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Background Secukinumab, an anti-interleukin (IL)-17A monoclonal antibody, induces histological and molecular resolution of psoriatic plaques by 12 weeks. However, the long-term effects of secukinumab on the molecular resolution of psoriatic inflammation remain unknown. Objectives To investigate the molecular resolution of psoriasis following 52 weeks of secukinumab treatment. Methods This was a two-part phase II randomized double-blinded placebo-controlled 52-week study of patients with moderate-to-severe psoriasis receiving secukinumab 300 mg (NCT01537432). Psoriatic lesional and nonlesional skin biopsies were obtained at baseline and at weeks 12 and 52, and the composition of the residual disease genomic profile (RDGP; i.e. 'molecular scar') of biopsies from secukinumab responders analysed. Results After 52 weeks of treatment, 14 of 24 enrolled patients were considered to be clinical responders [≥ 75% improvement in Psoriasis Area and Severity Index (PASI 75)], 4 of 24 were considered to be nonresponders (< PASI 75) and 6 of 24 patients were lost to follow-up; both the histological and transcriptomic profiles of PASI 75 responders improved from week 12 to week 52. RDGP transcripts of histological responders only partially overlapped between weeks 12 and 52, despite a similar number of transcripts in each RDGP; specifically, four novel transcript subsets showed distinct expression dynamics between weeks 12 and 52 ('slow-resolving', 'recurring', 'persistent' and 'resolved'), with anti-inflammatory and immunomodulatory genes (e.g. SOCS1 , CD207 and IL37) notably restored at week 52. Shorter disease duration prior to secukinumab treatment coincided with greater transcript improvements at weeks 12 and 52. Conclusions Secukinumab improves the histological and molecular phenotype of psoriatic lesional skin up to 52 weeks of treatment; these results suggest possible mechanisms that drive long-term control of psoriasis. [ABSTRACT FROM AUTHOR]

Background Secukinumab is effective against a range of psoriatic manifestations. Investigating psoriasis (PsO) relapse following secukinumab discontinuation could provide insights into long-term PsO remission. Objectives To examine PsO relapse rates on treatment discontinuation following 1 year of secukinumab treatment. Methods This study (clinical trial number: NCT01544595) is an extension of the phase III ERASURE/FIXTURE studies in patients with moderate-to-severe plaque PsO. After 1 year of secukinumab 300 mg or 150 mg treatment, participants who had responded to treatment with a ≥ 75% reduction in Psoriasis Area and Severity Index (PASI 75) at week 52 were randomly assigned to receive placebo (n = 120 and n = 100, respectively). On relapse, patients receiving placebo were switched to their previous secukinumab dose. The study primary outcome was the nonrelapse rate after secukinumab withdrawal. Results Following the last dose of secukinumab 300 mg, 20.8% (25/120) and 10.0% (12/120) of patients who switched to placebo did not relapse at 1 and 2 years after discontinuation, respectively. Patients who received secukinumab 150 mg for 1 year showed a lower proportion of nonrelapse following treatment discontinuation [14% (14/100) and 6% (6/100)] at 1 and 2 years, respectively. Patients who did not relapse maintained low mean PASI (2.8) at 1 year drug free vs. baseline (20.9); 1.7 at 2 years drug free vs. baseline (19.2), following an initial 52-week treatment with secukinumab 300 mg. Disease duration (P = 0.02) and severity (P = 0.02) were significantly associated with time to relapse in patients initially treated with secukinumab 300 mg; patients with shorter disease duration and lower baseline PASI remained relapse-free for longer. Conclusions Following discontinuation of secukinumab, a proportion of patients stayed relapse-free. Further, patients with shorter disease duration remained relapse-free for longer, suggesting that earlier treatment with secukinumab may result in long-term clinical control of moderate-to-severe PsO. [ABSTRACT FROM AUTHOR]

Rationale: Randomized controlled trials of continuous positive airway pressure (CPAP) therapy for cardiovascular disease (CVD) prevention among patients with obstructive sleep apnea (OSA) have been largely neutral. However, given that OSA is a heterogeneous disease, there may be unidentified subgroups demonstrating differential treatment effects. Objectives: We sought to apply a novel data-drive approach to identify nonsleepy OSA subgroups with heterogeneous effects of CPAP on CVD outcomes within the Impact of Sleep Apnea Syndrome in the Evolution of Acute Coronary Syndrome (ISAACC) study. Methods: Participants were randomly partitioned into two datasets. One for training (70%) our machine-learning model and a second (30%) for validation of significant findings. Model-based recursive partitioning was applied to identify subgroups with heterogeneous treatment effects. Survival analysis was conducted to compare treatment (CPAP vs. usual care [UC]) outcomes within subgroups. Results: A total of 1,224 nonsleepy OSA participants were included. Of 55 features entered into our model, only two appeared in the final model (i.e., average OSA event duration and hypercholesterolemia). Among participants at or below the model-derived average event duration threshold (19.5 s), CPAP was protective for a composite of CVD events (training hazard ratio [HR], 0.46; P = 0.002). For those with longer event duration (>19.5 s), an additional split occurred by hypercholesterolemia status. Among participants with longer event duration and hypercholesterolemia, CPAP resulted in more CVD events compared with UC (training HR, 2.24; P = 0.011). The point estimate for this harmful signal was also replicated in the testing dataset (HR, 1.83; P = 0.118). Conclusions: We discovered subgroups of nonsleepy OSA participants within the ISAACC study with heterogeneous effects of CPAP. Among the training dataset, those with longer OSA event duration and hypercholesterolemia had nearly 2.5 times more CVD events with CPAP compared with UC, whereas those with shorter OSA event duration had roughly half the rate of CVD events if randomized to CPAP. [ABSTRACT FROM AUTHOR]

Obstructive sleep apnea (OSA) affects almost a billion people worldwide and is associated with a myriad of adverse health outcomes. Among the most prevalent and morbid are cardiovascular diseases (CVDs). Nonetheless, randomized controlled trials (RCTs) of OSA treatment have failed to show improvements in CVD outcomes. A major limitation in our field is the lack of precision in defining OSA and specifically subgroups with the potential to benefit from therapy. Further, this has called into question the validity of using the time-honored apnea–hypopnea index as the ultimate defining criteria for OSA. Recent applications of advanced statistical methods and machine learning have brought to light a variety of OSA endotypes and phenotypes. These methods also provide an opportunity to understand the interaction between OSA and comorbid diseases for better CVD risk stratification. Lastly, machine learning and specifically heterogeneous treatment effects modeling can help uncover subgroups with differential outcomes after treatment initiation. In an era of data sharing and big data, these techniques will be at the forefront of OSA research. Advanced data science methods, such as machine-learning analyses and artificial intelligence, will improve our ability to determine the unique influence of OSA on CVD outcomes and ultimately allow us to better determine precision medicine approaches in OSA patients for CVD risk reduction. In this narrative review, we will highlight how team science via machine learning and artificial intelligence applied to existing clinical data, polysomnography, proteomics, and imaging can do just that. [ABSTRACT FROM AUTHOR]

