and CD. However, after excluding two SNPs, the outlier-corrected estimates yielded the opposite conclusion, identical to the result of the IVW, maximum likelihood, penalized weighted median, weighted median, and weighted mode method. Results from IVW or IVW (fixed) methods were consistent with the raw and outlier-corrected estimates from MR-PRESSO in the remaining analysis, demonstrating the stability of the results (Table 2).
Table 2.
MR-PRESSO estimates between psoriasis, psoriatic arthritis and CD, UC.
| Exposure | Outcome | Raw estimates | Outlier corrected estimates | ||||||
|---|---|---|---|---|---|---|---|---|---|
| N | OR | 95%CI | P value | N | OR | 95%CI | P value | ||
| Psoriasis | CD | 13 | 1.188 | (0.972, 1.452) | 0.115 | 11 | 1.249 | (1.139, 1.369) | 0.000 |
| Psoriasis | UC | 13 | 1.054 | (0.913, 1.217) | 0.482 | 11 | 1.012 | (0.946, 1.082) | 0.738 |
| Psoriasis arthritis | CD | 4 | 1.319 | (1.179, 1.476) | 0.017 | NA | NA | NA | NA |
| Psoriasis arthritis | UC | 4 | 1.007 | (0.946, 1.073) | 0.834 | NA | NA | NA | NA |
| CD | Psoriasis | 5 | 1.425 | (1.174, 1.731) | 0.023 | 3 | 1.395 | (1.299, 1.498) | 0.012 |
| CD | Psoriasis arthritis | 5 | 1.448 | (1.156, 1.812) | 0.032 | 3 | 1.492 | (1.344, 1.656) | 0.017 |
| UC | Psoriasis | 6 | 1.192 | (0.921, 1.542) | 0.240 | 4 | 1.182 | (0.951, 1.469) | 0.230 |
| UC | Psoriasis arthritis | 6 | 1.166 | (0.818, 1.664) | 0.435 | 4 | 1.119 | (0.884, 1.416) | 0.420 |
MR Mendelian randomization, CD Crohn's disease, UC ulcerative colitis, N number, OR odds ratio, CI confidence interval.
Discussion
A bidirectional causal relationship was found between psoriasis, PsA, and CD, but not between psoriasis, PsA, and UC. Results showed that psoriasis and PsA were associated with 35% and 31.9% increased CD risk, respectively. Similarly, genetically predicted CD was positively associated with the increased risks of 42.5% and 44.8% of psoriasis and PsA, respectively. However, there were no correlations between UC and psoriasis or PsA.
According to our findings, there is a bidirectional causal relationship between psoriasis, PsA, and CD. These findings align with previous studies16,34,35 and could be explained by the fact that these conditions have similar pathogenesis. Firstly, they have common genetic risk loci. More than 4500 cases and 10,000 controls were investigated in GWAS, where 7 non-HLA susceptibility loci shared by CD and psoriasis (9p24 near JAK2, 10q22 at ZMIZ1, 11q13 near PRDX5, 16p13 near SOCS1, 19p13 near FUT2, 17q21 at STAT3, 22q11 at YDJC) were found. Four previously identified common risk loci (IL23R, IL12B, REL, and TYK2) were affirmed36. Chromosomal locus 6p21, the most widely researched genetic region, encompasses the major histocompatibility complex (MHC)-related genes37, which corresponds to PSORS1 in psoriasis and IBD3 in IBD38. Secondly, patients with CD and psoriasis frequently have gut dysbiosis39. A gut-skin-joint axis has been proposed by researchers to shed light on the relationships between variations in gut microbiota, increased bowel permeability, and disturbed immune balance, which may cause inflammation of the skin and joints40. Gut microbiota will affect epidermal divergence signaling pathways to change skin homeostasis41. In addition, some bacteria, like parabacteroides and coprobacillus, are less common due to CD and psoriasis42. Thirdly, immunological mechanisms that link psoriasis and CD may be dysbiosis, which dysbiosis possibly acting as a common pathogenic pathway that causes an augmented Th17-driven immune response in genetically susceptible hosts43. Furthermore, IL-23 could promote the proliferation and survival of Th17 cells while also inducing the release of corresponding cytokines, thus serving as a crucial cytokine regulator in autoimmune disorders44,45. Patients with PsA are more likely to have an autoimmune disorder than those with only cutaneous disease46, which could be attributed to the fact that patients with PsA have higher levels of systemic inflammation than those with psoriasis46,47. The negative results associated with UC were consistent with the findings of several previous studies16,34,35. However, various studies have demonstrated associations between psoriasis, PsA, and UC, while some report a higher risk of CD than UC17,48,49. Despite the clinical signs, genetic risk loci, and immune pathways shared by CD and UC, they have distinctive properties that may illustrate the discrepancy in their link with psoriasis and PsA.
