Defining disease severity in atopic dermatitis and psoriasis for the application to biomarker research- an inter-disciplinary perspective.

More severe atopic dermatitis (AD) and psoriasis are associated with a higher cumulative impact on quality of life, multimorbidity and healthcare costs. Proactive, early intervention in those most at risk of severe disease may reduce this cumulative burden and modify the disease trajectory to limit progression. The lack of reliable biomarkers for this at-risk group represents a barrier to such a paradigm shift in practice. To expedite discovery and validation, the BIOMAP consortium (Biomarkers in AD and Psoriasis, a large-scale European, inter-disciplinary research initiative) has curated clinical and molecular data across diverse study designs and sources including cross-sectional and cohort studies (small scale through to large multi-centre registries), clinical trials, electronic health records and large-scale population-based biobanks. We map all dataset disease severity instruments and measures to three key domains (symptoms, inflammatory activity and disease course), and describe important co-dependencies and relationships across variables and domains. We prioritise definitions for more severe disease with reference to international consensus, reference standards and/or expert opinion. Key factors to consider when analysing datasets across these diverse study types include explicit early consideration of biomarker purpose and clinical context, candidate biomarkers associated with disease severity at a point in time and over time and how they are related, taking the stage of biomarker development into account when selecting disease severity measures for analyses and, validating biomarker associations with disease severity outcomes using both physician- and patient-reported measures and across domains. The outputs from this exercise will ensure coherence and focus across the BIOMAP consortium so that mechanistic insights and biomarkers are clinically relevant, patient-centric and more generalisable to current and future research efforts.

Genome-wide meta-analysis implicates variation affecting mast cell biology in urticaria.

BACKGROUND: Urticaria is characterized by inappropriate mast cell degranulation leading to the development of wheals and/or angioedema. Twin and family studies indicate that there is a substantial heritable component to urticaria risk. OBJECTIVE: Our aim was to identify genomic loci at which common genetic variation influences urticaria susceptibility. METHODS: Genome-wide association studies of urticaria (including all subtypes) from 3 European cohorts (UK Biobank, FinnGen, and the Trøndelag Health Study [HUNT]) were combined through statistical meta-analysis (14,306 urticaria cases and 650,664 controls). Cases were identified via electronic health care records from primary and/or secondary care. To identify putative causal variants and genes, statistical fine-mapping, colocalization, and interrogation of publicly available single-cell transcriptome sequencing resources were performed. RESULTS: Genome-wide significant associations (P < 5 × 10-8) were identified at 6 independent loci. These included 2 previously reported association signals at 1q44 and the human leucocyte antigen region on chromosome 6. Genes with expected or established roles in mast cell biology were associated with the 4 other genome-wide association signals (GCSAML, FCER1A, TPSAB1, and CBLB). Colocalization of association signals consistent with the presence of shared causal variants was observed between urticaria susceptibility and increased expression of GCSAML (posterior probability of colocalization [PPcoloc] = 0.89) and FCER1A (PPcoloc = 0.91) in skin. CONCLUSION: Common genetic variation influencing the risk of developing urticaria was identified at 6 genomic loci. The relationship between genes with roles in mast cell biology and several association signals implicates genetic variability of specific components of mast cell function in the development of urticaria.

The association of age at psoriasis onset and HLA-C*06:02 with biologic survival in patients with moderate-to-severe psoriasis: a cohort study from the British Association of Dermatologists Biologics and Immunomodulators Register (BADBIR).

