Polymorphisms in A20 (TNFAIP3), a negative regulator of ubiquitin-mediated immune signaling, are strongly associated with psoriasis and psoriasis arthritis (PsA). The tissue-specific roles of A20 in preventing these diseases are poorly understood. Because cutaneous psoriasis typically precedes PsA by several years, skin inflammation may represent a key driver of joint disease. We now find that keratinocyte-specific deletion of A20 in normally developed adult mice spontaneously triggers both psoriasiform skin and joint disease, demonstrating a crucial role for epidermal A20 in restricting PsA-like pathology. Mice with A20-deficient keratinocytes that lack T cells were protected from PsA-like disease, showing a key role for epidermally triggered lymphocytes in driving joint inflammation. Early gene expression analysis after keratinocyte A20 deletion identified activation of MyD88 and antiviral signaling, reflecting spatial transcriptomic changes of human psoriatic epidermis. Keratinocyte-specific loss of A20 together with MyD88 but not germline disruption of IFN receptors in vivo protected mice from skin and joint pathology. A20-deficient primary keratinocytes from both mice and CRISPR-edited human cells spontaneously produced inflammatory cytokines and chemokines in vitro in a MyD88-dependent manner. A20-deficient murine keratinocytes also directly triggered IL-17A secretion from wild-type T cells. Together, our data demonstrate that keratinocyte A20 is critical for preventing T-cell-dependent PsA-like disease.

BACKGROUND:Select patients are diagnosed with both psoriasis (PSO) and hidradenitis suppurativa (HS), leading to a unique disease pattern. Genetic risk factors remain unidentified. METHODS:The study harnessed an international collection of patients with PSO and HS (PSO-SH). Clinical and genetic data were collected and analyzed. RESULTS:Eighty-seven PSO-SH patients (70% female) were identified. They had a high number of comorbidities (89%) and worse general physical health compared to PSO-only (OR: 3.09; 95% CI: 1.56-6.12) or HS-only (OR: 2.5; 95% CI: 1.23-5.00) patients. PSO-SH patients were at significantly higher risk of having Crohn's disease (OR: 4.6-11.9; 95% CI). Data revealed the highest overall genetic risk score for PSO-SH patients (PSO-polygenic risk score; 108.22), followed by PSO (101.18), HS (99.84), and healthy controls (98.58). High non-human leukocyte antigen scores were associated with an increased risk for developing both PSO and HS, indicating a distinct biological profile compared to HS-only and PSO-only individuals. LIMITATIONS:Some clinical information was collected retrospectively. CONCLUSIONS:This study highlights a shared genetic susceptibility of HS and PSO at non-human leukocyte antigen loci. Recognizing PSO-SH patients as a distinct patient group with high morbidity and increased risk for developing Crohn's disease will help to improve patient management.

Psoriasis is a chronic, immune-mediated inflammatory skin disease associated with a polygenic mode of inheritance. There are few studies that explore the association of a psoriasis Polygenic Risk Score (PRS) with patient clinical characteristics, and to our knowledge there are no studies examining psoriasis PRS associations across different ethnicities. In this study, we used a multi-racial psoriasis cohort to investigate PRS associations with clinical phenotypes including age of onset, psoriatic arthritis, other comorbidities, psoriasis body location, psoriasis subtype, environmental triggers, and response to therapies. We collected patient data and Affymetrix genome-wide SNP data from a cohort of 607 psoriasis patients and calculated an 88-loci PRS (PRS-ALL), also partitioned between genetic loci within the HLA region (PRS-HLA; 11 SNPS) and loci outside the HLA region (PRS-NoHLA; 77 SNPS). We used t-test and logistic regression to analyze the association of PRS with clinical phenotypes. We found that PRS-HLA and PRS-noHLA had differing effects on psoriasis age of onset, psoriatic arthritis, psoriasis located on the ears, genitals, nails, soles of feet, skin folds, and palms, skin injury as an environmental trigger, cardiovascular comorbidities, and response to phototherapy. In some cases these PRS associations were ethnicity specific. Overall, these results show that the genetic basis for clinical manifestations of psoriasis are driven by distinct HLA and non-HLA effects, and that these PRS associations can be dependent on ethnicity.

Background: Preliminary evidence shows a possible association between hidradenitis suppurativa (HS) and obstructive sleep apnea (OSA), which is associated with various cardiovascular comorbidities. Objectives: To determine the odds of OSA among patients with HS compared with patients without HS. Methods: We performed a cross-sectional analysis using the All of Us research program database using electronic health records (EHR) and survey data from individual patient records extracted on 7 May 2022. Adult patients with available EHR records who either had at least one recorded diagnosis of HS determined by SNOMED-CT code (HS cohort) or did not have a diagnosis (non-HS cohort). The main outcome was a diagnosis of OSA as determined by SNOMED-CT code. Demographic features, survey data, and relevant comorbidities were also collected. Results: A total of 1647 patients with HS and 269,492 patients without HS were included. Of the HS patients, the mean age was 50.2 years, 79.0% were female, 39.8% were African American, 38.4% were White, and 17.4% were Hispanic or Latino. The prevalence of OSA in HS patients was 22.2% compared with 4.8% in non-HS patients. Univariate and multivariate odds ratios of OSA between HS and non-HS patients were 3.04 (95% confidence interval [CI]: 2.70-3.42) and 2.00 (95% CI: 1.72-2.33), respectively. The odds of OSA were highest in HS patients who were male, white, over 65 years of age, obese, and had hypertension, or hypothyroidism. Conclusions: The odds of being affected by both HS and OSA are augmented by multiple demographic factors, including white race, male gender, obesity, hypertension, hypothyroidism, and age over 65. Longitudinal studies are needed to confirm these findings.