Rationale: Studies have shown elevated inflammatory biomarkers in obstructive sleep apnea (OSA), but data after continuous positive airway pressure (CPAP) treatment are inconsistent. Objectives: We used the Olink proteomics panel to identify unique OSA clusters on the basis of inflammatory protein expression and assess the impact of CPAP therapy. Methods: Adults with newly diagnosed OSA had blood drawn at baseline and three to four months after CPAP. Samples were analyzed using the Olink proteomics platform, which measures 92 prespecified inflammatory proteins using proximity extension assay. Linear mixed-effects models were used to model changes in protein expression during the period of CPAP use, adjusting for batch, age, and sex. Unsupervised hierarchical clustering was performed to identify unique inflammatory OSA clusters on the basis of inflammatory biomarkers. Within-cluster impact of CPAP on inflammatory protein expression was assessed. Results: Among 46 patients, the mean age was 46 ± 12 years (22% women), mean body mass index was 31 ± 5 kg/m², and mean respiratory disturbance index was 33 ± 17 events/hour. Unsupervised cluster and heatmap analysis revealed three unique proteomic clusters, with low (n = 21), intermediate (n = 19), and high (n = 6) inflammatory protein expression. After CPAP, there were significant within-cluster differences in protein expression. The low inflammatory cluster had a significant increase in protein expression (16%; P = 0.02), and the high inflammatory cluster had a significant decrease in protein expression (220%; P = 0.003), more significant among those compliant with CPAP in the low (25%; P = 0.04) and high (222%; P = 0.01) clusters. Conclusions: We identified three unique inflammatory clusters in patients with OSA using plasma proteomics, with a differential response to CPAP by cluster. Our results are hypothesis generating and require further investigation in larger longitudinal studies for enhanced cardiovascular risk profiling in OSA. [ABSTRACT FROM AUTHOR]

Rationale: There is upper airway inflammation in patients with obstructive sleep apnea (OSA), which reduces with continuous positive airway pressure (CPAP) therapy. Objectives: Validate the use of positron emission tomography (PET)/magnetic resonance imaging (MRI) to quantify metabolic activity within the pharyngeal mucosa of patients with OSA against nasal lavage proteomics and assess the impact of CPAP therapy. Methods: Adults with OSA underwent [18F]-Fluoro-2-deoxy-Dglucose PET/MRI of the neck before and 3 months after initiating CPAP. Nasal lavage samples were collected. Inflammatory protein expression from samples was analyzed using the Olink platform. Upper airway imaging segmentation was performed. Target-tobackground ratio (TBRmax) was calculated from target pharyngeal maximum standard uptake values (SUV) and personalized background mean SUV. Most-diseased segment TBRmax was identified per participant at locations with the highest PET avidity. Correlation analysis was performed between baseline TBRmax and nasal lavage proteomics. TBRmax was compared before and after CPAP using linear mixed-effect models. Results: Among 38 participants, the baseline mean age was 46.3 years (standard deviation [SD], 12.5), 21% were female, the mean body mass index was 30.9 kg/m² (SD, 4.6), and the mean respiratory disturbance index measured by peripheral arterial tonometry was 31 events/h (SD, 16.4). There was a significant positive correlation between pharyngeal mucosa most-diseased segment TBRmax and nasal lavage proteomic inflammation (r = 0.41 [P,0.001, false discovery rate = 0.002]). Primary analysis revealed a reduction in the most-diseased segment TBRmax after a median of 2.91 months of CPAP therapy (20.86 [standard error (SE)60.30; P = 0.007]). Stratified analysis by smoking status revealed a significantly decreased most-diseased segment TBRmax after CPAP therapy among never-smokers but not among ever-smokers (21.01 [SE60.39; P = 0.015] vs. 20.64 [SE60.49; P = 0.201]). Conclusions: CPAP therapy reduces metabolic activity measured by PET/MRI within the upper airway of adults with OSA. Furthermore, PET/MRI measures of upper airway metabolic activity correlate with a noninvasive marker of inflammation (i.e., nasal lavage inflammatory protein expression). [ABSTRACT FROM AUTHOR]

Introduction: Molecular studies of hen's egg allergens help define allergic phenotypes, with IgE to sequential (linear) epitopes on the ovomucoid (OVM) protein associated with a persistent disease. Epitope profiles of other egg allergens are largely unknown. The objective of this study was to construct an epitope library spanning across 7 allergens and further evaluate sequential epitope-specific (ses-)IgE and ses-IgG4 among baked-egg reactive or tolerant children. Methods: A Bead-Based Epitope Assay was used to identify informative IgE epitopes from 15-mer overlapping peptides covering the entire OVM and ovalbumin (OVA) proteins in 38 egg allergic children. An amalgamation of 12 B-cell epitope prediction tools was developed using experimentally identified epitopes. This ensemble was used to predict epitopes from ovotransferrin, lysozyme, serum albumin, vitellogenin-II fragment, and vitellogenin-1 precursor. Ses-IgE and ses-IgG4 repertoires of 135 egg allergic children (82 reactive to baked-egg, the remaining 52 tolerant), 46 atopic controls, and 11 healthy subjects were compared. Results: 183 peptides from OVM and OVA were screened and used to create an aggregate algorithm, improving predictions of 12 individual tools. A final library of 65 sequential epitopes from 7 proteins was constructed. Egg allergic children had higher ses-IgE and lower ses-IgG4 to predominantly OVM epitopes than both atopic and healthy controls. Baked-egg reactive children had similar ses-IgG4 but greater ses-IgE than tolerant group. A combination of OVA-sIgE with ses-IgEs to OVM-023 and OVA-028 was the best predictor of reactive phenotype. Conclusion: We have created a comprehensive epitope library and showed that ses-IgE is a potential biomarker of baked-egg reactivity. [ABSTRACT FROM AUTHOR]

Background: Accurate diagnosis of peanut allergy is a significant clinical challenge. Here, a novel diagnostic blood test using the peanut bead‐based epitope assay ("peanut BBEA") was developed utilizing the LEAP cohort and then validated using two independent cohorts. Methods: The development of the peanut BBEA diagnostic test followed the National Academy of Medicine's established guidelines with discovery performed on 133 subjects from the non‐interventional arm of the LEAP trial and an independent validation performed on 82 subjects from the CoFAR2 and 84 subjects from the POISED study. All samples were analyzed using the peanut BBEA methodology, which measures levels of IgE to two Ara h 2 sequential (linear) epitopes and compares their combination to a threshold pre‐specified in the model development phase. When a patient has an inconclusive outcome by skin prick testing (or sIgE), IgE antibody levels to this combination of two epitopes can distinguish whether the patient is "Allergic" or "Not Allergic." Diagnoses of peanut allergy in all subjects were confirmed by double‐blind placebo‐controlled food challenge and subjects' ages were 7–55 years. Results: In the validation using CoFAR2 and POISED cohorts, the peanut BBEA diagnostic test correctly diagnosed 93% of the subjects, with a sensitivity of 92%, specificity of 94%, a positive predictive value of 91%, and negative predictive value of 95%. Conclusions: In validation of the peanut BBEA diagnostic test, the overall accuracy was found to be superior to existing diagnostic tests for peanut allergy including skin prick testing, peanut sIgE, and peanut component sIgE testing. [ABSTRACT FROM AUTHOR]