BACKGROUND: Few studies have used real-world data to investigate the association between biologic therapy survival and age at psoriasis onset or HLA-C*06:02 status in patients with moderate-to-severe psoriasis. The robustness of these studies is limited by small sample size, short follow-up and diverse safety and effectiveness measures. OBJECTIVES: To describe biologic survival and explore whether the response to biologics is modified by age at psoriasis onset or HLA-C*06:02 status in patients with moderate-to-severe psoriasis. METHODS: Data from patients in the UK and the Republic of Ireland registering to the British Association of Dermatologists Biologics and Immunomodulators Register (BADBIR) from 2007-2022 on first course of adalimumab, etanercept, secukinumab or ustekinumab with at least 6 months' follow-up and a subset of BADBIR patients with available HLA-C*06:02 information registered to Biomarkers and Stratification To Optimise outcomes in Psoriasis (BSTOP) were analysed. Patients aged ≥50 years at treatment initiation were classified into early onset psoriasis (EOP; presenting ≤40 years of age) and late onset (LOP; presenting > 40 years of age); BADBIR patients with available information in BSTOP were categorised into HLA-C*06:02-ve and HLA-C*06:02+ve. Biologic survival was defined as treatment discontinuation associated with ineffectiveness or occurrence of adverse events (AEs). Adjusted survival function and hazard ratio (aHR) with 95% confidence interval (CI) were estimated using a flexible parametric model to compare discontinuing therapy between age at psoriasis onset and HLA-C*06:02 groups. Each model included exposure (biologics), effect modifier (age at onset or HLA-C*06:02 status), interaction terms and several baseline demographic, clinical and disease severity covariates. RESULTS: Final analytical cohorts included 4250 patients (2929 [69%] EOP vs. 1321 [31%] LOP) and 3094 patients (1603 [52%] HLA-C*06:02+ve vs. 1491 [48%] HLA-C*06:02-ve). There was no significant difference between EOP and LOP in drug survival associated with ineffectiveness or AEs for any biologics. However, HLA-C*06:02+ve compared with HLA-C*06:02-ve patients were less likely to discontinue ustekinumab associated with ineffectiveness 0.56 [0.42, 0.75]. CONCLUSIONS: HLA-C*06:02 but not age at psoriasis onset is a predictive biomarker for biologic survival in psoriasis patients. Findings from this large cohort provide further, important information to aid clinicians using biologic therapies to manage psoriasis patients.

GWAS meta-analysis of psoriasis identifies new susceptibility alleles impacting disease mechanisms and therapeutic targets.

Psoriasis is a common, debilitating immune-mediated skin disease. Genetic studies have identified biological mechanisms of psoriasis risk, including those targeted by effective therapies. However, the genetic liability to psoriasis is not fully explained by variation at robustly identified risk loci. To move towards a saturation map of psoriasis susceptibility we meta-analysed 18 GWAS comprising 36,466 cases and 458,078 controls and identified 109 distinct psoriasis susceptibility loci, including 45 that have not been previously reported. These include susceptibility variants at loci in which the therapeutic targets IL17RA and AHR are encoded, and deleterious coding variants supporting potential new drug targets (including in STAP2, CPVL and POU2F3). We conducted a transcriptome-wide association study to identify regulatory effects of psoriasis susceptibility variants and cross-referenced these against single cell expression profiles in psoriasis-affected skin, highlighting roles for the transcriptional regulation of haematopoietic cell development and epigenetic modulation of interferon signalling in psoriasis pathobiology.

Atopic Polygenic Risk Score Is Associated with Paradoxical Eczema Developing in Patients with Psoriasis Treated with Biologics.

Biologic therapies for psoriasis can cause paradoxical eczema. The role of genetic factors in its pathogenesis is unknown. To identify risk variants, we conducted a GWAS of 3,212 patients with psoriasis, of whom 88 developed paradoxical eczema. Two lead SNPs reached genome-wide significance (P ≤ 5 × 10-8) for association with paradoxical eczema: rs192705221 (near UNC5B, P = 9.52 × 10-10) and rs72925168 (within SLC1A2, P = 1.66 × 10-9). Genome-wide significant SNPs from published GWAS were used to generate polygenic risk scores (PRSs) for atopic eczema, general atopic disease, or a combination, which were tested for association with paradoxical eczema. Improvement over a clinical risk model was assessed by the area under the curve. All three atopy polygenic risk scores were associated with paradoxical eczema (P < 0.05); polygenic risk score for a combination of atopic eczema and general atopic disease had the strongest association (OR = 1.83, 95% CI = 1.17-2.84, P = 0.0078). Including atopic polygenic risk scores in the multivariable model, which included age, sex, atopic background, and psoriatic arthritis history, increased the area under the curve from 0.671 to 0.681-0.686. Atopic genetic burden is associated with paradoxical eczema occurring in biologic-treated patients with psoriasis, indicating shared underlying mechanisms. Incorporating genetic risk may improve treatment outcome prediction models for psoriasis.

