Retrospective pharmacogenetic study of psoriasis highlights the role of KLK7 in tumour necrosis factor signalling.

BACKGROUND: Multiple treatment options are available for the management of psoriasis, but clinical response varies among individual patients and no biomarkers are available to facilitate treatment selection for improved patient outcomes. OBJECTIVES: To utilize retrospective data to conduct a pharmacogenetic study to explore the potential genetic pathways associated with drug response in the treatment of psoriasis. METHODS: We conducted a retrospective pharmacogenetic study using self-evaluated treatment response from 1942 genotyped patients with psoriasis. We examined 6 502 658 genetic markers to model their associations with response to six treatment options using linear regression, adjusting for cohort variables and demographic features. We further utilized an integrative approach incorporating epigenomics, transcriptomics and a longitudinal clinical cohort to provide biological implications for the topmost signals associated with drug response. RESULTS: Two novel markers were revealed to be associated with treatment response: rs1991820 (P = 1.30 × 10-6) for anti-tumour necrosis factor (TNF) biologics; and rs62264137 (P = 2.94 × 10-6) for methotrexate, which was also associated with cutaneous mRNA expression levels of two known psoriasis-related genes KLK7 (P = 1.0 × 10-12) and CD200 (P = 5.4 × 10-6). We demonstrated that KLK7 expression was increased in the psoriatic epidermis, as shown by immunohistochemistry, as well as single-cell RNA sequencing, and its responsiveness to anti-TNF treatment was highlighted. By inhibiting the expression of KLK7, we further illustrated that keratinocytes have decreased proinflammatory responses to TNF. CONCLUSIONS: Our study implicates the genetic regulation of cytokine responses in predicting clinical drug response and supports the association between pharmacogenetic loci and anti-TNF response, as shown here for KLK7.

Shared Genetic Risk Factors for Multiple Sclerosis/Psoriasis Suggest Involvement of Interleukin-17 and Janus Kinase-Signal Transducers and Activators of Transcription Signaling.

OBJECTIVE: Psoriasis and multiple sclerosis (MS) are complex immune diseases that are mediated by T cells and share multiple comorbidities. Previous studies have suggested psoriatic patients are at higher risk of MS; however, causal relationships between the two conditions remain unclear. Through epidemiology and genetics, we provide a comprehensive understanding of the relationship, and share molecular factors between psoriasis and MS. METHODS: We used logistic regression, trans-disease meta-analysis and Mendelian randomization. Medical claims data were included from 30 million patients, including 141,544 with MS and 742,919 with psoriasis. We used genome-wide association study summary statistics from 11,024 psoriatic, 14,802 MS cases, and 43,039 controls for trans-disease meta-analysis, with additional summary statistics from 5 million individuals for Mendelian randomization. RESULTS: Psoriatic patients have a significantly higher risk of MS (4,637 patients with both diseases; odds ratio [OR] 1.07, p = 1.2 × 10-5 ) after controlling for potential confounders. Using inverse variance and equally weighted trans-disease meta-analysis, we revealed >20 shared and opposing (direction of effect) genetic loci outside the major histocompatibility complex that showed significant genetic colocalization (in COLOC and COLOC-SuSiE v5.1.0). Co-expression analysis of genes from these loci further identified distinct clusters that were enriched among pathways for interleukin-17/tumor necrosis factor-α (OR >39, p < 1.6 × 10-3 ) and Janus kinase-signal transducers and activators of transcription (OR 35, p = 1.1 × 10-5 ), including genes, such as TNFAIP3, TYK2, and TNFRSF1A. Mendelian randomization found psoriasis as an exposure has a significant causal effect on MS (OR 1.04, p = 5.8 × 10-3 ), independent of type 1 diabetes (OR 1.05, p = 4.3 × 10-7 ), type 2 diabetes (OR 1.08, p = 2.3 × 10-3 ), inflammatory bowel disease (OR 1.11, p = 1.6 × 10-11 ), and vitamin D level (OR 0.75, p = 9.4 × 10-3 ). INTERPRETATION: By investigating the shared genetics of psoriasis and MS, along with their modifiable risk factors, our findings will advance innovations in treatment for patients suffering from comorbidities. ANN NEUROL 2023;94:384-397.