Background: Wearable devices enable monitoring and measurement of physiological parameters over a 24-h period, and some of which exhibit circadian rhythm characteristics. However, the currently available R package cosinor could only analyze daily cross-sectional data and compare the parameters between groups with two levels. To evaluate longitudinal changes in the circadian patterns, we need to extend the model to a mixed-effect model framework, allowing for random effects and interaction between COSINOR parameters and time-varying covariates. Results: We developed the cosinoRmixedeffects R package for modelling longitudinal periodic data using mixed-effects cosinor models. The model allows for covariates and interactions with the non-linear parameters MESOR, amplitude, and acrophase. To facilitate ease of use, the package utilizes the syntax and functions of the widely used emmeans package to obtain estimated marginal means and contrasts. Estimation and hypothesis testing involving the non-linear circadian parameters are carried out using bootstrapping. We illustrate the package functionality by modelling daily measurements of heart rate variability (HRV) collected among health care workers over several months. Differences in circadian patterns of HRV between genders, BMI, and during infection with SARS-CoV2 are evaluated to illustrate how to perform hypothesis testing. Conclusion: cosinoRmixedeffects package provides the model fitting, estimation and hypothesis testing for the mixed-effects COSINOR model, for the linear and non-linear circadian parameters MESOR, amplitude and acrophase. The model accommodates factors with any number of categories, as well as complex interactions with circadian parameters and categorical factors. [ABSTRACT FROM AUTHOR]

Background: Egg‐white ovomucoid, that is, Gal d 1, is associated with IgE‐mediated allergic reactions in most egg‐allergic children. Epitope‐specific IgE levels have been correlated with the severity of egg allergy, while emerging evidence suggests that other antibody isotypes (IgG1, IgG4, IgA, and IgD) may have a protective function; yet, their epitope‐specific repertoires and associations with atopic comorbidities have not been studied. Methods: Bead‐based epitope assay (BBEA) was used to quantitate the levels of epitope‐specific (es)IgA, esIgE, esIgD, esIgG1, and esIgG4 antibodies directed at 58 (15‐mer) overlapping peptides, covering the entire sequence of ovomucoid, in plasma of 38 egg‐allergic and 6 atopic children. Intraclass correlation (ICC) and coefficient of variation (CV) were used for the reliability assessment. The relationships across esIgs were evaluated using network analysis; linear and logistic regressions were used to compare groups based on egg allergy status and comorbidities. Results: BBEA had high reliability (ICC >0.75) and low variability (CV <20%) and could detect known IgE‐binding epitopes. Egg‐allergic children had lower esIgA1 (P =.010) and esIgG1 (P =.016) and higher esIgE (P <.001) and esIgD (P =.015) levels compared to the atopic controls. Interestingly, within the allergic group, children with higher esIgD had decreased odds of anaphylactic reactions (OR =0.48, P =.038). Network analysis identified most associations between esIgE with either esIgG4 or esIgD; indicating that IgE‐secreting plasma cells could originate from either sequential isotype switch from antigen‐experienced intermediate isotypes or directly from the IgD+ B cells. Conclusions: Collectively, these data point toward a contribution of epitope‐specific antibody repertoires to the pathogenesis of egg allergy. [ABSTRACT FROM AUTHOR]

A comparative study of releasing and nonreleasing human basophils: nonreleasing basophils lack an early component of the signal transduction pathway that follows IgE cross-linking. GLO:1X5/01jul21:all14752-fig-0002.jpg PHOTO (COLOR): 2 Diversity of peanut epitopes IgE expressed in allergic patients is proportional to their sensitivity to basophil activation. Since IgE diversity likely results in greater basophil activation due to increased cross-linking of the high-affinity Fc RI receptors,8 we examined P-BAT association with the Ara h 1, Ara h 2 and Ara h 3 epitope sIgE. [Extracted from the article]

Background: The majority of children with cow's milk allergy (CMA) tolerate baked milk. However, reactivity to fermented milk products such as yogurt/cheese has not been previously evaluated. We sought to determine whether children with CMA could tolerate yogurt/cheese and whether a patient's IgE and IgG4‐binding pattern to milk protein epitopes could distinguish clinical reactivity. Methods: Four groups of reactivity were identified by Oral food challenge: baked milk reactive, fermented milk reactive, whole milk reactive, and outgrown. sIgE and sIgG4 binding to milk protein epitopes were assessed with a novel Luminex‐based peptide assay (LPA). Using machine learning techniques, a model was developed to predict different degrees of CMA. Results: The baked milk reactive patients demonstrated the highest degree of IgE epitope binding, which was followed sequentially by fermented milk reactive, whole milk reactive, and outgrown. Data were randomly divided into two groups with 75% of the data utilized for model development (n = 68) and 25% for testing (n = 21). All 68 children used for training were correctly classified with models using IgE and IgG4 epitopes. The average cross‐validation accuracy was much higher for models using IgE plus IgG4 epitopes by LPA (84.8%), twice the performance of the serum component proteins assayed by UniCAP (41.9%). The performance of the model on "unseen data" was tested using the 21 withheld patients, and the accuracy of IgE was 86% (AUC = 0.89) while of IgE+IgG4 model was 81% (AUC = 0.94). Conclusion: Using a novel high‐throughput LPA, we were able to distinguish the diversity of IgE/IgG4 binding to epitopes in the varying CMA phenotypes. LPA is a promising tool to predict correctly different degrees of CMA. The new food challenge sequence and Luminex‐based peptide assay to identify the clinical phenotypes of reactivity to baked, fermented, and whole cow's milk. [ABSTRACT FROM AUTHOR]

Summary Analysis of epitope-specific antibody repertoires has provided novel insights into the pathogenesis of inflammatory disorders, especially allergies. A novel multiplex immunoassay, termed Bead-Based Epitope Assay (BBEA), was developed to quantify levels of epitope-specific immunoglobulins, including IgE, IgG, IgA and IgD isotypes. bbeaR is an open-source R package, developed for the BBEA, provides a framework to import, process and normalize.csv data files exported from the Luminex reader, evaluate various quality control metrics, analyze differential epitope-binding antibodies with linear modeling, visualize results and map epitopes' amino acid sequences to their respective primary protein structures. bbeaR enables streamlined and reproducible analysis of epitope-specific antibody profiles. Availability and implementation bbeaR is open-source and freely available from GitHub as an R package: https://github.com/msuprun/bbeaR ; vignettes included. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Hidradenitis suppurativa (HS) is a chronic skin disease of the pilo-sebaceous apocrine unit characterized by significant inflammation and an impaired quality of life. The pathogenesis of HS remains unclear. To determine the HS skin and blood transcriptomes and HS blood proteome, patient data from previously published studies were analysed and integrated from a cohort of patients with moderate to severe HS (n = 17) compared to healthy volunteers (n = 10). The analysis utilized empirical Bayes methods to determine differentially expressed genes (DEGs) (fold change (FCH) >2.0 and false discovery rate (FDR) <0.05), and differentially expressed proteins (DEPs) (FCH>1.5, FDR<0.05). In the HS skin transcriptome (lesional skin compared to non-lesional skin), there was an abundance of immunoglobulins, antimicrobial peptides, and an interferon signature. Gene-sets related to Notch signalling and Interferon pathways were differentially activated in lesional compared to non-lesional skin. CIBERSORT analysis of the HS skin transcriptome revealed a significantly increased proportion of plasma cells in lesional skin. In the HS skin and blood transcriptomes and HS blood proteome, gene-sets related to the complement system changed significantly (FDR<0.05), with dysregulation of complement-specific DEGs and DEPs. These data point towards an exaggerated immune response in lesional skin that may be responding to commensal cutaneous bacterial presence and raise the possibility that this may be an important driver of HS disease progression. [ABSTRACT FROM AUTHOR]

