Investigating modifiable pathways in psoriasis: A Mendelian randomization study

Evidence of a Causal Relationship Between Body Mass Index and Immune-Mediated and Inflammatory Skin Diseases and Biomarkers: A Mendelian Randomization Study

Aim

Increasing observational studies are revealing a positive correlation between body mass index (BMI) and the risk of Immune-mediated and Inflammatory Skin Diseases (IMID), however the causal relationship is not yet definite.

Objective

The aim of the study was to conduct a two-sample Mendelian randomization (TSMR) to explore the potential causality between BMI, and IMID and biomarkers.

Methods

The summary statistics for BMI (n = 322,154), at genome-wide significant level, were derived from the Genetic Investigation of Anthropometric Traits consortium (GIANT). The outcome data for IMID (Psoriasis, vitiligo, Atopic dermatitis (AD), acne, Bullous diseases, Dermatitis herpetiformis, Systemic lupus erythematosus (SLE), Alopecia Areata (AA), Hidradenitis suppurativa (HS) and Systemic sclerosis), and biomarkers were obtained from genome-wide association studies (GWAS). The TSMR analyses were performed in four methods, including inverse variance weighted (IVW) method, MR-Egger regression, the weighted median estimator (WME) and simple mode.

Results

The IVW analysis showed that the per standard deviation (SD) increase in BMI increased a 57% risk of psoriasis. We also observed the suggestive evidence of a causal relationship between BMI and AD and HS. This analysis did not support causality of Vitiligo, Acne, Bullous pemphigoid, Dermatitis herpetiformis, SLE, AA and Systemic sclerosis. The higher risk of BMI may be explained by higher levels of Triglycerides, C-reactive protein (CRP), Interleukin 6, Erythrocyte sedimentation rate (ESR) and Neutrophil count. The high-density lipoprotein (HDL) has an inverse relationship with BMI. No influences were defined for Total cholesterol, low-density lipoprotein (LDL), Rheumatoid factor (RF), Basophil count and Eosinophil count.

Conclusion

Our two-sample MR analysis proved the causal evidence for the associations between BMI and IMID, including psoriasis, AD and HS, which might be related to the elevated expression of biomarkers, including Triglycerides, CRP, Interleukin 6, ESR and neutrophil count.

A polygenic risk score model for psoriasis based on the protein interactions of psoriasis susceptibility loci

Introduction

Polygenic Risk Scores (PRS) are an emerging tool for predicting an individual's genetic risk to a complex trait. Several methods have been proposed to construct and calculate these scores. Here, we develop a biologically driven PRS using the UK BioBank cohort through validated protein interactions (PPI) and network construction for psoriasis, incorporating variants mapped to the interacting genes of 14 psoriasis susceptibility (PSORS) loci, as identified from previous genetic linkage studies.

Methods

We constructed the PPI network via the implementation of two major meta-databases of protein interactions, and identified variants mapped to the identified PSORS-interacting genes. We selected only European unrelated participants including individuals with psoriasis and randomly selected healthy controls using an at least 1:4 ratio to maximize statistical power. We next compared our PPI-PRS model to (i) clinical risk models and (ii) conventional PRS calculations through p-value thresholding.

Results

Our PPI-PRS model provides comparable results to both clinical risk models and conventional approaches, despite the incorporation of a limited number of variants which have not necessarily reached genome-wide significance (GWS). Exclusion of variants mapped to the HLA-C locus, an established risk locus for psoriasis resulted in highly similar associations compared to our primary model, indicating the contribution of the genetic variability mapped to non-GWS variants in PRS computations.

Discussion

Our findings support the implementation of biologically driven approaches in PRS calculations in psoriasis, highlighting their potential clinical utility in risk assessment and treatment management.

A large-scale retrospective study in China explores risk factors for disease severity in plaque psoriasis

Severe psoriasis has a long course and poor outcome, and it has long been a problem for patients. Understanding the independent risk factors that contribute to patients with severe psoriasis is critical for the development of effective treatment strategies. This large, multicenter study recruited 2,109 plaque psoriasis patients from 12 hospitals across China (October 31, 2019 - May 31, 2022). The logistic regression model underwent internal validation and external validation using two independent cohorts over future time periods (June 1, 2022 - January 31, 2023). The discriminative power of our model was substantiated by a C-index of 0.863 (95% CI: 0.848-0.879) in internal validation, further affirmed through 1,000 bootstrap validation (C-index: 0.860, 95% CI: 0.836-0.885) and external validation cohorts, where the C-index reached up to 0.910 (95% CI: 0.868-0.953) and 0.951 (95% CI: 0.924-0.977) in 2 external validation cohorts. To enhance accessibility for clinicians, the model has been made available as a dynamic nomogram and QR code. Our study identified 10 risk factors (the "DELPHI" consensus dichotomy, the DLQI index, the extent of skin involvement as measured by body surface area, the age of the patient at the time of clinical visit, sex, body weight in kilograms, career, the presence of scalp involvement, facial involvement, and arthropathy) for the overall severity of psoriasis (PASI ≥ 10). "Nomogram-10" provides clinicians with a practical tool to develop personalized intervention strategies based on an individual's risk profile.Trial registration: Chinese Clinical Trial Registry: ChiCTR1900024852.