Genome-Wide Association Study in Acute Tubulointerstitial Nephritis.

SIGNIFICANCE STATEMENT: Polymorphisms of HLA genes may confer susceptibility to acute tubulointerstitial nephritis (ATIN), but small sample sizes and candidate gene design have hindered their investigation. The first genome-wide association study of ATIN identified two significant loci, risk haplotype DRB1*14-DQA1*0101-DQB1*0503 (DR14 serotype) and protective haplotype DRB1*1501-DQA1*0102-DQB1*0602 (DR15 serotype), with amino acid position 60 in the peptide-binding groove P10 of HLA-DR ß 1 key. Risk alleles were shared among different causes of ATIN and HLA genotypes associated with kidney injury and immune therapy response. HLA alleles showed the strongest association. The findings suggest that a genetically conferred risk of immune dysregulation is part of the pathogenesis of ATIN. BACKGROUND: Acute tubulointerstitial nephritis (ATIN) is a rare immune-related disease, accounting for approximately 10% of patients with unexplained AKI. Previous elucidation of the relationship between genetic factors that contribute to its pathogenesis was hampered because of small sample sizes and candidate gene design. METHODS: We undertook the first two-stage genome-wide association study and meta-analysis involving 544 kidney biopsy-defined patients with ATIN and 2346 controls of Chinese ancestry. We conducted statistical fine-mapping analysis, provided functional annotations of significant variants, estimated single nucleotide polymorphism (SNP)-based heritability, and checked genotype and subphenotype correlations. RESULTS: Two genome-wide significant loci, rs35087390 of HLA-DQA1 ( P =3.01×10 -39 ) on 6p21.32 and rs2417771 of PLEKHA5 on 12p12.3 ( P =2.14×10 -8 ), emerged from the analysis. HLA imputation using two reference panels suggested that HLA-DRB1*14 mainly drives the HLA risk association . HLA-DRB1 residue 60 belonging to pocket P10 was the key amino acid position. The SNP-based heritability estimates with and without the HLA locus were 20.43% and 10.35%, respectively. Different clinical subphenotypes (drug-related or tubulointerstitial nephritis and uveitis syndrome) seemed to share the same risk alleles. However, the HLA risk genotype was associated with disease severity and response rate to immunosuppressive therapy. CONCLUSIONS: We identified two candidate genome regions associated with susceptibility to ATIN. The findings suggest that a genetically conferred risk of immune dysregulation is involved in the pathogenesis of ATIN.

Large-scale epidemiological analysis of common skin diseases to identify shared and unique comorbidities and demographic factors.

Introduction: The utilization of large-scale claims databases has greatly improved the management, accessibility, and integration of extensive medical data. However, its potential for systematically identifying comorbidities in the context of skin diseases remains unexplored. Methods: This study aims to assess the capability of a comprehensive claims database in identifying comorbidities linked to 14 specific skin and skin-related conditions and examining temporal changes in their association patterns. This study employed a retrospective case-control cohort design utilizing 13 million skin/skin-related patients and 2 million randomly sampled controls from Optum's de-identified Clinformatics® Data Mart Database spanning the period from 2001 to 2018. A broad spectrum of comorbidities encompassing cancer, diabetes, respiratory, mental, immunity, gastrointestinal, and cardiovascular conditions were examined for each of the 14 skin and skin-related disorders in the study. Results: Using the established type-2 diabetes (T2D) and psoriasis comorbidity as example, we demonstrated the association is significant (P-values<1x10-15) and stable across years (OR=1.15-1.31). Analysis of the 2014-2018 data reveals that celiac disease, Crohn's disease, and ulcerative colitis exhibit the strongest associations with the 14 skin/skin-related conditions. Systemic lupus erythematosus (SLE), leprosy, and hidradenitis suppurativa show the strongest associations with 30 different comorbidities. Particularly notable associations include Crohn's disease with leprosy (odds ratio [OR]=6.60, 95% confidence interval [CI]: 3.09-14.08), primary biliary cirrhosis with SLE (OR=6.07, 95% CI: 4.93-7.46), and celiac disease with SLE (OR=6.06, 95% CI: 5.49-6.69). In addition, changes in associations were observed over time. For instance, the association between atopic dermatitis and lung cancer demonstrates a marked decrease over the past decade, with the odds ratio decreasing from 1.75 (95% CI: 1.47-2.07) to 1.02 (95% CI: 0.97-1.07). The identification of skin-associated comorbidities contributes to individualized healthcare and improved clinical management, while also enhancing our understanding of shared pathophysiology. Moreover, tracking these associations over time aids in evaluating the progression of clinical diagnosis and treatment. Discussion: The findings highlight the potential of utilizing comprehensive claims databases in advancing research and improving patient care in dermatology.