Since our results seem to be interesting in the literature there are a few studies which present similar results. Yajia et al. have presented another MR analysis which confirms the bidirectional relationship between psoriasis, psoriatic arthritis, and CD50. However, findings of Dennis' study only support a unidirectional causal effect between CD and psoriasis as well as psoriatic arthritis51. There are some discrepancies between these reported estimates and our results. We believe that the difference may be caused by the different data source themselves. Notably these studies (including our results) all denied a causal association between UC and psoriasis (including PsA).
Since many studies were cross-sectional or retrospective, it was difficult to determine the timing of the diagnosis of psoriasis and PsA with IBD. Although subsequent cohort studies have emerged, they can still not circumvent the effects of confounding factors. Therefore, we applied the Mendelian randomization study to circumvent these shortcomings. The robustness and reliability of our results were also improved by using multiple statistical approaches based on different assumptions for two-sample MR analysis. In addition, the summary GWAS data we extracted for psoriasis, PsA, and IBD were all from subjects of European lineage, reducing potential bias. More importantly, we provide a basis for scientific exploration between psoriasis (including PsA) and IBD.
Our study also has some limitations. Firstly, since each method we applied in the analyses has its advantages and disadvantages, there is a risk of obtaining inconsistent results. Fortunately, the results of all methods we have applied are consistent in direction, with only a few statistically insignificant. Secondly, as with all MR studies, we could not address unobserved pleiotropy. Thirdly, as our data are drawn from publicly published databases, the number of IVs screened is still limited despite our selection of the largest publicly published GWAS. This requires us to track relevant databases and update our data in time. Fourthly, the study population only included individuals of European ancestry. More studies should be conducted to verify the applicability of these results to other ethnicities.
Conclusion
Our MR analysis strengthens the evidence for the bidirectional causal relationship between psoriasis (including PsA) and Crohn’s disease. Furthermore, the results suggest a compelling rationale for the clinician to detect the earlier potential development of these diseases.
Supplementary Information
Acknowledgements
The authors thank all investigators and participants from the FinnGen biobank for sharing the GWAS data for psoriasis, PsA, CD, and UC.
Abbreviations
- PsA
Psoriatic arthritis
- IBD
Inflammatory bowel disease
- UC
Ulcerative colitis
- CD
Crohn's disease
- MR
Mendelian randomization
- GWAS
Genome-wide association studies
- IV
Instrument variable
- IVW
Inverse variance weighting
- SNP
Single nucleotide polymorphism
Author contributions
Y.S. and JT.Z. wrote the main manuscript text and Y.L. prepared figures 1-4 and Tables 1-2. All authors reviewed the manuscript.
Data availability
All data used during the study were provided by a third party (GWAS summary data: https://gwas.mrcieu.ac.uk/). Direct requests for these materials may be made to the provider as indicated in the Acknowledgments.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
The online version contains supplementary material available at 10.1038/s41598-022-24872-5.