Keloids are benign fibroproliferative tumors more frequently found among African Americans. Until now, keloid etiopathogenesis is not fully understood. To characterize keloids in African Americans, we performed transcriptional profiling of biopsies from large chronic keloids, adjacent non-lesional (NL) skin (n=3) and a newly formed keloid lesion using Affymetrix HGU133 2.0 plus arrays. Quantitative RT-PCR (qRT-PCR) and immunohistochemistry (IHC) staining were performed to confirm increased expression of relevant genes. We identified 1202 upregulated and 961 downregulated differentially expressed genes (DEGs) between keloid and NL skin; 1819 up- and 1867 downregulated DEGs between newly formed keloid and NL skin; and 492 up- and 775 downregulated DEGs between chronic and newly formed keloid (fold change >2, false discovery rate <0.05). Many of the top upregulated DEGs between chronic keloid and NL skin and between newly formed keloid and NL skin are involved in bone/cartilage formation including Fibrillin 2 (FBN2), Collagen type X alpha 1, Asporin (ASPN), Cadherin 11 (CDH11), Bone morphogenic protein 1 (BMP1), Secreted phosphoprotein 1 and Runt-related transcription factor 2 (RUNX2). qRT-PCR confirmed significant ( P<.05) upregulation of BMP1, RUNX2, CDH11 and FBN2 in chronic keloid compared to NL skin. IHC staining showed increased protein expression of ASPN, CDH11, BMP1 and RUNX2 on chronic and newly formed keloid compared to NL skin. Our study shows that large keloids in African Americans represent a dysplasia of cutaneous connective tissue towards immature cartilage or bone differentiation. The phenotype is potentially regulated by overexpression of RUNX2. This knowledge may give insights to guide the development of better treatment for the disease in the future. [ABSTRACT FROM AUTHOR]

We developed an automated approach for generating quantitative image analysis metrics (imaging biomarkers) that are then analysed with a set of 13 machine learning algorithms to generate an overall risk score that is called a Q-score. These methods were applied to a set of 120 'difficult' dermoscopy images of dysplastic nevi and melanomas that were subsequently excised/classified. This approach yielded 98% sensitivity and 36% specificity for melanoma detection, approaching sensitivity/specificity of expert lesion evaluation. Importantly, we found strong spectral dependence of many imaging biomarkers in blue or red colour channels, suggesting the need to optimize spectral evaluation of pigmented lesions. [ABSTRACT FROM AUTHOR]

The article discusses lacking of therapeutic strategies for food allergens (FA) and patch testing for food allergens. Topics discussed include FA inviolving IgE-mediated and T-cell mediated delayed-type hypersensitivity, 12 patients having positive food patch tests (FPT) in the test, and using microarrays to compare gene expression induction by FPT.

Atopic dermatitis ( AD) is the most common inflammatory skin disease, but treatment options for moderate-to-severe disease are limited. Ustekinumab is an IL-12/ IL-23p40 antagonist that suppresses Th1, Th17 and Th22 activation, commonly used for psoriasis patients. We sought to assess efficacy and safety of ustekinumab in patients with moderate-to-severe AD. In this phase II, double-blind, placebo-controlled study, 33 patients with moderate-to-severe AD were randomly assigned to either ustekinumab (n=16) or placebo (n=17), with subsequent crossover at 16 weeks, and last dose at 32 weeks. Background therapy with mild topical steroids was allowed to promote retention. Study endpoints included clinical ( SCORAD50) and biopsy-based measures of tissue structure and inflammation, using protein and gene expression studies. The ustekinumab group achieved higher SCORAD50 responses at 12, 16 (the primary endpoint) and 20 weeks compared to placebo, but the difference between groups was not significant. The AD molecular profile/transcriptome showed early robust gene modulation, with sustained further improvements until 32 weeks in the initial ustekinumab group. Distinct and more robust modulation of Th1, Th17 and Th22 but also Th2-related AD genes was seen after 4 weeks of ustekinumab treatment (i.e. MMP12, IL-22, IL-13, IFN-γ, elafin/ PI3, CXCL1 and CCL17; P<.05). Epidermal responses ( K16, terminal differentiation) showed faster (4 weeks) and long-term regulation (32 weeks) from baseline in the ustekinumab group. No severe adverse events were observed. Ustekinumab had clear clinical and molecular effects, but clinical outcomes might have been obscured by a profound 'placebo' effect, most likely due to background topical glucocorticosteroids and possibly insufficient dosing for AD. [ABSTRACT FROM AUTHOR]

Summary In biological assays, systematic variability, known as a batch effect, can often confound the effects of true biological conditions and has been well documented for a variety of high-throughput technologies. In microplate-based multiplex experiments, such as Luminex or OLINK assays, researchers need to consider both position and plate effects. Those effects can be easily accounted for if the experiments are properly designed, which includes randomization of the samples across multiple experimental runs. However, doing the ad hoc randomization becomes challenging when handling multiple samples. PlateDesigner is the first web-based application that provides randomization for microplate experiments, ensuring that the main principles of the experimental design, such as grouping samples from the same biological units and balancing the distribution of experimental conditions, are applied. Creating randomizations with PlateDesigner is simple and the results can be exported in a variety of formats, and easily integrated with microplate readers and statistical analysis software. Availability and implementation PlateDesigner is written in R/Shiny and is hosted online by the Center of Biostatistics at the Icahn School of Medicine at Mount Sinai. This application is freely available at platedesigner.net. [ABSTRACT FROM AUTHOR]

Introduction: There is a controversy surrounding the existence of palmoplantar pustulosis (PPP) and palmoplantar pustular psoriasis (PPPP) as separate clinical entities or as variants of the same clinical entity. We used gene expression microarray to compare gene expression in PPP and PPPP. Methodology/Principal findings: Skin biopsies from subjects with PPP (3), PPPP (6), psoriasis vulgaris (10) and acral skin from normal subjects (7) were analyzed using gene expression microarray. Principal component analysis showed that PPP and PPPP were different from psoriasis vulgaris and normal acral skin. However gene expression of PPP and PPPP clustered together and could not be used to differentiate PPP from PPPP. Gene-wise comparison between PPP and PPPP found no gene to be differentially expressed at a false discovery rate lower than 0.05. Surprisingly we found a higher expression of several genes involved in neural pathways (e.g. GPRIN and ADAM23) in PPP/PPPP as compared to psoriasis vulgaris and normal acral skin. Immunohistochemistry confirmed those findings and showed a keratinocyte localization for those proteins. Conclusion significance: PPP and PPPP could not be differentiated using gene expression microarray suggesting that they are not distinct clinical entities. Increased expression of GPRIN1, and ADAM23 in keratinocytes suggests that these proteins could be new therapeutic targets for PPP/PPPP. [ABSTRACT FROM AUTHOR]

Alopecia areata ( AA) is a common inflammatory disease targeting the anagen-stage hair follicle. Different cytokines have been implicated in the disease profile, but their pathogenic role is not yet fully determined. We studied biopsies of pretreatment lesional and non-lesional ( NL) scalp and post-treatment (intra-lesional steroid injection) lesional scalp of 6 patchy patients with AA using immunohistochemistry and gene expression analysis. Immunohistochemistry showed increases in CD3+, CD8+ T cells, CD11c+ dendritic cells and CD1a+ Langerhans cells within and around hair follicles of pretreatment lesional scalp, which decreased upon treatment. qRT- PCR showed in pretreatment lesional scalp (compared to NL) significant increases ( P < 0.05) in expression of inflammatory markers ( IL-2, IL-2 RA, JAK3, IL-15), Th1 ( CXCL10 and CXCL9), Th2 ( IL-13, CCL17 and CCL18), IL-12/ IL-23p40 and IL-32. Among these, we observed significant downregulation with treatment in IL-12/ IL-23p40, CCL18 and IL-32. We also observed significant downregulation of several hair keratins in lesional scalp, with significant upregulation of KRT35, KRT75 and KRT86 in post-treatment lesional scalp. This study shows concurrent activation of Th1 and Th2 immune axes as well as IL-23 and IL-32 cytokine pathways in lesional AA scalp and defined a series of response biomarkers to corticosteroid injection. Clinical trials with selective antagonists coupled with cytokine-pathway biomarkers will be necessary to further dissect pathogenic immunity. [ABSTRACT FROM AUTHOR]