Psoriasis is an immune-mediated inflammatory skin disease typically characterized by erythematous and scaly plaques. It affects 3% of the Newfoundland population while only affecting 1.7% of the general Canadian population. Recent genome-wide association studies (GWAS) in psoriasis have identified more than 63 genetic susceptibility loci that individually have modest effects. Prior studies have shown that a genetic risk score (GRS) combining multiple loci can improve psoriasis disease prediction. However, these prior GRS studies have not fully explored the association of GRS with patient clinical characteristics. In this study, we calculated three types of GRS: one using all known GWAS SNPs (GRS-ALL), one using a subset of SNPs from the HLA region (GRS-HLA), and the last using non-HLA SNPs (GRS-noHLA). We examined the relationship between these GRS and a number of psoriasis features within a well characterized Newfoundland psoriasis cohort. We found that both GRS-ALL and GRS-HLA were significantly associated with early age of psoriasis onset, psoriasis severity, first presentation of psoriasis at the elbow or knee, and the total number of body locations affected, while only GRS-ALL was associated with a positive family history of psoriasis. GRS-noHLA was uniquely associated with genital psoriasis. These findings clarify the relationship of the HLA and non-HLA components of GRS with important clinical features of psoriasis.

To the Editor: Patients with psoriasis have an increased risk for comorbidities such as cardiometabolic disease and psoriatic arthritis.1Yamazaki F. Psoriasis: comorbidities.J Dermatol. 2021; 48: 732-740https://doi.org/10.1111/1346-8138.15840Crossref PubMed Scopus (39) Google Scholar However, the association of other rheumatic diseases with psoriasis remains to be fully elucidated. We conducted a cross-sectional cohort study in the United States-based racially and ethnically diverse All of Us (AoU) national database (∼40% non-White; https://allofus.nih.gov), investigating the association between psoriasis and rheumatic diseases. Subjects were adults aged 18 and older with electronic health records (EHRs) in the AoU database. Two cohorts, including a psoriasis (PsO) group (2 or more ICD9/10 diagnoses of psoriasis) and a control group (individuals without a diagnosis of PsO), were identified on May 14, 2022. Rheumatic diseases of interest (axial spondyloarthritis [axSpA], dermatomyositis [DM], fibromyalgia [FM], gout, osteoarthritis [OA], polymyositis [PM], psoriatic arthritis [PsA], rheumatoid arthritis [RA], Sjogren's syndrome [SS], systemic lupus erythematosus [SLE], and systemic sclerosis [SSc]) were identified according to ICD9/10 coded criteria (Supplementary Table 1, available via Mendeley at https://doi.org/10.17632/5hbv6s26fd.1). Data from participant surveys, including age, sex at birth, race, and ethnicity, smoking history, alcohol use history, income, and rural location were extracted. R version 4.1.2 was used to analyze information provided in the All of Us (AoU) database using EHR data for PsO patients and non-PsO controls. The Benjamini–Hochberg procedure was used to correct for multiple testing. Demographic data are shown in Table I, and univariate and multivariate analysis are summarized in Table II. After controlling for age, race, ethnicity, obesity, smoking, alcohol, income, and delay in care due to rural location, there was a significant association of PsO with psoriatic arthritis (PsA), osteoarthritis (OA), gout, fibromyalgia (FM), rheumatoid arthritis (RA), AS, Sjogren’s syndrome (SS), and systemic sclerosis (SSc). There was a significant and strong association of PsO with CD but not UC, which was performed as an internal control. Due to clinical overlap between PsA and other rheumatic conditions, we examined the percentage of PsA patients diagnosed with concomitant diseases (Supplementary Table 3, available via Mendeley at https://doi.org/10.17632/5hbv6s26fd.1). Common co-diagnosis in PsA patients includes OA (47.6%), RA (15.1%), and FM (12.7%).Table IDemographics for psoriasis (PsO) patients versus nonpsoriasis controls. P-values calculated using χ2 statistics. For each variable examined, the totals reflect number of patients without missing dataPsOControlsP-valueTotal (n)3267265,957–Age, mean (SD)62.28 (14.72)54.69 (16.67)<1.00e-5BMI, mean (SD)30.81 (7.39)29.76197 (7.48)<1.00e-5Obesity (BMI > 30), n (%)<1.00e-5 Nonobese1658 (52.62%)153719 (59.22%) Obese1493 (47.38%)105840 (40.78%)Age group, n (%)<1.00e-5 18-44527 (16.13%)85550 (32.17%) 45-651167 (35.72%)100173 (37.67%) >651573 (48.15%)80234 (30.17%)Sex at birth, n (%).35 Male1295 (40.26%)103441 (39.43%) Female1923 (59.74%)158916 (60.57%)Race, n (%)<1.00e-5 White2390 (85.11%)131409 (61.87%) Black or African American229 (8.16%)63166 (29.74%) Asian88 (3.13%)8442 (3.97%) Other∗Defined as a sum of the answer choices “Another single population”, “More than one population”, and “None of these”.101 (3.60%)9386 (4.41%)Ethnicity, n (%)<1.00e-5 Not Hispanic/Latinx2706 (85.41%)203763 (78.94%) Hispanic/Latinx462 (14.58%)54347 (21.1%)Alcohol use (ever), n (%)<1.00e-5 Yes2973 (92.91%)226189 (87.64%) No227 (7.09%)31883 (12.35%)Alcohol use within past year, n (%)5.03e-4 Yes2345 (72.53%)182515 (69.97%) No888 (27.47%)79324 (30.03%)Cigarette use (>100 cigarettes/lifetime), n (%)<1.00e-5 Yes1561 (48.87%)106697 (41.61%) No1633 (51.13%)149704 (58.39%)Annual income level<1.00e-5 Low (<$50k)1246 (44.7%)118397 (56.7%) Middle ($50k-$150k)1070 (38.4%)66201 (31.7%) High (>$150k)470 (16.9%)24145 (11.6%)Rural†Defined as a participant-reported delay in care due to living in a rural location..62 No1616 (97.23%)89964 (97.14%) Yes46 (2.76%)2762 (2.86%)BMI, Body mass index; n, number; PMD, patient missing data; PsO, psoriasis; SD, standard deviation.∗ Defined as a sum of the answer choices “Another single population”, “More than one population”, and “None of these”.