References
- 1.Greb JE, et al. Psoriasis. Nat. Rev. Dis. Prim. 2016;2:16082. doi: 10.1038/nrdp.2016.82. [DOI] [PubMed] [Google Scholar]
- 2.Chandran V, Raychaudhuri SP. Geoepidemiology and environmental factors of psoriasis and psoriatic arthritis. J. Autoimmun. 2010;34:J314–321. doi: 10.1016/j.jaut.2009.12.001. [DOI] [PubMed] [Google Scholar]
- 3.Ding X, et al. Prevalence of psoriasis in China: A population-based study in six cities. Eur. J. Dermatol. EJD. 2012;22:663–667. doi: 10.1684/ejd.2012.1802. [DOI] [PubMed] [Google Scholar]
- 4.Gelfand JM, et al. The prevalence of psoriasis in African Americans: Results from a population-based study. J. Am. Acad. Dermatol. 2005;52:23–26. doi: 10.1016/j.jaad.2004.07.045. [DOI] [PubMed] [Google Scholar]
- 5.Yin X, et al. Genome-wide meta-analysis identifies multiple novel associations and ethnic heterogeneity of psoriasis susceptibility. Nat. Commun. 2015;6:6916. doi: 10.1038/ncomms7916. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Stuart PE, et al. Genome-wide association analysis of psoriatic arthritis and cutaneous psoriasis reveals differences in their genetic architecture. Am. J. Hum. Genet. 2015;97:816–836. doi: 10.1016/j.ajhg.2015.10.019. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Lenman M, Abraham S. Diagnosis and management of psoriatic arthropathy in primary care. Br. J. Gen. Pract. J. R. Coll. Gen. Pract. 2014;64:424–425. doi: 10.3399/bjgp14X681181. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Parisi R, Symmons DP, Griffiths CE, Ashcroft DM. Global epidemiology of psoriasis: A systematic review of incidence and prevalence. J. Investig. Dermatol. 2013;133:377–385. doi: 10.1038/jid.2012.339. [DOI] [PubMed] [Google Scholar]
- 9.Brandrup F, Holm N, Grunnet N, Henningsen K, Hansen HE. Psoriasis in monozygotic twins: Variations in expression in individuals with identical genetic constitution. Acta Dermato-venereol. 1982;62:229–236. [PubMed] [Google Scholar]
- 10.Nestle FO, Kaplan DH, Barker J. Psoriasis. N. Engl. J. Med. 2009;361:496–509. doi: 10.1056/NEJMra0804595. [DOI] [PubMed] [Google Scholar]
- 11.Moll JM, Wright V. Familial occurrence of psoriatic arthritis. Ann. Rheum. Dis. 1973;32:181–201. doi: 10.1136/ard.32.3.181. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Springate DA, et al. Incidence, prevalence and mortality of patients with psoriasis: A U.K. population-based cohort study. Br. J. Dermatol. 2017;176:650–658. doi: 10.1111/bjd.15021. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Khor B, Gardet A, Xavier RJ. Genetics and pathogenesis of inflammatory bowel disease. Nature. 2011;474:307–317. doi: 10.1038/nature10209. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Molodecky NA, et al. Increasing incidence and prevalence of the inflammatory bowel diseases with time, based on systematic review. Gastroenterology. 2012;142:46–54. doi: 10.1053/j.gastro.2011.10.001. [DOI] [PubMed] [Google Scholar]
- 15.Hedin CRH, Sonkoly E, Eberhardson M, Ståhle M. Inflammatory bowel disease and psoriasis: Modernizing the multidisciplinary approach. J. Intern. Med. 2021;290:257–278. doi: 10.1111/joim.13282. [DOI] [PubMed] [Google Scholar]
- 16.Li WQ, Han JL, Chan AT, Qureshi AA. Psoriasis, psoriatic arthritis and increased risk of incident Crohn's disease in US women. Ann. Rheum. Dis. 2013;72:1200–1205. doi: 10.1136/annrheumdis-2012-202143. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Moon JM, et al. Incidence of psoriasis in patients with inflammatory bowel disease: A nationwide population-based matched cohort study. Dermatology (Basel, Switzerland) 2021;237:330–337. doi: 10.1159/000514030. [DOI] [PubMed] [Google Scholar]
- 18.Alinaghi F, et al. Global prevalence and bidirectional association between psoriasis and inflammatory bowel disease—A systematic review and meta-analysis. J. Crohn's Colitis. 2020;14:351–360. doi: 10.1093/ecco-jcc/jjz152. [DOI] [PubMed] [Google Scholar]
- 19.Pugliese D, et al. Paradoxical psoriasis in a large cohort of patients with inflammatory bowel disease receiving treatment with anti-TNF alpha: 5-year follow-up study. Aliment. Pharmacol. Ther. 2015;42:880–888. doi: 10.1111/apt.13352. [DOI] [PubMed] [Google Scholar]
- 20.Smith GD, Ebrahim S. 'Mendelian randomization': Can genetic epidemiology contribute to understanding environmental determinants of disease? Int. J. Epidemiol. 2003;32:1–22. doi: 10.1093/ije/dyg070. [DOI] [PubMed] [Google Scholar]
- 21.Elsworth, B. et al. The MRC IEU OpenGWAS data infrastructure. BioRxiv (2020).