Scalp psoriasis shows a variable clinical spectrum and in many cases poses a great therapeutic challenge. However, it remains unknown whether the immune response of scalp psoriasis differs from understood pathomechanisms of psoriasis in other skin areas. We sought to determine the cellular and molecular phenotype of scalp psoriasis by performing a comparative analysis of scalp and skin using lesional and nonlesional samples from 20 Caucasian subjects with untreated moderate to severe psoriasis and significant scalp involvement and 10 control subjects without psoriasis. Our results suggest that even in the scalp, psoriasis is a disease of the inter-follicular skin. The immune mechanisms that mediate scalp psoriasis were found to be similar to those involved in skin psoriasis. However, the magnitude of dysregulation, number of differentially expressed genes, and enrichment of the psoriatic genomic fingerprint were more prominent in skin lesions. Furthermore, the scalp transcriptome showed increased modulation of several gene-sets, particularly those induced by interferon-gamma, compared with that of skin psoriasis, which was mainly associated with activation of TNFα/L-17/IL-22-induced keratinocyte response genes. We also detected differences in expression of gene-sets involving negative regulation, epigenetic regulation, epidermal differentiation, and dendritic cell or Th1/Th17/Th22-related T-cell processes. [ABSTRACT FROM AUTHOR]

Activation of Sirtuin (silent mating type information regulation 2 homolog) 1, or SIRT1, is an unexplored therapeutic approach for treatment of inflammatory diseases. We randomized 40 patients with moderate-to-severe psoriasis (4:1) to three escalating doses of SRT2104, a selective activator of SIRT1, or placebo. Across all SRT2104 groups, 35% of patients (p<0.0001) achieved good to excellent histological improvement based on skin biopsies taken at baseline and day 84 but was not consistently in agreement with PASI. Improvement in histology was associated with modulation of IL-17 and TNF-α signaling pathways and keratinocyte differentiation target genes. 27 subjects (69%) across all treatment groups, including placebo, experienced at least one treatment emergent adverse event. The majority of AEs were either mild or moderate. Most common were headache (8%), dizziness (8%), upper respiratory tract infection (8%), and psoriatic arthropathy (8%). Average drug exposure increased in a dose-dependent manner for escalating doses of SRT2104 and had high intra-subject variability in exposure (AUC %CV: 51–89%). Given the interesting signals of clinical activity, impact on gene expression and the generally favorable safety profile seen in this study, further investigation of SIRT1 activators for the treatment of psoriasis is warranted. Trial Registration: Clinicaltrials.gov [ABSTRACT FROM AUTHOR]

Background: Atopic dermatitis (AD) is a common inflammatory skin disease with limited treatment options. Several microarray experiments have been conducted on lesional/LS and non-lesional/NL AD skin to develop a genomic disease phenotype. Although these experiments have shed light on disease pathology, inter-study comparisons reveal large differences in resulting sets of differentially expressed genes (DEGs), limiting the utility of direct comparisons across studies. Methods: We carried out a meta-analysis combining 4 published AD datasets to define a robust disease profile, termed meta-analysis derived AD (MADAD) transcriptome. Results: This transcriptome enriches key AD pathways more than the individual studies, and associates AD with novel pathways, such as atherosclerosis signaling (IL-37, selectin E/SELE). We identified wide lipid abnormalities and, for the first time in vivo, correlated Th2 immune activation with downregulation of key epidermal lipids (FA2H, FAR2, ELOVL3), emphasizing the role of cytokines on the barrier disruption in AD. Key AD "classifier genes" discriminate lesional from nonlesional skin, and may evaluate therapeutic responses. Conclusions: Our meta-analysis provides novel and powerful insights into AD disease pathology, and reinforces the concept of AD as a systemic disease. [ABSTRACT FROM AUTHOR]

Psoriasis, which presents as red, scaly patches on the body, is a common, autoimmune skin disease that affects 2 to 3 percent of the world population. To leverage recent molecular findings into the personalized treatment of psoriasis, we need a strategy that integrates clinical stratification with molecular phenotyping. In this study, we sought to stratify psoriasis patients by histological measurements of epidermal thickness, and to compare their molecular characterizations by gene expression, serum cytokines, and response to biologics. We obtained histological measures of epidermal thickness in a cohort of 609 psoriasis patients, and identified a mixture of two subpopulations—thick and thin plaque psoriasis—from which they were derived. This stratification was verified in a subcohort of 65 patients from a previously published study with significant differences in inflammatory cell infiltrates in the psoriatic skin. Thick and thin plaque psoriasis shared 84.8% of the meta-analysis-derived psoriasis transcriptome, but a stronger dysregulation of the meta-analysis-derived psoriasis transcriptome was seen in thick plaque psoriasis on microarray. RT-PCR revealed that gene expression in thick and thin plaque psoriasis was different not only within psoriatic lesional skin but also in peripheral non-lesional skin. Additionally, differences in circulating cytokines and their changes in response to biologic treatments were found between the two subgroups. All together, we were able to integrate histological stratification with molecular phenotyping as a way of exploring clinical phenotypes with different expression levels of the psoriasis transcriptome and circulating cytokines. [ABSTRACT FROM AUTHOR]

Objective To our knowledge, there is no broad genomic analysis comparing skin and synovium in psoriatic arthritis (PsA). Also, there is little understanding of the relative levels of cytokines and chemokines in skin and synovium. The purpose of this study was to better define inflammatory pathways in paired lesional skin and affected synovial tissue in patients with PsA. Methods We conducted a comprehensive analysis of cytokine and chemokine activation and genes representative of the inflammatory processes in PsA. Paired PsA synovial tissue and skin samples were obtained from 12 patients on the same day. Gene expression studies were performed using Affymetrix HGU133 Plus 2.0 arrays. Confirmatory quantitative real-time polymerase chain reaction (PCR) was performed on selected transcripts. Cell populations were assessed by immunohistochemistry and immunofluorescence. Results Globally, gene expression in PsA synovium was more closely related to gene expression in PsA skin than to gene expression in synovium in other forms of arthritis. However, PsA gene expression patterns in skin and synovium were clearly distinct, showing a stronger interleukin-17 (IL-17) gene signature in skin than in synovium and more equivalent tumor necrosis factor (TNF) and interferon-γ gene signatures in both tissues. These results were confirmed with real-time PCR. Conclusion This is the first comprehensive molecular comparison of paired lesional skin and affected synovial tissue samples in PsA. Our results support clinical trial data showing that PsA skin and joint disease are similarly responsive to TNF antagonists, while IL-17 antagonists have better results in PsA skin than in PsA joints. Genes selectively expressed in PsA synovium might direct future therapies for PsA. [ABSTRACT FROM AUTHOR]

The article discuss a study on in vitro alteration of gene expression of epidermal melanocytes by dendritic cells (DCs) of melanocytic nevus. It mentions the hematoxylin and eosin staining of nevus cells followed by immunohistiochemistry of several immune cell markers. It mentions the correlation of DCs and melanocytic cells and infers that the senescence-associated nevus cell phenotype supposedly affects the DCs within the nevus nest.