Enhanced rare disease mapping for phenome-wide genetic association in the UK Biobank.

BACKGROUND: Rare diseases collectively affect up to 10% of the population, but often lack effective treatment, and typically little is known about their pathophysiology. Major challenges include suboptimal phenotype mapping and limited statistical power. Population biobanks, such as the UK Biobank, recruit many individuals who can be affected by rare diseases; however, investigation into their utility for rare disease research remains limited. We hypothesized the UK Biobank can be used as a unique population assay for rare diseases in the general population. METHODS: We constructed a consensus mapping between ICD-10 codes and ORPHA codes for rare diseases, then identified individuals with each rare condition in the UK Biobank, and investigated their age at recruitment, sex bias, and comorbidity distributions. Using exome sequencing data from 167,246 individuals of European ancestry, we performed genetic association controlling for case/control imbalance (SAIGE) to identify potential rare pathogenic variants for each disease. RESULTS: Using our mapping approach, we identified and characterized 420 rare diseases affecting 23,575 individuals in the UK Biobank. Significant genetic associations included JAK2 V617F for immune thrombocytopenic purpura (p = 1.24 × 10-13) and a novel CALR loss of function variant for essential thrombocythemia (p = 1.59 × 10-13). We constructed an interactive resource highlighting demographic information ( http://www-personal.umich.edu/~mattpat/rareDiseases.html ) and demonstrate transferability by applying our mapping to a medical claims database. CONCLUSIONS: Enhanced disease mapping and increased power from population biobanks can elucidate the demographics and genetic associations for rare diseases.

Alcohol consumption and smoking in relation to psoriasis: a Mendelian randomization study.

BACKGROUND: Alcohol consumption and smoking have been reported to be associated with psoriasis risk. However, a conclusion with high-quality evidence of causality could not be easily drawn from regular observational studies. OBJECTIVES: This study aims to assess the causal associations of alcohol consumption and smoking with psoriasis. METHODS: Genome-wide association study (GWAS) summary-level data for alcohol consumption (N = 941 280), smoking initiation (N = 1 232 091), cigarettes per day (N = 337 334) and smoking cessation (N = 547 219) was obtained from the GSCAN consortium (Sequencing Consortium of Alcohol and Nicotine use). The GWAS results for lifetime smoking (N = 462 690) were obtained from the UK Biobank samples. Summary statistics for psoriasis were obtained from a recent GWAS meta-analysis of eight cohorts comprising 19 032 cases and 286 769 controls and the FinnGen consortium, comprising 4510 cases and 212 242 controls. Linkage disequilibrium score regression was applied to compute the genetic correlation. Bidirectional Mendelian randomization (MR) analyses were conducted to determine casual direction using independent genetic variants that reached genome-wide significance (P < 5 × 10-8 ). RESULTS: There were genetic correlations between smoking and psoriasis. MR revealed a causal effect of smoking initiation [odds ratio (OR) 1·46, 95% confidence interval (CI) 1·32-1·60, P = 6·24E-14], cigarettes per day (OR 1·38, 95% CI 1·13-1·67, P = 0·001) and lifetime smoking (OR 1·96, 95% CI 1·41-2·73, P = 7·32E-05) on psoriasis. Additionally, a suggestive causal effect of smoking cessation on psoriasis was observed (OR 1·39, 95% CI 1·07-1·79, P = 0·012). We found no causal relationship between alcohol consumption and psoriasis (P = 0·379). The reverse associations were not statistically significant. CONCLUSIONS: Our findings provide causal evidence for the effects of smoking on psoriasis risk. What is already known about this topic? Alcohol consumption and smoking have been reported to be associated with psoriasis risk. Whether alcohol consumption and smoking have a causal effect on psoriasis risk remains unclear. What does this study add? This Mendelian randomization study shows a causal association between smoking, but not alcohol consumption, and the risk of developing psoriasis. Restricting smoking could be helpful in reducing the burden of psoriasis.