† Defined as a participant-reported delay in care due to living in a rural location. Open table in a new tab Table IIPrevalence and odds ratio (OR) of concomitant musculoskeletal and rheumatologic diseasesPsO(% of total)Controls(% of total)Univariate OR (95% CI)Univariate P-valueMultivariate OR∗Multivariate analysis controlled for age group, race, ethnicity, obesity, smoker, alcohol use within the past year, income level, and delay in care due to rural location. (95% CI)Multivariate P-valuePsA705 (21.6%)314 (0.1%)146.46 (119.95-179.58)<2e-16135.02 (108.25-169.27)<2E-16OA1233 (37.7%)41289 (15.5%)2.56 (2.30-2.85)<2e-162.23 (1.97-2.53)<2E-16Gout192 (5.9%)5118 (1.9%)2.45 (1.90-3.10)5.63E-132.15 (1.63-2.78)1.78E-08FM219 (6.7%)5628 (2.1%)2.96 (2.38-3.64)<2e-162.82 (2.21-3.56)<2E-16SLE54 (1.7%)2124 (8.0%)1.32 (0.74-2.17)0.3011.19 (0.59-2.12)0.59RA193 (5.9%)4089 (1.5%)3.70 (2.91-4.63)<2e-163.33 (2.54-4.29)<2E-16AxSpA33 (1.0%)367 (0.1%)5.76 (3.30-9.36)3.37E-115.19 (2.78-8.91)2.35E-08SS74 (2.3%)1972 (0.7%)2.25 (1.57-3.11)3.55E-061.93 (1.28-2.80)9.41E-04SSc<20†Exact values not reported to protect patient privacy, as per the All of Us database user agreements.<400†Exact values not reported to protect patient privacy, as per the All of Us database user agreements.3.12 (1.32-6.20)0.00352.93 (1.14-6.16)0.01PM<20†Exact values not reported to protect patient privacy, as per the All of Us database user agreements.<200†Exact values not reported to protect patient privacy, as per the All of Us database user agreements.3.41 (0.55-11.26)0.092.28 (0.13-10.93)0.42DM<20†Exact values not reported to protect patient privacy, as per the All of Us database user agreements.<100†Exact values not reported to protect patient privacy, as per the All of Us database user agreements.2.37 (0.39-7.68)0.232.96 (0.48-9.81)0.14CD90 (2.8%)1581 (0.6%)3.30 (2.29-4.58)1.21E-113.11 (2.06-4.49)9.44E-09UC57 (1.7%)1530 (0.6%)1.59 (0.95-2.46)0.05511.09 (0.56-1.89)0.78AxSpA, Axial spondyloarthritis; CD, Crohn's disease; CI, confidence interval; DM, dermatomyositis; FM, fibromyalgia; OA, osteoarthritis; OR, odds ratio; PM, polymyositis; PsA, psoriatic arthritis; PsO, psoriasis; RA, rheumatoid arthritis; SLE, systemic lupus erythematosus; SS, Sjogren's syndrome; SSc, systemic sclerosis (scleroderma); UC, ulcerative colitis.∗ Multivariate analysis controlled for age group, race, ethnicity, obesity, smoker, alcohol use within the past year, income level, and delay in care due to rural location.† Exact values not reported to protect patient privacy, as per the All of Us database user agreements. Open table in a new tab BMI, Body mass index; n, number; PMD, patient missing data; PsO, psoriasis; SD, standard deviation. AxSpA, Axial spondyloarthritis; CD, Crohn's disease; CI, confidence interval; DM, dermatomyositis; FM, fibromyalgia; OA, osteoarthritis; OR, odds ratio; PM, polymyositis; PsA, psoriatic arthritis; PsO, psoriasis; RA, rheumatoid arthritis; SLE, systemic lupus erythematosus; SS, Sjogren's syndrome; SSc, systemic sclerosis (scleroderma); UC, ulcerative colitis. The association of PsO with systemic conditions is a growing focus because of its impact on the overall wellbeing of patients beyond the skin manifestations. Co-occurrence of psoriasis and rheumatic diagnoses may in part be due to common underlying mechanisms such as higher BMI.2Kulkarni K. Karssiens T. Kumar V. Pandit H. Obesity and osteoarthritis.Maturitas. 2016; 89: 22-28https://doi.org/10.1016/j.maturitas.2016.04.006Abstract Full Text Full Text PDF PubMed Scopus (167) Google Scholar, 3D'Onghia M. Ciaffi J. Lisi L. et al.Fibromyalgia and obesity: a comprehensive systematic review and meta-analysis.Semin Arthritis Rheum. 2021; 51: 409-424https://doi.org/10.1016/j.semarthrit.2021.02.007Crossref PubMed Scopus (24) Google Scholar, 4Armstrong A.W. Harskamp C.T. Armstrong E.J. The association between psoriasis and obesity: a systematic review and meta-analysis of observational studies.Nutr Diabetes. 2012; 2e54https://doi.org/10.1038/nutd.2012.26Crossref PubMed Scopus (350) Google Scholar, 5Han J.H. Lee J.H. Han K.D. et al.Increased risk of psoriasis in subjects with abdominal obesity: a nationwide population-based study.J Dermatol. 2019; 46: 695-701https://doi.org/10.1111/1346-8138.14939Crossref PubMed Scopus (19) Google Scholar In our analysis, obesity as an independent covariate was significantly associated with an increased risk of all joint diagnoses investigated (PsA, OA, gout, RA, and AxSpA) as well as FM (Supplementary Table 2, available via Mendeley at https://doi.org/10.17632/5hbv6s26fd.1). Of note, however, PsO was associated with an increased odds of rheumatic diseases compared to controls even after adjustment for body mass index (BMI). The strength of this cross-sectional study is the inclusion of a relatively diverse set of patients in the AoU database, which allows our conclusions to be more generalizable. However, the potential for misclassification by incorrect diagnoses in the EHR is a limitation, especially regarding rheumatic disease in relation to PsA. The study was cross-sectional, limiting analysis of the temporal relationship between PsO and these rheumatic diseases. Overall, this study suggests the importance of screening PsO patients for MSK symptoms and referral to a rheumatologist if warranted. Tina Bhutani is a principal investigator for trials sponsored by Abbvie, Castle, CorEvitas, Dermavant, Galderma, Mindera, and Pfizer. She has received research grant funding from Novartis and Regeneron. She has been an advisor for Abbvie, Arcutis, Boehringer-Ingelheim, Bristol Myers Squibb, Janssen, Leo, Lilly, Novartis, Pfizer, Sun, and UCB. Wilson Liao has received research grant funding from Abbvie, Amgen, Janssen, Leo, Novartis, Pfizer, Regeneron, and TRex Bio. Lianne S. Gensler has received grant funding from Novartis, Pfizer and UCB and has been an advisor for AbbVie, Eli Lilly, Fresenius Kabi, Gilead, Janssen, MoonLake, Novartis, Pfizer and UCB. The remaining authors have nothing to disclose. The All of Us Research Program is supported by the following: the National Institutes of Health, Office of the Director: Regional Medical Centers: 1 OT2 OD026549; 1 OT2 OD026554; 1 OT2 OD026557; 1 OT2 OD026556; 1 OT2 OD026550; 1 OT2 OD 026552; 1 OT2 OD026553; 1 OT2 OD026548; 1 OT2 OD026551; 1 OT2 OD026555; IAA #: AOD 16037; Federally Qualified Health Centers: HHSN 263201600085U; Data and Research Center: 5 U2C OD023196; Biobank: 1 U24 OD023121; The Participant Center: U24 OD023176; Participant Technology Systems Center: 1 U24 OD023163; Communications and Engagement: 3 OT2 OD023205; 3 OT2 OD023206; and Community Partners: 1 OT2 OD025277; 3 OT2 OD025315; 1 OT2 OD025337; 1 OT2 OD025276. We thank all the participants of All of Us for their invaluable participation and collaboration with this program.