Mutations in the caspase recruitment domain, family member 14 (CARD14) gene have recently been described in psoriasis patients, and explain the psoriasis susceptibility locus 2 (PSORS2). CARD14 is a scaffolding protein that regulates NF-κB activation, and psoriasis-associated CARD14 mutations lead to enhanced NF-κB signaling. CARD14 is expressed mainly in epidermal keratinocytes, but also in unidentified dermal cells. In this manuscript, the identity of the dermal cell types expressing CARD14, as well the potential functional consequence of overactive CARD14 in these dermal cell types, was determined. Using two-color immunofluorescence, dermal CARD14 did not co-localize with T-cells, dendritic cells, or macrophages. However, dermal CARD14 did highly co-localize with CD31+ endothelial cells (ECs). CARD14 was also expressed non-dermal endothelial cells, such as aortic endothelial cells, which may indicate a role of CARD14+ECs in the systemic inflammation and cardiovascular comorbidities associated with psoriasis. Additionally, phosphorylated NF-κB was found in psoriatic CARD14+ CD31+ ECs, demonstrating this pathway is active in dermal ECs in psoriasis. Transfection of dermal ECs with psoriasis-associated CARD14 mutations resulted in increased expression of several chemokines, including CXCL10, IL-8, and CCL2. These results provide preliminary evidence that CARD14 expression in ECs may contribute to psoriasis through increased expression of chemokines and facilitating recruitment of immune cells into skin. [ABSTRACT FROM AUTHOR]

BMC Bioinformatics (2021) 22:553 https://doi.org/10.1186/s12859-021... Following the publication of the original article [[1]], the authors would like to correct the sentence under the heading B Implementation b . The original article can be found online at https://doi.org/10.1186/s12859-021-04463-3. The sentences currently reads: Fit a linear mixed-effect model by reweighted least squares; The sentences should read: Fit a linear mixed-effect model by restricted maximum likelihood; The original article [[1]] has been corrected. [Extracted from the article]

The skin is the front line of defense against insult and injury and contains many epidermal and immune elements that comprise the skin-associated lymphoid tissue (SALT). The reaction of these components to injury allows an effective cutaneous response to restore homeostasis. Psoriasis vulgaris is the best-understood and most accessible human disease that is mediated by T cells and dendritic cells. Inflammatory myeloid dendritic cells release IL-23 and IL-12 to activate IL-17-producing T cells, Th1 cells, and Th22 cells to produce abundant psoriatic cytokines IL-17, IFN-γ, TNF, and IL-22. These cytokines mediate effects on keratinocytes to amplify psoriatic inflammation. Therapeutic studies with anticytokine antibodies have shown the importance of the key cytokines IL-23, TNF, and IL-17 in this process. We discuss the genetic background of psoriasis and its relationship to immune function, specifically genetic mutations, key PSORS loci, single nucleotide polymorphisms, and the skin transcriptome. The association between comorbidities and psoriasis is reviewed by correlating the skin transcriptome and serum proteins. Psoriasis-related cytokine-response pathways are considered in the context of the transcriptome of different mouse models. This approach offers a model for other inflammatory skin and autoimmune diseases. [ABSTRACT FROM AUTHOR]

Background: IL-17 is the defining cytokine of the Th17, Tc17, and γδ T cell populations that plays a critical role in mediating inflammation and autoimmunity. Psoriasis vulgaris is an inflammatory skin disease mediated by Th1 and Th17 cytokines with relevant contributions of IFN-γ, TNF-α, and IL-17. Despite the pivotal role IL-17 plays in psoriasis, and in contrast to the other key mediators involved in the psoriasis cytokine cascade that are capable of inducing broad effects on keratinocytes, IL-17 was demonstrated to regulate the expression of a limited number of genes in monolayer keratinocytes cultured in vitro. Methodology/Principal Findings: Given the clinical efficacy of anti-IL-17 agents is associated with an impressive reduction in a large set of inflammatory genes, we sought a full-thickness skin model that more closely resemble in vivo epidermal architecture. Using a reconstructed human epidermis (RHE), IL-17 was able to upregulate 419 gene probes and downregulate 216 gene probes. As possible explanation for the increased gene induction in the RHE model is that C/CAAT-enhancer-binding proteins (C/EBP) -β, the transcription factor regulating IL-17-responsive genes, is expressed preferentially in differentiated keratinocytes. Conclusions/Significance: The genes identified in IL-17-treated RHE are likely relevant to the IL-17 effects in psoriasis, since ixekizumab (anti-IL-17A agent) strongly suppressed the “RHE” genes in psoriasis patients treated in vivo with this IL-17 antagonist. [ABSTRACT FROM AUTHOR]

Background: As microarray technology has become mature and popular, the selection and use of a small number of relevant genes for accurate classification of samples has arisen as a hot topic in the circles of biostatistics and bioinformatics. However, most of the developed algorithms lack the ability to handle multiple classes, arguably a common application. Here, we propose an extension to an existing regularization algorithm, called Threshold Gradient Descent Regularization (TGDR), to specifically tackle multi-class classification of microarray data. When there are several microarray experiments addressing the same/similar objectives, one option is to use a meta-analysis version of TGDR (Meta-TGDR), which considers the classification task as a combination of classifiers with the same structure/model while allowing the parameters to vary across studies. However, the original Meta-TGDR extension did not offer a solution to the prediction on independent samples. Here, we propose an explicit method to estimate the overall coefficients of the biomarkers selected by Meta-TGDR. This extension permits broader applicability and allows a comparison between the predictive performance of Meta-TGDR and TGDR using an independent testing set. Results: Using real-world applications, we demonstrated the proposed multi-TGDR framework works well and the number of selected genes is less than the sum of all individualized binary TGDRs. Additionally, Meta-TGDR and TGDR on the batch-effect adjusted pooled data approximately provided same results. By adding Bagging procedure in each application, the stability and good predictive performance are warranted. Conclusions: Compared with Meta-TGDR, TGDR is less computing time intensive, and requires no samples of all classes in each study. On the adjusted data, it has approximate same predictive performance with Meta-TGDR. Thus, it is highly recommended. [ABSTRACT FROM AUTHOR]

Immune suppressed organ transplant recipients suffer increased morbidity and mortality from primary cutaneous SCC. We studied tumor microenvironment in transplant-associated SCC (TSCC), immune-competent SCC and normal skin by IHC, IF and RT-PCR on surgical discard. We determined T cell polarization in TSCC and SCC by intracellular cytokine staining of T cell crawl outs from human skin explants. We studied the effects of IL-22, an inducer of keratinocyte proliferation, on SCC proliferation in vitro. SCC and TSCC are both associated with significantly higher numbers of CD3+ and CD8+ T cells compared to normal skin. TSCC showed a higher proportion of Foxp3+ T regs to CD8+ T cells compared to SCC and a lower percentage of IFN-γ producing CD4+ T cells. TSCC, however, had a higher percentage of IL-22 producing CD8+ T cells compared to SCC. TSCC showed more diffuse Ki67 and IL-22 receptor (IL-22R) expression by IHC. IL-22 induced SCC proliferation in vitro despite serum starvation. Diminished cytotoxic T cell function in TSCC due to decreased CD8/T-reg ratio may permit tumor progression. Increased IL-22 and IL-22R expression could accelerate tumor growth in transplant patients. IL-22 may be an attractive candidate for targeted therapy of SCC without endangering allograft survival. [ABSTRACT FROM AUTHOR]