Direct cellular reprogramming enables development of viral T antigen-driven Merkel cell carcinoma in mice.

Merkel cell carcinoma (MCC) is an aggressive neuroendocrine skin cancer that frequently carries an integrated Merkel cell polyomavirus (MCPyV) genome and expresses viral transforming antigens (TAgs). MCC tumor cells also express signature genes detected in skin-resident, postmitotic Merkel cells, including atonal bHLH transcription factor 1 (ATOH1), which is required for Merkel cell development from epidermal progenitors. We now report the use of in vivo cellular reprogramming, using ATOH1, to drive MCC development from murine epidermis. We generated mice that conditionally expressed MCPyV TAgs and ATOH1 in epidermal cells, yielding microscopic collections of proliferating MCC-like cells arising from hair follicles. Immunostaining of these nascent tumors revealed p53 accumulation and apoptosis, and targeted deletion of transformation related protein 53 (Trp53) led to development of gross skin tumors with classic MCC histology and marker expression. Global transcriptome analysis confirmed the close similarity of mouse and human MCCs, and hierarchical clustering showed conserved upregulation of signature genes. Our data establish that expression of MCPyV TAgs in ATOH1-reprogrammed epidermal cells and their neuroendocrine progeny initiates hair follicle-derived MCC tumorigenesis in adult mice. Moreover, progression to full-blown MCC in this model requires loss of p53, mimicking the functional inhibition of p53 reported in human MCPyV-positive MCCs.

Cytokine responses in nonlesional psoriatic skin as clinical predictor to anti-TNF agents.

BACKGROUND: A major issue with the current management of psoriasis is our inability to predict treatment response. OBJECTIVE: Our aim was to evaluate the ability to use baseline molecular expression profiling to assess treatment outcome for patients with psoriasis. METHODS: We conducted a longitudinal study of 46 patients with chronic plaque psoriasis treated with anti-TNF agent etanercept, and molecular profiles were assessed in more than 200 RNA-seq samples. RESULTS: We demonstrated correlation between clinical response and molecular changes during the course of the treatment, particularly for genes responding to IL-17A/TNF in keratinocytes. Intriguingly, baseline gene expressions in nonlesional, but not lesional, skin were the best marker of treatment response at week 12. We identified USP18, a known regulator of IFN responses, as positively correlated with Psoriasis Area and Severity Index (PASI) improvement (P = 9.8 × 10-4) and demonstrate its role in regulating IFN/TNF responses in keratinocytes. Consistently, cytokine gene signatures enriched in baseline nonlesional skin expression profiles had strong correlations with PASI improvement. Using this information, we developed a statistical model for predicting PASI75 (ie, 75% of PASI improvement) at week 12, achieving area under the receiver-operating characteristic curve value of 0.75 and up to 80% accurate PASI75 prediction among the top predicted responders. CONCLUSIONS: Our results illustrate feasibility of assessing drug response in psoriasis using nonlesional skin and implicate involvement of IFN regulators in anti-TNF responses.

Transcriptomic characterization of prurigo nodularis and the therapeutic response to nemolizumab.