Characteristics associated with poor COVID-19 outcomes in people with psoriasis, psoriatic arthritis and axial spondyloarthritis: data from the COVID-19 PsoProtect and Global Rheumatology Alliance physician-reported registries.

OBJECTIVES: To investigate factors associated with severe COVID-19 in people with psoriasis (PsO), psoriatic arthritis (PsA) and axial spondyloarthritis (axSpA). METHODS: Demographic data, clinical characteristics and COVID-19 outcome severity of adults with PsO, PsA and axSpA were obtained from two international physician-reported registries. A three-point ordinal COVID-19 severity scale was defined: no hospitalisation, hospitalisation (and no death) and death. ORs were estimated using multivariable ordinal logistic regression. RESULTS: Of 5045 cases, 18.3% had PsO, 45.5% PsA and 36.3% axSpA. Most (83.6%) were not hospitalised, 14.6% were hospitalised and 1.8% died. Older age was non-linearly associated with COVID-19 severity. Male sex (OR 1.54, 95% CI 1.30 to 1.83), cardiovascular, respiratory, renal, metabolic and cancer comorbidities (ORs 1.25-2.89), moderate/high disease activity and/or glucocorticoid use (ORs 1.39-2.23, vs remission/low disease activity and no glucocorticoids) were associated with increased odds of severe COVID-19. Later pandemic time periods (ORs 0.42-0.52, vs until 15 June 2020), PsO (OR 0.49, 95% CI 0.37 to 0.65, vs PsA) and baseline exposure to TNFi, IL17i and IL-23i/IL-12+23i (OR 0.57, 95% CI 0.44 to 0.73; OR 0.62, 95% CI 0.45 to 0.87; OR 0.67, 95% CI 0.45 to 0.98; respectively; vs no disease-modifying antirheumatic drug) were associated with reduced odds of severe COVID-19. CONCLUSION: Older age, male sex, comorbidity burden, higher disease activity and glucocorticoid intake were associated with more severe COVID-19. Later pandemic time periods, PsO and exposure to TNFi, IL17i and IL-23i/IL-12+23i were associated with less severe COVID-19. These findings will enable risk stratification and inform management decisions for patients with PsO, PsA and axSpA during COVID-19 waves or similar future respiratory pandemics.

Development of antidrug antibodies against adalimumab maps to variation within the HLA-DR peptide-binding groove.

Targeted biologic therapies can elicit an undesirable host immune response characterized by the development of antidrug antibodies (ADA), an important cause of treatment failure. The most widely used biologic across immune-mediated diseases is adalimumab, a tumor necrosis factor inhibitor. This study aimed to identify genetic variants that contribute to the development of ADA against adalimumab, thereby influencing treatment failure. In patients with psoriasis on their first course of adalimumab, in whom serum ADA had been evaluated 6-36 months after starting treatment, we observed a genome-wide association with ADA against adalimumab within the major histocompatibility complex (MHC). The association signal mapped to the presence of tryptophan at position 9 and lysine at position 71 of the HLA-DR peptide-binding groove, with both residues conferring protection against ADA. Underscoring their clinical relevance, these residues were also protective against treatment failure. Our findings highlight antigenic peptide presentation via MHC class II as a critical mechanism in the development of ADA against biologic therapies and downstream treatment response.

Nonadherence to systemic immune-modifying therapy in people with psoriasis during the COVID-19 pandemic: findings from a global cross-sectional survey.