The autoinflammatory disorder, Neonatal-onset Multisystem Inflammatory Disease (NOMID) is the most severe phenotype of disorders caused by mutations in CIAS1 that result in increased production and secretion of active IL-1β. NOMID patients present with systemic and organ-specific inflammation of the skin, central nervous system and bone, and respond dramatically to treatment with IL-1 blocking agents. We compared the cellular infiltrates and transcriptome of skin biopsies from patients with NOMID (n = 14) before treatment (lesional (LS) and non-lesional (pre-NL) skin) and after treatment (post-NL) with the IL-1 blocker anakinra (recombinant IL-1 receptor antagonist, Kineret®, Swedish Orphan Biovitrum AB, SOBI), to normal skin (n = 5) to assess tissue responses in the context of untreated and treated disease. Abundant neutrophils distinguish LS skin from pre-NL and post-NL skin. CD11c+ dermal dendritic cells and CD163+ macrophages expressed activated caspase-1 and are a likely source of cutaneous IL-1 production. Treatment with anakinra led to the disappearance of neutrophils, but CD3+ T cells and HLA-DR+ cells remained elevated. Among the upregulated genes IL-6, IL-8, TNF, IL-17A, CCL20, and the neutrophil defensins DEFA1 and DEFA3 were differentially regulated in LS tissues (compared to normal skin). Important significantly downregulated pathways in LS skin included IL-1 R/TLR signaling, type I and II cytokine receptor signaling, mitochondrial dysfunction, and antigen presentation. The differential expression and regulation of microRNAs and pathways involved in post-transcriptional modification were suggestive of epigenetic modification in the chronically inflamed tissue. Overall, the dysregulated genes and pathways suggest extensive "adaptive" mechanisms to control inflammation and maintain tissue homeostasis, likely triggered by chronic IL-1 release in the skin of patients with NOMID. [ABSTRACT FROM AUTHOR]

The cause of psoriasis, a common chronic inflammatory skin disease, is not fully understood. Microarray experiments have been widely used in recent years to identify genes associated with psoriasis pathology, by comparing expression levels of lesional (LS) with adjacent non-lesional (NL) skin. It is commonly observed that the differentially expressed genes (DEGs) differ greatly across experiments, due to variations introduced in the microarray experiment pipeline. Therefore, a statistically based meta-analytic approach, which combines the results of individual studies, is warranted. In this study, a meta-analysis was conducted on 5 microarray data sets, including 193 LS and NL pairs. We termed this the Meta-Analysis Derived (MAD) transcriptome. In "MAD-5'' transcriptome, 677 genes were up-regulated and 443 were down-regulated in LS skin compared to NL skin. This represents a much larger set than the intersection of DEGs of these 5 studies, which consisted of 100 DEGs. We also analyzed 3 of the studies conducted on the Affymetrix hgu133plus2 chips and found a greater number of DEGs (1084 up- and 748 down-regulated). Top canonical pathways over-represented in the MAD transcriptome include Atherosclerosis Signaling and Fatty Acid Metabolism, while several ''new'' genes identified are involved in Cardiovascular Development and Lipid Metabolism. These findings highlight the relationship between psoriasis and systemic manifestations such as the metabolic syndrome and cardiovascular disease. Then, the Meta Threshold Gradient Descent Regularization (MTGDR) algorithm was used to select potential markers distinguishing LS and NL skin. The resulting set (20 genes) contained many genes that were part of the residual disease genomic profile (RDGP) or ''molecular scar''after successful treatment, and also genes subject to differential methylation in LS tissues. To conclude, this MAD transcriptome yielded a reference list of reliable psoriasis DEGs, and represents a robust pool of candidates for further discovery of pathogenesis and treatment evaluation. [ABSTRACT FROM AUTHOR]

To understand the development of new psoriasis lesions, we studied a group of moderate-to-severe psoriasis patients who experienced a relapse after ceasing efalizumab (anti-CD11a, Raptiva, Genentech). There were increased CD3+ T cells, neutrophils, CD11c+ and CD83+ myeloid dendritic cells (DCs), but no increase in CD1c+ resident myeloid DCs. In relapsed lesions, there were many CD11c+CD1c-, inflammatory myeloid DCs identified by TNFSF10/TRAIL, TNF, and iNOS. CD11c+ cells in relapsed lesions co-expressed CD14 and CD16 in situ. Efalizumab induced an improvement in many psoriasis genes, and during relapse, the majority of these genes reversed back to a lesional state. Gene Set Enrichment Analysis (GSEA) of the transcriptome of relapsed tissue showed that many of the gene sets known to be present in psoriasis were also highly enriched in relapse. Hence, on ceasing efalizumab, T cells and myeloid cells rapidly enter the skin to cause classic psoriasis. [ABSTRACT FROM AUTHOR]

Background: Studies of patients with paraneoplastic neurologic disorders (PND) have revealed that apoptotic tumor serves as a potential potent trigger for the initiation of naturally occurring tumor immunity. The purpose of this study was to assess the feasibility, safety, and immunogenicity of an apoptotic tumor-autologous dendritic cell (DC) vaccine. Methods and Findings: We have modeled PND tumor immunity in a clinical trial in which apoptotic allogeneic prostate tumor cells were used to generate an apoptotic tumor-autologous dendritic cell vaccine. Twenty-four prostate cancer patients were immunized in a Phase I, randomized, single-blind, placebo-controlled study to assess the safety and immunogenicity of this vaccine. Vaccinations were safe and well tolerated. Importantly, we also found that the vaccine was immunogenic, inducing delayed type hypersensitivity (DTH) responses and CD4+ and CD8+ T cell proliferation, with no effect on FoxP3+ regulatory T cells. A statistically significant increase in T cell proliferation responses to prostate tumor cells in vitro (p = 0.002), decrease in prostate specific antigen (PSA) slope (p = 0.016), and a two-fold increase in PSA doubling time (p = 0.003) were identified when we compared data before and after vaccination. Conclusions: An apoptotic cancer cell vaccine modeled on naturally occurring tumor immune responses in PND patients provides a safe and immunogenic tumor vaccine. (ClinicalTrials.gov number NCT00289341). Trial Registration: ClinicalTrials.gov NCT00289341 [ABSTRACT FROM AUTHOR]

Background: Our objective was to develop a consistent molecular definition of psoriasis. There have been several published microarray studies of psoriasis, and we compared disease-related genes identified across these different studies of psoriasis with our own in order to establish a consensus. Methodology/Principal Findings: We present a psoriasis transcriptome from a group of 15 patients enrolled in a clinical study, and assessed its biological validity using a set of important pathways known to be involved in psoriasis. We also identified a key set of cytokines that are now strongly implicated in driving disease-related pathology, but which are not detected well on gene array platforms and require more sensitive methods to measure mRNA levels in skin tissues. Comparison of our transcriptome with three other published lists of psoriasis genes showed apparent inconsistencies based on the number of overlapping genes. We extended the well-established approach of Gene Set Enrichment Analysis (GSEA) to compare a new study with these other published list of differentially expressed genes (DEG) in a more comprehensive manner. We applied our method to these three published psoriasis transcriptomes and found them to be in good agreement with our study. Conclusions/Significance: Due to wide variability in clinical protocols, platform and sample handling, and subtle disease-related signals, intersection of published DEG lists was unable to establish consensus between studies. In order to leverage the power of multiple transcriptomes reported by several laboratories using different patients and protocols, more sophisticated methods like the extension of GSEA presented here, should be used in order to overcome the shortcomings of overlapping individual DEG approach. [ABSTRACT FROM AUTHOR]