Background: Introduction: Hidradenitis suppurativa (HS) and psoriasis are chronic inflammatory skin disorders with shared features in pathogenesis [1-3]. However, there is a paucity of studies characterizing patients with both diseases. This study seeks to elucidate the clinical characteristics associated with this patient population.

Psoriasis is an immune-mediated disease characterized by skin and systemic inflammation that affects 125 million people worldwide. However, the underlying pathways contributing to psoriasis pathogenesis have not been fully elucidated. This project uses single-cell transcriptomes of T cells and other immune cell types from healthy and psoriatic skin in an effort to identify key biomarkers and pathways of psoriasis. T cells were clustered into subtypes and differential gene expression analysis was performed between lesional and healthy skin to identify psoriatic marker genes in each T cell subtype. Regulatory CD4+ T cells in psoriasis lesional skin were found to upregulate cytokines such as IL-32, as well as genes in the interferon-gamma-mediated signaling, NF-κB signaling, and putrescine catabolic pathways. As a result, psoriatic Tregs may amplify several of the pathways behind psoriasis and drive inflammation via IL-32, which has been previously found to be significantly upregulated in plaque psoriasis. Ongoing work includes using stratification by HLA type, VDJ analysis to more closely investigate psoriatic TCR abnormalities, and incorporation of more patient data.