Causal associations between psoriasis, eczema, urticaria, and mental illness: A bidirectional Mendelian randomization study of the European population

Observational studies have reported a relationship between multiple common dermatoses and mental illness. To assess the potential bidirectional causality between 3 skin disorders (psoriasis, eczema, and urticaria) and 4 psychiatric disorders (bipolar disorder, schizophrenia, major depressive disorder, and anxiety) in the European population, we used Mendelian randomization (MR) analysis, which provides definitive evidence for causal inference. Eligible single nucleotide polymorphisms were screened for dermatological and psychiatric disorders using a genome-wide association study database. We conducted bidirectional, 2-sample MR analysis using instrumental variables related to psoriasis, eczema, and urticaria as exposure factors, and bipolar disorder, schizophrenia, major depression, and anxiety as outcomes. Reverse MR analysis with bipolar disorder, schizophrenia, major depression, and anxiety as exposure and psoriasis, eczema, and urticaria as outcomes were also performed, and the causality was analyzed using inverse-variance weighting (IVW), MR-Egger, and weighted median methods. To thoroughly assess causality, sensitivity analyses were conducted using the IVW, MR-PRESSO, and MR-Egger methods. The results showed that bipolar disorder increased the incidence of psoriasis (odds ratio = 1.271, 95% confidence interval = 1.003-1.612, P = .047), heterogeneity test with Cochran Q test in the IVW showed P value > .05, (P = .302), the MR-Pleiotropy and MR-PRESSO (outlier methods) in the multiplicity test showed P value > .05, (P = .694; P = .441), and MR-Pleiotropy evidence showed no apparent intercept (intercept = -0.060; SE = 0.139; P = .694). Major depression increased the risk of eczema (odds ratio = 1.002, 95% confidence interval = 1.000-1.004, P = .024), heterogeneity test showed P value > .05, (P = .328), multiplicity detection showed P value > .05, (P = .572; P = .340), and MR-Pleiotropy evidence showed no apparent intercept (intercept = -0.099; SE = 0.162; P = .572). Sensitivity analyses of the above results were reliable, and no heterogeneity or multiplicity was found. This study demonstrated a statistically significant causality between bipolar disorder and psoriasis, major depression, and eczema in a European population, which could provide important information for physicians in the clinical management of common skin conditions.

Genomic correlation, shared loci, and causal relationship between insomnia and psoriasis: a large-scale genome-wide cross-trait analysis

Psoriasis and insomnia have co-morbidities, however, their common genetic basis is still unclear. We analyzed psoriasis and insomnia with summary statistics from genome-wide association studies. We first quantified overall genetic correlations, then ascertained multiple effector loci and expression-trait associations, and lastly, we analyzed the causal effects between psoriasis and insomnia. A prevalent genetic link between psoriasis and insomnia was found, four pleiotropic loci affecting psoriasis and insomnia were identified, and 154 genes were shared, indicating a genetic link between psoriasis and insomnia. Yet, there is no causal relationship between psoriasis and insomnia by two-sample Mendelian randomization. We discovered a genetic connection between insomnia and psoriasis driven by biological pleiotropy and unrelated to causation. Cross-trait analysis indicates a common genetic basis for psoriasis and insomnia. The results of this study highlight the importance of sleep management in the pathogenesis of psoriasis.

A genome-wide cross-trait analysis identifies shared loci and causal relationships of obesity and lipidemic traits with psoriasis

Background

Obesity and dyslipidemia, major global health concerns, have been linked to psoriasis, but previous studies faced methodological limitations and their shared genetic basis remains unclear. This study examines various obesity-related and lipidemic traits as potential contributors to psoriasis development, aiming to clarify their genetic associations and potential causal links.

Methods

Summary statistics from genome-wide association studies (GWAS) conducted for obesity-related traits (body mass index (BMI), waist-to-hip ratio (WHR), and waist-to-hip ratio adjusted for the body mass index (WHRadjBMI)) and lipidemic traits (high-density lipoprotein (HDL), LDL, triglyceride (TG), total Cholesterol (TC), apolipoprotein A1 (apoA1), apolipoprotein B (apoB), and apolipoprotein E (apoE)) and psoriasis, all in populations of European ancestry, were used. We quantified genetic correlations, identified shared loci and explored causal relationship across traits.