BACKGROUND: Nonadherence to immune-modifying therapy is a complex behaviour which, before the COVID-19 pandemic, was shown to be associated with mental health disorders in people with immune-mediated diseases. The COVID-19 pandemic has led to a rise in the global prevalence of anxiety and depression, and limited data exist on the association between mental health and nonadherence to immune-modifying therapy during the pandemic. OBJECTIVES: To assess the extent of and reasons underlying nonadherence to systemic immune-modifying therapy during the COVID-19 pandemic in individuals with psoriasis, and the association between mental health and nonadherence. METHODS: Online self-report surveys (PsoProtectMe), including validated screens for anxiety and depression, were completed globally during the first year of the pandemic. We assessed the association between anxiety or depression and nonadherence to systemic immune-modifying therapy using binomial logistic regression, adjusting for potential cofounders (age, sex, ethnicity, comorbidity) and country of residence. RESULTS: Of 3980 participants from 77 countries, 1611 (40.5%) were prescribed a systemic immune-modifying therapy. Of these, 408 (25.3%) reported nonadherence during the pandemic, most commonly due to concerns about their immunity. In the unadjusted model, a positive anxiety screen was associated with nonadherence to systemic immune-modifying therapy [odds ratio (OR) 1.37, 95% confidence interval (CI) 1.07-1.76]. Specifically, anxiety was associated with nonadherence to targeted therapy (OR 1.41, 95% CI 1.01-1.96) but not standard systemic therapy (OR 1.16, 95% CI 0.81-1.67). In the adjusted model, although the directions of the effects remained, anxiety was not significantly associated with nonadherence to overall systemic (OR 1.20, 95% CI 0.92-1.56) or targeted (OR 1.33, 95% CI 0.94-1.89) immune-modifying therapy. A positive depression screen was not strongly associated with nonadherence to systemic immune-modifying therapy in the unadjusted (OR 1.22, 95% CI 0.94-1.57) or adjusted models (OR 1.14, 95% CI 0.87-1.49). CONCLUSIONS: These data indicate substantial nonadherence to immune-modifying therapy in people with psoriasis during the pandemic, with attenuation of the association with mental health after adjusting for confounders. Future research in larger populations should further explore pandemic-specific drivers of treatment nonadherence. Clear communication of the reassuring findings from population-based research regarding immune-modifying therapy-associated adverse COVID-19 risks to people with psoriasis is essential, to optimize adherence and disease outcomes.

Comorbidities of Keloid and Hypertrophic Scars Among Participants in UK Biobank.

Importance: Keloids and hypertrophic scars (excessive scarring) are relatively understudied disfiguring chronic skin conditions with high treatment resistance. Objective: To evaluate established comorbidities of excessive scarring in European individuals, with comparisons across ethnic groups, and to identify novel comorbidities via a phenome-wide association study (PheWAS). Design, Setting, and Participants: This multicenter cross-sectional population-based cohort study used UK Biobank (UKB) data and fitted logistic regression models for testing associations between excessive scarring and a variety of outcomes, including previously studied comorbidities and 1518 systematically defined disease categories. Additional modeling was performed within subgroups of participants defined by self-reported ethnicity (as defined in UK Biobank). Of 502 701 UKB participants, analyses were restricted to 230078 individuals with linked primary care records. Exposures: Keloid or hypertrophic scar diagnoses. Main Outcomes and Measures: Previously studied disease associations (hypertension, uterine leiomyoma, vitamin D deficiency, atopic eczema) and phenotypes defined in the PheWAS Catalog. Results: Of the 972 people with excessive scarring, there was a higher proportion of female participants compared with the 229 106 controls (65% vs 55%) and a lower proportion of White ethnicity (86% vs 95%); mean (SD) age of the total cohort was 64 (8) years. Associations were identified with hypertension and atopic eczema in models accounting for age, sex, and ethnicity, and the association with atopic eczema (odds ratio [OR], 1.68; 95% CI, 1.36-2.07; P < .001) remained statistically significant after accounting for additional potential confounders. Fully adjusted analyses within ethnic groups revealed associations with hypertension in Black participants (OR, 2.05; 95% CI, 1.13-3.72; P = .02) and with vitamin D deficiency in Asian participants (OR, 2.24; 95% CI, 1.26-3.97; P = .006). The association with uterine leiomyoma was borderline significant in Black women (OR, 1.93; 95% CI, 1.00-3.71; P = .05), whereas the association with atopic eczema was significant in White participants (OR, 1.68; 95% CI, 1.34-2.12; P < .001) and showed a similar trend in Asian (OR, 2.17; 95% CI, 1.01-4.67; P = .048) and Black participants (OR, 1.89; 95% CI, 0.83-4.28; P = .13). The PheWAS identified 110 significant associations across disease systems; of the nondermatological, musculoskeletal disease and pain symptoms were prominent. Conclusions and Relevance: This cross-sectional study validated comorbidities of excessive scarring in UKB with comprehensive coverage of health outcomes. It also documented additional phenome-wide associations that will serve as a reference for future studies to investigate common underlying pathophysiologic mechanisms.