Ankylosing spondylitis (AS) is an immune-mediated inflammatory disorder that primarily affects the axial skeleton, especially the sacroiliac joints and spine. This results in chronic back pain and, in extreme cases, ankylosis of the spine. Despite its debilitating effects, the pathogenesis of AS remains to be further elucidated. This study used single cell CITE-seq technology to analyze peripheral blood mononuclear cells (PBMCs) in AS and in healthy controls. We identified a number of molecular features associated with AS. CD52 was found to be overexpressed in both RNA and surface protein expression across several cell types in patients with AS. CD16 + monocytes overexpressed TNFSF10 and IL-18Rα in AS, while CD8 + T EM cells and natural killer cells overexpressed genes linked with cytotoxicity, including GZMH, GZMB , and NKG7 . Tregs underexpressed CD39 in AS, suggesting reduced functionality. We identified an overrepresented NK cell subset in AS that overexpressed CD16, CD161, and CD38, as well as cytotoxic genes and pathways. Finally, we developed machine learning models derived from CITE-seq data for the classification of AS and achieved an Area Under the Receiver Operating Characteristic (AUROC) curve of > 0.95. In summary, CITE-seq identification of AS-associated genes and surface proteins in specific cell subsets informs our understanding of pathogenesis and potential new therapeutic targets, while providing new approaches for diagnosis via machine learning.