Results

We found positive genetic correlation between BMI and psoriasis (rg=0.22, p=2.44×10-18), and between WHR and psoriasis (rg=0.19, p=1.41×10-12). We further found the positive genetic correlation between psoriasis and WHRadjBMI(rg=0.07, p=1.81×10-2) the genetic correlation, in while the effect of BMI was controlled for. We identified 14 shared loci underlying psoriasis and obesity-related traits and 43 shared loci between psoriasis and lipidemic traits via cross-trait meta-analysis. Mendelian randomization (MR) supported the causal roles of BMI (IVW OR=1.483, 95%CI=1.333-1.649), WHR (IVW OR=1.393, 95%CI=1.207-1.608) and WHRadjBMI (IVW OR=1.18, 95%CI=1.047-1.329) in psoriasis, but not observe any significant association between lipidemic traits and the risk of psoriasis. Genetic predisposition to psoriasis did not appear to affect the risk of obesity and lipidemic traits.

Conclusions

An intrinsic link between obesity-related traits and psoriasis has been demonstrated. The genetic correlation and causal role of obesity-related traits in psoriasis highlight the significance of weight management in both the prevention and treatment of this condition.

Multiple long-term conditions in people with psoriasis: a latent class and bidirectional Mendelian randomization analysis

BACKGROUND

Coexisting long-term conditions (LTCs) in psoriasis and their potential causal associations with the disease are not well -established.

OBJECTIVES

To determine distinct clusters of LTCs in people with psoriasis and the potential bidirectional causal association between these LTCs and psoriasis.

METHODS

Using latent class analysis, cross-sectional data from people with psoriasis from the UK Biobank were analysed to identify distinct psoriasis-related comorbidity profiles. Linkage disequilibrium score regression (LDSR) was applied to compute the genetic correlation between psoriasis and LTCs. Two-sample bidirectional Mendelian randomization (MR) analysis assessed the potential causal direction using independent genetic variants that reached genome-wide significance (P < 5 × 10-8).

RESULTS

Five comorbidity clusters were identified in a population of 10 873 people with psoriasis. LDSR revealed that psoriasis was positively genetically correlated with heart failure [genetic correlation (rg) = 0.23, P = 8.8 × 10-8], depression (rg = 0.12, P = 2.7 × 10-5), coronary artery disease (CAD; rg = 0.15, P = 2 × 10-4) and type 2 diabetes (rg = 0.19, P = 3 × 10-3). Genetic liability to CAD was associated with an increased risk of psoriasis [inverse variance weighted (IVW) odds ratio (ORIVW) 1.159, 95% confidence interval (CI) 1.055-1.274; P = 2 × 10-3]. The MR pleiotropy residual sum and outlier (MR-PRESSO; ORMR-PRESSO 1.13, 95% CI 1.042-1.228; P = 6 × 10-3) and the MR-robust adjusted profile score (RAPS) (ORMR-RAPS 1.149, 95% CI 1.062-1.242; P = 5 × 10-4) approaches corroborate the IVW findings. The weighted median (WM) generated similar and consistent effect estimates but was not statistically significant (ORWM 1.076, 95% CI 0.949-1.221; P = 0.25). Evidence for a suggestive increased risk was detected for CAD (ORIVW 1.031, 95% CI 1.003-1.059; P = 0.03) and heart failure (ORIVW 1.019, 95% CI 1.005-1.033; P = 9 × 10-3) in those with a genetic liability to psoriasis; however, MR sensitivity analyses did not reach statistical significance.

CONCLUSIONS

Five distinct clusters of psoriasis comorbidities were observed with these findings to offer opportunities for an integrated approach to comorbidity prevention and treatment. Coexisting LTCs share with psoriasis common genetic and nongenetic risk factors, and aggressive lifestyle modification in these people is anticipated to have an impact beyond psoriasis risk. Genetically predicted CAD is possibly associated with an increased risk of psoriasis, altering our prior knowledge.

Disentangling the complexity of psoriasis in the post-genome-wide association era

In recent years, genome-wide association studies (GWAS) have been instrumental in unraveling the genetic architecture of complex diseases, including psoriasis. The application of large-scale GWA studies in psoriasis has illustrated several associated loci that participate in the cutaneous inflammation, however explaining a fraction of the disease heritability. With the advent of high-throughput sequencing technologies and functional genomics approaches, the post-GWAS era aims to unravel the functional mechanisms underlying the inter-individual variability in psoriasis patients. In this review, we present the key advances of psoriasis GWAS in under-represented populations, rare, non-coding and structural variants and epistatic phenomena that orchestrate the interplay between different cell types. We further review the gene-gene and gene-environment interactions contributing to the disease predisposition and development of comorbidities through Mendelian randomization studies and pleiotropic effects of psoriasis-associated loci. We finally examine the holistic approaches conducted in psoriasis through system genetics and state-of-the-art transcriptomic analyses, discussing their potential implication in the expanding field of precision medicine and characterization of comorbidities.