BACKGROUND: Prurigo nodularis (PN) is a debilitating, difficult-to-treat, intensely pruritic, chronic inflammatory skin disease characterized by hyperkeratotic skin nodules. The pathogenesis of PN is not well understood but is believed to involve cross talk between sensory nerve fibers, immune cells, and the epidermis. It is centered around the neuroimmune cytokine IL-31, driving an intractable itch-scratch cycle. OBJECTIVE: We sought to provide a comprehensive view of the transcriptomic changes in PN skin and characterize the mechanism of action of the anti-IL-31 receptor inhibitor nemolizumab. METHOD: RNA sequencing of biopsy samples obtained from a cohort of patients treated with the anti-IL-31 receptor inhibitor nemolizumab and taken at baseline and week 12. Generation and integration of patient data with RNA-Seq data generated from reconstructed human epidermis stimulated with IL-31 and other proinflammatory cytokines. RESULTS: Our results demonstrate that nemolizumab effectively decreases IL-31 responses in PN skin, leading to effective suppression of downstream inflammatory responses including TH2/IL-13 and TH17/IL-17 responses. This is accompanied by decreased keratinocyte proliferation and normalization of epidermal differentiation and function. Furthermore, our results demonstrate how transcriptomic changes associated with nemolizumab treatment correlate with improvement in lesions, pruritus, stabilization of extracellular matrix remodeling, and processes associated with cutaneous nerve function. CONCLUSION: These data demonstrate a broad response to IL-31 receptor inhibition with nemolizumab and confirm the critical upstream role of IL-31 in PN pathogenesis.

IL18-containing 5-gene signature distinguishes histologically identical dermatomyositis and lupus erythematosus skin lesions.

Skin lesions in dermatomyositis (DM) are common, are frequently refractory, and have prognostic significance. Histologically, DM lesions appear similar to cutaneous lupus erythematosus (CLE) lesions and frequently cannot be differentiated. We thus compared the transcriptional profile of DM biopsies with CLE lesions to identify unique features. Type I IFN signaling, including IFN-κ upregulation, was a common pathway in both DM and CLE; however, CLE also exhibited other inflammatory pathways. Notably, DM lesions could be distinguished from CLE by a 5-gene biomarker panel that included IL18 upregulation. Using single-cell RNA-sequencing, we further identified keratinocytes as the main source of increased IL-18 in DM skin. This study identifies a potentially novel molecular signature, with significant clinical implications for differentiating DM from CLE lesions, and highlights the potential role for IL-18 in the pathophysiology of DM skin disease.

Integrative Approach to Reveal Cell Type Specificity and Gene Candidates for Psoriatic Arthritis Outside the MHC.

We recently conducted a large association analysis to compare the genetic profiles between patients with psoriatic arthritis (PsA) and cutaneous-only psoriasis (PsC). Despite including over 7,000 genotyped patients, only the MHC achieved genome-wide significance. In this study, we hypothesized that appropriate epigenomic elements (H3K27ac marks for active enhancers) can guide us to reveal valuable information about the loci with suggestive evidence of association. Our aim is to investigate these loci and explore how they may lead to the development of PsA. We evaluated this potential by investigating the genes connected with these loci from the perspective of pharmacogenomics and gene expression. We illustrated that markers with suggestive evidence of association outside the MHC region are enriched in H3K27ac marks for osteoblast and chondrogenic differentiated cells; using pharmacogenomics resources, we showed that genes near these markers are targeted by existing drugs used to treat psoriatic arthritis. Significantly, six of the ten suggestive significant loci overlapping the regulatory elements encompass genes differentially expressed (FDR < 5%) in differentiated osteoblasts, including genes participating in the Wnt signaling such as RUNX1, FUT8, and CTNNAL1. Our approach shows that epigenomic information can be used as cost-effective approach to enhance the inferences for GWAS results, especially in situations when few genome-wide significant loci are available. Our results also point the way to more directed investigations comparing the genetics of PsA and PsC.

Genetic signature to provide robust risk assessment of psoriatic arthritis development in psoriasis patients.

Psoriatic arthritis (PsA) is a complex chronic musculoskeletal condition that occurs in ~30% of psoriasis patients. Currently, no systematic strategy is available that utilizes the differences in genetic architecture between PsA and cutaneous-only psoriasis (PsC) to assess PsA risk before symptoms appear. Here, we introduce a computational pipeline for predicting PsA among psoriasis patients using data from six cohorts with >7000 genotyped PsA and PsC patients. We identify 9 new loci for psoriasis or its subtypes and achieve 0.82 area under the receiver operator curve in distinguishing PsA vs. PsC when using 200 genetic markers. Among the top 5% of our PsA prediction we achieve >90% precision with 100% specificity and 16% recall for predicting PsA among psoriatic patients, using conditional inference forest or shrinkage discriminant analysis. Combining statistical and machine-learning techniques, we show that the underlying genetic differences between psoriasis subtypes can be used for individualized subtype risk assessment.