Journal of Psoriasis and Psoriatic Arthritis 2022, Vol. 7(2) 99–108 © The Author(s) 2022 Article reuse guidelines: sagepub.com/journals-permissions DOI: 10.1177/24755303221084594 journals.sagepub.com/home/jps Abstracts from the 2021 NPF Research Symposium Meeting Every 2 years the National Psoriasis Foundation hosts the Research Symposium, where the latest in psoriatic disease and comorbidities research is presented and discussed. The 2021 symposium focused on research efforts aimed at improving health outcomes in those with psoriatic disease. NPF welcomed stakeholders to submit abstracts that are related to outcomes in psoriasis and psoriatic arthritis. Via peer-review, 19 abstracts were accepted and provided permission to share here. Multi-omics Diagnosis of Psoriatic Arthritis Julie Hong, Mimi Chung, Jared Liu, Sugandh Kumar, ZhiMing Huang, Diana Paez, Megan Mosca, Edward Hadeler, Marwa Hakimi, Samuel Yeroushalmi, Erin Bartholomew, Chun Ye, Mehrdad Matloubian, Tina Bhutani, Lianne Gensler, and Wilson Liao University of California, San Francisco, CA, USA Up to 30% of patients with psoriasis also develop psoriatic arthritis (PsA), a debilitating condition affecting the joints and musculoskeletal system that significantly lowers patients’ quality of life. It is crucial to have a diagnostic test available for PsA, which will allow for earlier detection and therapeutic intervention. To tackle this problem, we brought together a diverse team of dermatologists, rheumatologists, and bioinformaticians. We hypothesized that to identify suitable molecular markers for PsA, we would need to take a discovery approach casting a broad net in search of novel markers. We therefore utilized CITE-Seq (Cellular Indexing of Transcriptomes and Epitopes by Sequencing) and SNP genotyping to profile the PBMCs of patients with PsA, psoriasis without PsA (PsO), and healthy controls. We generated full single cell transcriptome and 282-cell surface marker data for 90 individuals, identifying over 30 distinct PBMC subsets including CD4 CTL, CD4 Naive, CD4 Proliferating, CD4 TCM, CD4 TEM, CD8 Naive, C08 Proliferating, CD8 TCM, CD8 TEM, Treg, gamma delta T, B intermediate, B memory, B naive, Plasmablast, ILC, MAIT, NK, NK Proliferating, NK CD56bright, C014 Mono, CD16 Mono, cDC1, cOC2, pDC, ASDC, and HSPC. Comparing PsA with PsO, we found that the cellular proportion of Tregs significantly differed between these two groups. Moreover, we identified >1000 individual gene or protein markers differentially expressed between PsA and PsO with an adjusted P-value less than 1E-04. We constructed a multi-marker predictive model demonstrating a mean PsA classification accuracy of >95%. In the next phase of this project, wewill validate the PsA signature using independent patient cohorts. Ultimately, we hope to develop a diagnostic test that is simple for patients to obtain, that can be objectively interpreted, and is highly accurate. Cardiac biomarkers are associated with the development of cardiovascular events in patients with psoriatic disease Keith Colaco, Ker-Ai Lee, Shadi Akhtari, Raz Winer, Paul Welsh, Naveed Sattar, Iain B McInnes, Vinod Chandran, Paula Harvey, Richard J Cook, Dafna D Gladman, Vincent Piguet, and Lihi Eder Women’s College Research Institute, Women’s College Hospital, Toronto, ON, Canada Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada Schroeder Arthritis Institute, University Health Network, Toronto, ON, Canada Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, ON, Canada Department of Cardiology, Women’s College Hospital, Toronto, ON, Canada Department of Medicine, University of Toronto, Toronto, ON, Canada Department of Neurology, Rambam Health Care Campus, Haifa, Israel BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, UK Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow, UK Women’s College Research Institute, Women’s College Hospital, Toronto, ON, Canada Background/Purpose: N-terminal pro-brain-type natriuretic peptide (NT-proBNP) and troponin I (Tnl) are established cardiac biomarkers that predict cardiovascular events (CVEs) and mortality in apparently healthy individuals and at-risk populations. While patients with psoriatic arthritis and psoriasis, collectively termed psoriatic disease (PsD), have an increased risk of developing CVEs, the use of these cardiac biomarkers to predict CV risk has not been investigated in this population. We aimed to evaluate the association between these cardiac biomarkers and incident CVEs and assess their predictive value beyond the Framingham Risk Score (FRS). Methods: A longitudinal cohort study was conducted in patients with PsD without prior history of CVEs. NT-proBNP and Tnl concentrations were measured using automated clinical assays in the first available serum sample. The study outcome included any of the following CVEs occurring within the first 10 years of biomarker assessment: angina, myocardial infarction, transient ischemic attack, cerebrovascular accident, revascularization procedures and CV death. Associations with incident CVEs were analyzed separately for each biomarker using Cox proportional hazards regression models first adjusted for age and sex, and subsequently for the FRS. The added value of cardiac biomarkers to improve predictive performance beyond the FRS was assessed using the area under the receiver operator characteristic curve (AUC), net reclassification index (NRI) and integrated discrimination index (IOI). Results: A total of 1000 patients with PsD were assessed between 2002 and 2019 (mean age 49 ± 12.8 years, 44.6% female). During a mean follow-up of 7.1 years, 64 (6.4%) patients developed incident CVEs. Both Tnl (Hazard Ratio (HR) 3.02, 95% Confidence Interval (Cl) 1.12, 8.16) and NTproBNP (HR2.02; 95% Cl 1.28, 3.18) predicted CVEs independently of the FRS. The association was stronger in males than females. Including all cardiac biomarkers and the FRS in a single model, NTproBNP retained statistical significance (HR 1.91, 95% Cl 1.23, 2.97), while Tnl did not (HR 2.60, 95% Cl .98, 6.87). When comparing the predictive performance of the base model (FRS alone, AUC 75.4) to the expanded models, there was no significant improvement in any of the predictive indices with the addition of Tnl (AUC 73.5, P = .21; NRI .08, P = .67; IOI .005, P = .37), NTproBNP (AUC 71.0, P =.35; NRI .20, P = .06; IOI .017, P = .10), or both Tnl and NT-proBNP (AUC 7.0, P = .23; NRI .27, P = .05; IOI .021, p =.05). Conclusions: In patients with PsO, elevated NT-proBNP and Tnl predict incident CVEs independent of the FRS. We did not observe a significant improvement in the performance of the predictive model when combining these cardiac biomarkers with the FRS. MHC haplotype controls the development of IL-23 minicircle-induced murine spondyloarthritis Emma K. Haley, Mederbek Matmusaev, Jyotsna Soundararajan, and Joerg Ermann Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital Boston, MA, USA Harvard Medical School, Boston, MA, USA Introduction: Arthritis induced by systemic overexpression of IL-23 in B1.RIII mice is an established model of spondyloarthritis. Tissue-resident gd T cells expressing the IL-23 receptor are thought to play a critical role in this model. B1.RIII is an MHC congenic strain carrying the RIII-derived H-2r region on a C57BL/10 (B10) background. We found that neither B10 nor the closely related C57BL/6 (B6) reference strain develop IL-23 minicircle-induced arthritis. Due to incomplete backcrossing, the genome of B1.RIII mice contains RIII-derived regions outside of H-2. One of these ‘contaminating’ regions, Cia8 on chromosome 10, was previously shown to control the development of collagen antibody induced arthritis. The goal of this study was to genetically interrogate the role of Cia8 and H-2 in IL-23 minicircle-induced murine spondyloarthritis. Methods: Informative crosses were set up between B1.RIII (Cia8r/r.H-2r/r) and B10 (Cia8b/b.H-2b/b) mice and between B1.RIII and B6 (Cia8b/b.H-2b/b) mice, respectively. Genotyped adult male littermates were hydrodynamically injected with 50 ng IL-23 EEV (System Bioscience) and blindly monitored for the development of arthritis every other day for 2 weeks. At the end of the study, IL-23 was measured in the serum and forepaws were analyzed by light microscopy. Results: In the offspring from a (B1.RIII × B10) N2 intercross, Cia8r/r.H-2r/r and Cia8b/b.H-2r/r mice developed arthritis with similar incidence and severity whereas Cia8r/r.H2b/b mice did not develop arthritis. In (B1.RIII × B6) F2 mice, H-2b/b mice were similarly protected while H-2r/r and H-2b/r mice developed arthritis. The Cia8 genotype (Cia8r/r vs. Cia8b/b) had no impact on arthritis development in (B1.RIII × B6) F2 mice. Serum IL-23 levels were comparable between groups. Conclusions: The development of IL-23 induced murine spondyloarthritis is controlled by the genomic background of the mice. Data from two complementary experiments demonstrate that arthritis susceptibility in this model maps to the H-2 (MHC) region on chromosome 17 and not Cia8 on chromosome 1. The critical role of the MHC in IL-23 minicircle-induced arthritis is surprising, considering that gd T cells are not MHC restricted. IL-23 minicircle-induced arthritis may serve as a model to interrogate the relationship between MHC and the IL-23/IL-17A axis. Platelet activation is present in psoriasis and associated with biomarkers of inflammation and vascular stiffness Kamelia Drenkova, Khrystyna Myndzar, Stuart D Katz, Andrea Neimann, Jose U Scher, James Krueger, Jeffrey S Berger, and Michael Garshick NYU Langone Health, New York, NY, USA New York University School of Medicine, New York, NY, USA The Rockefeller University, New York, NY, USA NYU Langone Medical Center, New York, NY, USA 100 Journal of Psoriasis and Psoriatic Art