- 22.Hemani G, et al. The MR-base platform supports systematic causal inference across the human phenome. Elife. 2018 doi: 10.7554/eLife.34408. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Pierce BL, Ahsan H, Vanderweele TJ. Power and instrument strength requirements for Mendelian randomization studies using multiple genetic variants. Int. J. Epidemiol. 2011;40:740–752. doi: 10.1093/ije/dyq151. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Lawlor DA, Harbord RM, Sterne JA, Timpson N, Davey Smith G. Mendelian randomization: Using genes as instruments for making causal inferences in epidemiology. Stat. Med. 2008;27:1133–1163. doi: 10.1002/sim.3034. [DOI] [PubMed] [Google Scholar]
- 25.Egger M, Smith GD, Phillips AN. Meta-analysis: Principles and procedures. BMJ (Clin. Res. Ed.) 1997;315:1533–1537. doi: 10.1136/bmj.315.7121.1533. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Yang J, et al. Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits. Nat. Genet. 2012;44(369–375):s361–363. doi: 10.1038/ng.2213. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Burgess S, Dudbridge F, Thompson SG. Combining information on multiple instrumental variables in Mendelian randomization: Comparison of allele score and summarized data methods. Stat. Med. 2016;35:1880–1906. doi: 10.1002/sim.6835. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: Effect estimation and bias detection through Egger regression. Int. J. Epidemiol. 2015;44:512–525. doi: 10.1093/ije/dyv080. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Bowden J, Davey Smith G, Haycock PC, Burgess S. Consistent estimation in Mendelian randomization with some invalid instruments using a weighted median estimator. Genet. Epidemiol. 2016;40:304–314. doi: 10.1002/gepi.21965. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Hartwig FP, Davey Smith G, Bowden J. Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption. Int. J. Epidemiol. 2017;46:1985–1998. doi: 10.1093/ije/dyx102. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Milne RL, et al. Identification of ten variants associated with risk of estrogen-receptor-negative breast cancer. Nat. Genet. 2017;49:1767–1778. doi: 10.1038/ng.3785. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Burgess S, Thompson SG. Interpreting findings from Mendelian randomization using the MR-Egger method. Eur. J. Epidemiol. 2017;32:377–389. doi: 10.1007/s10654-017-0255-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.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;50:693–698. doi: 10.1038/s41588-018-0099-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Charlton R, et al. Risk of uveitis and inflammatory bowel disease in people with psoriatic arthritis: A population-based cohort study. Ann. Rheum. Dis. 2018;77:277–280. doi: 10.1136/annrheumdis-2017-212328. [DOI] [PubMed] [Google Scholar]
- 35.Lee FI, Bellary SV, Francis C. Increased occurrence of psoriasis in patients with Crohn's disease and their relatives. Am. J. Gastroenterol. 1990;85:962–963. [PubMed] [Google Scholar]