Comparative Genetic Analysis of Psoriatic Arthritis and Psoriasis for the Discovery of Genetic Risk Factors and Risk Prediction Modeling.

OBJECTIVES: Psoriatic arthritis (PsA) has a strong genetic component, and the identification of genetic risk factors could help identify the ~30% of psoriasis patients at high risk of developing PsA. Our objectives were to identify genetic risk factors and pathways that differentiate PsA from cutaneous-only psoriasis (PsC) and to evaluate the performance of PsA risk prediction models. METHODS: Genome-wide meta-analyses were conducted separately for 5,065 patients with PsA and 21,286 healthy controls and separately for 4,340 patients with PsA and 6,431 patients with PsC. The heritability of PsA was calculated as a single-nucleotide polymorphism (SNP)-based heritability estimate (h2 SNP ) and biologic pathways that differentiate PsA from PsC were identified using Priority Index software. The generalizability of previously published PsA risk prediction pipelines was explored, and a risk prediction model was developed with external validation. RESULTS: We identified a novel genome-wide significant susceptibility locus for the development of PsA on chromosome 22q11 (rs5754467; P = 1.61 × 10-9 ), and key pathways that differentiate PsA from PsC, including NF-κB signaling (adjusted P = 1.4 × 10-45 ) and Wnt signaling (adjusted P = 9.5 × 10-58 ). The heritability of PsA in this cohort was found to be moderate (h2 SNP = 0.63), which was similar to the heritability of PsC (h2 SNP = 0.61). We observed modest performance of published classification pipelines (maximum area under the curve 0.61), with similar performance of a risk model derived using the current data. CONCLUSION: Key biologic pathways associated with the development of PsA were identified, but the investigation of risk classification revealed modest utility in the available data sets, possibly because many of the PsC patients included in the present study were receiving treatments that are also effective in PsA. Future predictive models of PsA should be tested in PsC patients recruited from primary care.

Biomarkers of systemic treatment response in people with psoriasis: a scoping review.

BACKGROUND: Responses to the systemic treatments commonly used to treat psoriasis vary. Biomarkers that accurately predict effectiveness and safety would enable targeted treatment selection, improved patient outcomes and more cost-effective healthcare. OBJECTIVES: To perform a scoping review to identify and catalogue candidate biomarkers of systemic treatment response in psoriasis for the translational research community. METHODS: A systematic search of CENTRAL, Embase, LILACS and MEDLINE was performed for relevant articles published between 1990 and December 2021. Eligibility criteria were studies involving patients with psoriasis (any age, n ≥ 50) reporting biomarkers associated with systemic treatment response. The main outcomes were any measure of systemic treatment efficacy or safety. Data were extracted by one reviewer and checked by a second; studies meeting minimal quality criteria (use of methods to control for confounding) were formally assessed for bias. Candidate biomarkers were identified by an expert multistakeholder group using a majority voting consensus exercise and mapped to relevant cellular and molecular pathways. RESULTS: Of 71 included studies (67 studying effectiveness outcomes and eight safety outcomes; four studied both), most reported genomic or proteomic biomarkers associated with response to biologics (48 studies). Methodological or reporting limitations frequently compromised the interpretation of findings, including inadequate control for key covariates, lack of adjustment for multiple testing, and selective outcome reporting. We identified candidate biomarkers of efficacy to tumour necrosis factor inhibitors [variation in CARD14, CDKAL1, IL1B, IL12B and IL17RA loci, and lipopolysaccharide-induced phosphorylation of nuclear factor (NF)-κB in type 2 dendritic cells] and ustekinumab (HLA-C*06:02 and variation in an IL1B locus). None were supported by sufficient evidence for clinical use without further validation studies. Candidate biomarkers were found to be involved in the immune cellular crosstalk implicated in psoriasis pathogenesis, most notably antigen presentation, T helper (Th)17 cell differentiation, positive regulation of NF-κB, and Th17 cell activation. CONCLUSIONS: This comprehensive catalogue provides a key resource for researchers and reveals a diverse range of biomarker types and outcomes in the included studies. The candidate biomarkers identified require further evaluation in methodologically robust studies to establish potential clinical utility. Future studies should aim to address the common methodological limitations highlighted in this review to expedite discovery and validation of biomarkers for clinical use. What is already known about this topic? Responses to the systemic treatments commonly used to treat psoriasis vary. Biomarkers that accurately predict effectiveness and safety would enable targeted treatment selection, improved patient outcomes and more cost-effective healthcare. What does this study add? This review provides a comprehensive catalogue of investigated biomarkers of systemic treatment response in psoriasis. A diverse range of biomarker types and outcomes was found in the included studies, serving as a key resource for the translational research community.