Early diagnosis of psoriatic arthritis (PSA) is important for successful therapeutic intervention but currently remains challenging due, in part, to the scarcity of non-invasive biomarkers. In this study, we performed single cell profiling of transcriptome and cell surface protein expression to compare the peripheral blood immunocyte populations of individuals with PSA, individuals with cutaneous psoriasis (PSO) alone, and healthy individuals. We identified genes and proteins differentially expressed between PSA, PSO, and healthy subjects across 30 immune cell types and observed that some cell types, as well as specific phenotypic subsets of cells, differed in abundance between these cohorts. Cell type-specific gene and protein expression differences between PSA, PSO, and healthy groups, along with 200 previously published genetic risk factors for PSA, were further used to perform machine learning classification, with the best models achieving AUROC ≥ 0.87 when either classifying subjects among the three groups or specifically distinguishing PSA from PSO. Our findings thus expand the repertoire of gene, protein, and cellular biomarkers relevant to PSA and demonstrate the utility of machine learning-based diagnostics for this disease.

INTRODUCTION:Psoriasis (PSO) and psoriatic arthritis (PSA) represent a large burden of global inflammatory disease, but sustained treatment response and early diagnosis remain challenging. Both conditions arise from complex immune cell dysregulation. Single-cell techniques, including single-cell RNA sequencing (scRNA-seq), have revolutionized our understanding of pathogenesis by illuminating heterogeneous cell populations and their interactions.AREAS COVERED:We discuss the transcriptional profiles and cellular interactions unique to PSO/PSA affecting T cells, myeloid cells, keratinocytes, innate lymphoid cells, and stromal cells. We also review advances, limitations, and future challenges associated with single-cell studies.EXPERT OPINION:Following analyses of 22 single-cell studies, several themes emerged. A small subpopulation of cells can have a large impact on disease pathogenesis. Multiple cell types identified via scRNA-seq play supporting roles in PSO pathogenesis, contrary to the traditional paradigm focusing on IL-23/IL-17 signaling among dendritic cells and T cells. Immune cell states are dynamic, with psoriatic subpopulations aberrantly re-activating and differentiating into inflammatory phenotypes depending on surrounding signaling cues. Comparison of circulating immune cells with resident skin/joint cells has uncovered specific T cell clonotypes associated with the disease. Finally, machine learning models demonstrate great promise in identifying biomarkers to diagnose clinically ambiguous rashes and PSA at earlier stages.

The IL-17A inhibitor secukinumab is efficacious for the treatment of psoriasis. To better understand its mechanism of action, we investigated its impact on psoriatic lesions from 15 patients with moderate-to-severe plaque psoriasis undergoing secukinumab treatment. We characterized the longitudinal transcriptomic changes of whole lesional skin tissue as well as cutaneous CD4+ and CD8+ T effector cells and CD4+ T regulatory cells across 12 weeks of treatment. Secukinumab was clinically effective and reduced disease-associated overexpression of IL17A, IL17F, IL23A, IL23R, and IFNG in whole tissue as soon as 2 weeks after initiation of treatment. IL17A overexpression in T-cell subsets, primarily CD8+ T cells, was also reduced. Although secukinumab treatment resolved 89‒97% of psoriasis-associated expression differences in bulk tissue and T-cell subsets by week 12 of treatment, we observed expression differences involved in IFN signaling and metallothionein synthesis that remained unresolved at this time point as well as potential treatment-associated expression differences involved in IL-15 signaling. These changes were accompanied by shifts in broader immune cell composition on the basis of deconvolution of RNA-sequencing data. In conclusion, our study reveals several phenotypic and cellular changes within the lesion that underlie clinical improvement from secukinumab.

Background: Despite numerous genome-wide association studies conducted in psoriasis and psoriatic arthritis, only a small fraction of the identified genes has been therapeutically targeted. Objective: We sought to identify and analyze potential therapeutic targets for psoriasis and psoriatic arthritis (PsA) using the priority index (Pi), a genetics-dependent drug target prioritization approach. Methods: Significant genetic variants from GWAS for psoriasis, PsA, and combined psoriatic disease were annotated and run through the Pi pipeline. Potential drug targets were identified based on genomic predictors, annotation predictors, pathway enrichment, and pathway crosstalk. Results: Several gene targets were identified for psoriasis and PsA that demonstrated biological associations to their respective diseases. Some are currently being explored as potential therapeutic targets (i.e. ICAM1, NF-kB, REV3 L, ADRA1B for psoriasis; CCL11 for PsA); others have not yet been investigated (i.e. LNPEP, LCE3 for psoriasis; UBLCP1 for PsA). Additionally, many nodal points of potential intervention were identified as promising therapeutic targets. Of these, some are currently being studied such as TYK2 for psoriasis, and others have yet to be explored (i.e. PPP2CA, YAP1, PI3 K, AKT, FOXO1, RELA, CSF2, IFNGR1, IFNGR2 for psoriasis; GNAQ, PLCB1, GNAI2 for PsA). Conclusion: Through Pi, we identified data-driven candidate therapeutic gene targets and pathways for psoriasis and PsA. Given the sparse PsA specific genetic studies and PsA specific drug targets, this analysis could prove to be particularly valuable in the pipeline for novel psoriatic therapies.