- 36.Ellinghaus D, et al. Combined analysis of genome-wide association studies for Crohn disease and psoriasis identifies seven shared susceptibility loci. Am. J. Hum. Genet. 2012;90:636–647. doi: 10.1016/j.ajhg.2012.02.020. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Ahmad T, Marshall SE, Jewell D. Genetics of inflammatory bowel disease: The role of the HLA complex. World J. Gastroenterol. 2006;12:3628–3635. doi: 10.3748/wjg.v12.i23.3628. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Skroza N, et al. Correlations between psoriasis and inflammatory bowel diseases. BioMed Res. Int. 2013;2013:983902. doi: 10.1155/2013/983902. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Polak K, et al. Psoriasis and gut microbiome-current state of art. Int. J. Mol. Sci. 2021;22:4529. doi: 10.3390/ijms22094529. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Myers B, et al. The gut microbiome in psoriasis and psoriatic arthritis. Best Pract. Res. Clin. Rheumatol. 2019;33:101494. doi: 10.1016/j.berh.2020.101494. [DOI] [PubMed] [Google Scholar]
- 41.O'Neill CA, Monteleone G, McLaughlin JT, Paus R. The gut-skin axis in health and disease: A paradigm with therapeutic implications. BioEssays News Rev. Mol. Cell. Dev. Biol. 2016;38:1167–1176. doi: 10.1002/bies.201600008. [DOI] [PubMed] [Google Scholar]
- 42.Scher JU, et al. Decreased bacterial diversity characterizes the altered gut microbiota in patients with psoriatic arthritis, resembling dysbiosis in inflammatory bowel disease. Arthritis Rheumatol. (Hoboken, N.J.) 2015;67:128–139. doi: 10.1002/art.38892. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Eppinga H, Konstantinov SR, Peppelenbosch MP, Thio HB. The microbiome and psoriatic arthritis. Curr. Rheumatol. Rep. 2014;16:407. doi: 10.1007/s11926-013-0407-2. [DOI] [PubMed] [Google Scholar]
- 44.Blauvelt A. T-helper 17 cells in psoriatic plaques and additional genetic links between IL-23 and psoriasis. J. Investig. Dermatol. 2008;128:1064–1067. doi: 10.1038/jid.2008.85. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Kobayashi T, et al. IL23 differentially regulates the Th1/Th17 balance in ulcerative colitis and Crohn's disease. Gut. 2008;57:1682–1689. doi: 10.1136/gut.2007.135053. [DOI] [PubMed] [Google Scholar]
- 46.Wu JJ, Nguyen TU, Poon KY, Herrinton LJ. The association of psoriasis with autoimmune diseases. J. Am. Acad. Dermatol. 2012;67:924–930. doi: 10.1016/j.jaad.2012.04.039. [DOI] [PubMed] [Google Scholar]
- 47.Chandran V, et al. Soluble biomarkers differentiate patients with psoriatic arthritis from those with psoriasis without arthritis. Rheumatology (Oxford) 2010;49:1399–1405. doi: 10.1093/rheumatology/keq105. [DOI] [PubMed] [Google Scholar]
- 48.Cohen AD, Dreiher J, Birkenfeld S. Psoriasis associated with ulcerative colitis and Crohn's disease. J. Eur. Acad. Dermatol. Venereol. JEADV. 2009;23:561–565. doi: 10.1111/j.1468-3083.2008.03031.x. [DOI] [PubMed] [Google Scholar]
- 49.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. Investig. Dermatol. 2019;139:316–323. doi: 10.1016/j.jid.2018.07.029. [DOI] [PubMed] [Google Scholar]
- 50.Li Y, Guo J, Cao Z, Wu J. Causal association between inflammatory bowel disease and psoriasis: A two-sample bidirectional Mendelian randomization study. Front. Immunol. 2022;13:916645. doi: 10.3389/fimmu.2022.916645. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Freuer D, Linseisen J, Meisinger C. Association between inflammatory bowel disease and both psoriasis and psoriatic arthritis: A bidirectional 2-sample Mendelian randomization study. JAMA Dermatol. 2022 doi: 10.1001/jamadermatol.2022.3682. [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
Data Availability Statement
All data used during the study were provided by a third party (GWAS summary data: https://gwas.mrcieu.ac.uk/). Direct requests for these materials may be made to the provider as indicated in the Acknowledgments.