Biomarkers of disease progression in people with psoriasis: a scoping review.

BACKGROUND: Identification of those at risk of more severe psoriasis and/or associated morbidities offers opportunity for early intervention, reduced disease burden and more cost-effective healthcare. Prognostic biomarkers of disease progression have thus been the focus of intense research, but none are part of routine practice. OBJECTIVES: To identify and catalogue candidate biomarkers of disease progression in psoriasis for the translational research community. METHODS: A systematic search of CENTRAL, Embase, LILACS and MEDLINE was performed for relevant articles published between 1990 and December 2021. Eligibility criteria were studies involving patients with psoriasis (any age, n ≥ 50) reporting biomarkers associated with disease progression. The main outcomes were any measure of skin severity or any prespecified psoriasis comorbidity. Data were extracted by one reviewer and checked by a second; studies meeting minimal quality criteria (longitudinal design and/or use of methods to control for confounding) were formally assessed for bias. Candidate biomarkers were identified by an expert multistakeholder group using a majority voting consensus exercise, and mapped to relevant cellular and molecular pathways. RESULTS: Of 181 included studies, most investigated genomic or proteomic biomarkers associated with disease severity (n = 145) or psoriatic arthritis (n = 30). Methodological and reporting limitations compromised interpretation of findings, most notably a lack of longitudinal studies, and inadequate control for key prognostic factors. The following candidate biomarkers with future potential utility were identified for predicting disease severity: LCE3D, interleukin (IL)23R, IL23A, NFKBIL1 loci, HLA-C*06:02 (genomic), IL-17A, IgG aHDL, GlycA, I-FABP and kallikrein 8 (proteomic), tyramine (metabolomic); psoriatic arthritis: HLA-C*06:02, HLA-B*27, HLA-B*38, HLA-B*08, and variation at the IL23R and IL13 loci (genomic); IL-17A, CXCL10, Mac-2 binding protein, integrin b5, matrix metalloproteinase-3 and macrophage-colony stimulating factor (proteomic) and tyramine and mucic acid (metabolomic); and type 2 diabetes mellitus: variation in IL12B and IL23R loci (genomic). No biomarkers were supported by sufficient evidence for clinical use without further validation. CONCLUSIONS: This review provides a comprehensive catalogue of investigated biomarkers of disease progression in psoriasis. Future studies must address the common methodological limitations identified herein to expedite discovery and validation of biomarkers for clinical use. What is already known about this topic? The current treatment paradigm in psoriasis is reactive. There is a need to develop effective risk-stratified management approaches that can proactively attenuate the substantial burden of disease. Prognostic biomarkers of disease progression have therefore been the focus of intense research. What does this study add? This review is the first to scope, collate and catalogue research investigating biomarkers of disease progression in psoriasis. The review identifies potentially promising candidate biomarkers for further investigation and highlights common important limitations that should be considered when designing and conducting future studies in this area.

Genome-wide association meta-analysis identifies 29 new acne susceptibility loci.

Acne vulgaris is a highly heritable skin disorder that primarily impacts facial skin. Severely inflamed lesions may leave permanent scars that have been associated with long-term psychosocial consequences. Here, we perform a GWAS meta-analysis comprising 20,165 individuals with acne from nine independent European ancestry cohorts. We identify 29 novel genome-wide significant loci and replicate 14 of the 17 previously identified risk loci, bringing the total number of reported acne risk loci to 46. Using fine-mapping and eQTL colocalisation approaches, we identify putative causal genes at several acne susceptibility loci that have previously been implicated in Mendelian hair and skin disorders, including pustular psoriasis. We identify shared genetic aetiology between acne, hormone levels, hormone-sensitive cancers and psychiatric traits. Finally, we show that a polygenic risk score calculated from our results explains up to 5.6% of the variance in acne liability in an independent cohort.