Regulatory T cells (Tregs) reside in nonlymphoid tissues where they carry out unique functions. The molecular mechanisms responsible for Treg accumulation and maintenance in these tissues are relatively unknown. Using an unbiased discovery approach, we identified LAYN (layilin), a C-type lectin-like receptor, to be preferentially and highly expressed on a subset of activated Tregs in healthy and diseased human skin. Expression of layilin on Tregs was induced by TCR-mediated activation in the presence of IL-2 or TGF-β. Mice with a conditional deletion of layilin in Tregs had reduced accumulation of these cells in tumors. However, these animals somewhat paradoxically had enhanced immune regulation in the tumor microenvironment, resulting in increased tumor growth. Mechanistically, layilin expression on Tregs had a minimal effect on their activation and suppressive capacity in vitro. However, expression of this molecule resulted in a cumulative anchoring effect on Treg dynamic motility in vivo. Taken together, our results suggest a model whereby layilin facilitates Treg adhesion in skin and, in doing so, limits their suppressive capacity. These findings uncover a unique mechanism whereby reduced Treg motility acts to limit immune regulation in nonlymphoid organs and may help guide strategies to exploit this phenomenon for therapeutic benefit.

Background: Psoriasis is an inflammatory, IL-17-driven skin disease in which autoantigen-induced CD8(+) T cells have been identified as pathogenic drivers. Objective: Our study focused on comprehensively characterizing the phenotypic variation of CD8(+) T cells in psoriatic lesions. Methods: We used single-cell RNA sequencing to compare CD8(+) T-cell transcriptomic heterogeneity between psoriatic and healthy skin. Results: We identified 11 transcriptionally diverse CD8(+) T-cell subsets in psoriatic and healthy skin. Among several inflammatory subsets enriched in psoriatic skin, we observed 2 Tc17 cell subsets that were metabolically divergent, were developmentally related, and expressed CXCL13, which we found to be a biomarker of psoriasis severity and which achieved comparable or greater accuracy than IL17A in a support vector machine classifier of psoriasis and healthy transcriptomes. Despite high coinhibitory receptor expression in the Tc17 cell clusters, a comparison of these cells with melanoma-infiltrating CD8(+) T cells revealed upregulated cytokine, cytolytic, and metabolic transcriptional activity in the psoriatic cells that differed from an exhaustion program. Conclusion: Using high-resolution single-cell profiling in tissue, we have uncovered the diverse landscape of CD8(+) T cells in psoriatic and healthy skin, including 2 nonexhausted Tc17 cell subsets associated with disease severity.

Intestinal microbiota are considered a sensor for molecular pathways, which orchestrate energy balance, immune responses, and cell regeneration. We previously reported that microbiota restriction promoted higher levels of systemic radiation-induced genotoxicity, proliferative lymphocyte activation, and apoptotic polarization of metabolic pathways. Restricted intestinal microbiota (RM) that harbors increased abundance of Lactobacillus johnsonii (LBJ) has been investigated for bacterial communities that correlated radiation-induced genotoxicity. Indicator phylotypes were more abundant in RM mice and increased in prevalence after whole body irradiation in conventional microbiota (CM) mice, while none of the same ten most abundant phylotypes were different in abundance between CM mice before and after heavy ion irradiation. Muribaculum intestinale was detected highest in female small intestines in RM mice, which were lacking Ureaplasma felinum compared with males, and thus these bacteria could be contributing to the differential amounts of radiation-induced systemic genotoxicity between the CM and RM groups. Helicobacter rodentium and M.intestinale were found in colons in the radiation-resistant CM phenotype. While the expression of interferon-γ was elevated in the small intestine, and lower in blood in CM mice, high-linear energy transfer radiation reduced transforming growth factor-β with peripheral interleukin (IL)-17 in RM mice, particularly in females. We found that female RM mice showed improved micro-architectural bone structure and anti-inflammatory radiation response compared with CM mice at a delayed phase 6 weeks postexposure to particle radiation. However, microbiota restriction reduced inflammatory markers of tumor necrosis factor in marrow, when IL-17 was reduced by intraperitoneal injection of IL-17 neutralizing antibody.

Probiotics are considered to have multiple beneficial effects on the human gastrointestinal tract, including immunomodulation, pathogen inhibition, and improved host nutrient metabolism. However, extensive characterization of these properties is needed to define suitable clinical applications for probiotic candidates. Lactobacillus johnsonii 456 (LBJ 456) was previously demonstrated to have anti-inflammatory and anti-genotoxic effects in a mouse model. Here, we characterize its resistance to gastric and bile acids as well as its ability to inhibit gut pathogens and adhere to host mucosa. While bile resistance and in vitro host attachment properties of LBJ 456 were comparable to other tested probiotics, LBJ 456 maintained higher viability at lower pH conditions compared to other tested strains. LBJ 456 also altered pathogen adhesion to LS 174T monolayers and demonstrated contact-dependent and independent inhibition of pathogen growth. Genome analyses further revealed possible genetic elements involved in host attachment and pathogen inhibition. Importantly, we show that ingestion of Lactobacillus johnsonii 456 over a one week yogurt course leads to persistent viable bacteria detectable even beyond the period of initial ingestion, unlike many other previously described probiotic species of lactic acid bacteria.

Output of GraphPad Prism for statistics of heterogeneity of microbial communities isolated from skin associated with different disease state. (XML 18 kb)