Background: Alefacept treatment is highly effective in a select group patients with moderate-to-severe psoriasis, and is an ideal candidate to develop systems to predict who will respond to therapy. A clinical trial of 22 patients with moderate to severe psoriasis treated with alefacept was conducted in 2002-2003, as a mechanism of action study. Patients were classified as responders or non-responders to alefacept based on histological criteria. Results of the original mechanism of action study have been published. Peripheral blood was collected at the start of this clinical trial, and a prior analysis demonstrated that gene expression in PBMCs differed between responders and non-responders, however, the analysis performed could not be used to predict response. Methods: Microarray data from PBMCs of 16 of these patients was analyzed to generate a treatment response classifier. We used a discriminant analysis method that performs sample classification from gene expression data, via "nearest shrunken centroid method". Centroids are the average gene expression for each gene in each class divided by the within-class standard deviation for that gene. Results: A disease response classifier using 23 genes was created to accurately predict response to alefacept (12.3% error rate). While the genes in this classifier should be considered as a group, some of the individual genes are of great interest, for example, cAMP response element modulator (CREM), v-MAF avian musculoaponeurotic fibrosarcoma oncogene family (MAFF), chloride intracellular channel protein 1 (CLIC1, also called NCC27), NLR family, pyrin domain-containing 1 (NLRP1), and CCL5 (chemokine, cc motif, ligand 5, also called regulated upon activation, normally T expressed, and presumably secreted/RANTES). Conclusions: Although this study is small, and based on analysis of existing microarray data, we demonstrate that a treatment response classifier for alefacept can be created using gene expression of PBMCs in psoriasis. This preliminary study may provide a useful tool to predict response of psoriatic patients to alefacept. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

Background: Microarray studies of the same phenomenon in different labs often appear at variance because the published lists of regulated transcripts have disproportionately small intersections. We demonstrate that comparing studies by intersecting lists in this manner is methodologically flawed by reanalyzing three studies of the molecular signature of "stemness" in human embryonic stem cells. There are only 7 genes common to all three published lists, suggesting disagreement. Results: Carefully reanalyzing all three together from the raw data we detect 111 genes upregulated and 95 downregulated in all three studies. The upregulated list was subject to rtRTPCR analysis and 75% of the genes were confirmed. Conclusion: Our findings show that the three studies have a substantial core of common genes, which is missed if only the published lists are examined. Combined analysis of multiple experiments can be a powerful way to distil coherent conclusions. [ABSTRACT FROM AUTHOR]

Background: Microscopists are familiar with many blemishes that fluorescence images can have due to dust and debris, glass flaws, uneven distribution of fluids or surface coatings, etc. Microarray scans show similar artefacts, which affect the analysis, particularly when one tries to detect subtle changes. However, most blemishes are hard to find by the unaided eye, particularly in high-density oligonucleotide arrays (HDONAs). Results: We present a method that harnesses the statistical power provided by having several HDONAs available, which are obtained under similar conditions except for the experimental factor. This method "harshlights" blemishes and renders them evident. We find empirically that about 25% of our chips are blemished, and we analyze the impact of masking them on screening for differentially expressed genes. Conclusion: Experiments attempting to assess subtle expression changes should be carefully screened for blemishes on the chips. The proposed method provides investigators with a novel robust approach to improve the sensitivity of microarray analyses. By utilizing topological information to identify and mask blemishes prior to model based analyses, the method prevents artefacts from confounding the process of background correction, normalization, and summarization. [ABSTRACT FROM AUTHOR]

We propose the local-global neural networks model within the context of lime series models. This formulation encompasses some already existing nonlinear models and also admits the mixture of experts approach. We emphasize the linear expert case and extensively discuss the theoretical aspects of the model: stationarity conditions, existence, consistency and asymptotic normality of the parameter estimates, and mixed identifiability. The proposed model consists of a mixture of stationary and nonstationary linear models and is able to describe "intermittent" dynamics; the system spends a large fraction of time in a bounded region, but sporadically develops an instability that grows exponentially for some time and then suddenly collapses, lntermittency is a commonly observed behavior in ecology and epidemiology, fluid dynamics, and other natural systems. A model-building strategy is also considered, and the parameters are estimated by concentrated maximum likelihood. The procedure is illustrated with two real time series. [ABSTRACT FROM AUTHOR]

Identification of allergenic IgE epitopes is instrumental for the development of novel diagnostic and prognostic methods in food allergy. In this work, we present the quantification and validation of a Bead-Based Epitope Assay (BBEA) that through multiplexing of epitopes and multiple sample processing enables completion of large experiments in a short period of time, using minimal quantities of patients' blood. Peptides that are uniquely coupled to beads are incubated with serum or plasma samples, and after a secondary fluorophore-labeled antibody is added, the level of fluorescence is quantified with a Luminex reader. The signal is then normalized and converted to epitope-specific antibody binding values. We show that the effect of technical artifacts, i.e. well position or reading order, is minimal; and batch effects - different individual microplate runs - can be easily estimated and eliminated from the data. Epitope-specific antibody binding quantified with BBEA is highly reliable, reproducible and has greater sensitivity of epitope detection compared to peptide microarrays. IgE directed at allergenic epitopes is a sensitive biomarker of food allergy and can be used to predict allergy severity and phenotypes; and quantification of the relationship between epitope-specific IgE and IgG4 can further improve our understanding of the immune mechanisms behind allergic sensitization. [ABSTRACT FROM AUTHOR]

Psoriasis is a complex inflammatory disease resulting from the activation of T helper (Th) 1 and Th17 cells. Recent evidence suggests that abnormal activation of Toll-like receptors (TLRs) 7, 8 and 9 contributes to the initiation and maintenance of psoriasis. We have evaluated the effects of TLR antagonists on the gene expression profile in an IL-23-induced skin inflammation model in mice. Psoriasis-like skin lesions were induced in C57BL/6 mice by intradermal injection of IL-23 in the dorsum. Two TLR antagonists were compared: IMO-3100, an antagonist of TLRs 7 and 9, and IMO-8400, an antagonist of TLRs 7, 8 and 9, both of which previously have been shown to reduce epidermal hyperplasia in this model. Skin gene expression profiles of IL-23-induced inflammation were compared with or without TLR antagonist treatment. IL-23 injection resulted in alteration of 5100 gene probes (fold change ≥ 2, FDR < 0.05) including IL-17 pathways that are up-regulated in psoriasis vulgaris. Targeting TLRs 7, 8 and 9 with IMO-8400 resulted in modulation of more than 2300 mRNAs while targeting TLRs 7 and 9 with IMO-3100 resulted in modulation of more than 1900 mRNAs. Both agents strongly decreased IL-17A expression (>12-fold reduction), normalized IL-17 induced genes such as beta-defensin and CXCL1, and normalized aberrant expression of keratin 16 (indicating epidermal hyperplasia). These results suggest that IL-23-driven inflammation in mouse skin may be dependent on signaling mediated by TLRs 7, 8, and 9 and that these receptors represent novel therapeutic targets in psoriasis vulgaris and other diseases with similar pathophysiology. [ABSTRACT FROM AUTHOR]