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• W2551760472 abstract "Chronic rhinosinusitis (CRS) represents a heterogeneous disease comprising several different subtypes that are grouped together by common criteria lasting at least 12 weeks. The classification of CRS subtypes remains largely clinical and carries little prognostic value. At present, clinicians possess limited capability in predicting a patient's disease course and anticipating response to available therapies. More recently, efforts have focused on categorizing CRS subtypes into endotypes. Endotypes organize disease subtypes according to molecular patterns believed to underlie the expression of different clinical phenotypes.1Akdis C.A. Bachert C. Cingi C. Dykewicz M.S. Hellings P.W. Naclerio R.M. et al.Endotypes and phenotypes of chronic rhinosinusitis: a PRACTALL document of the European Academy of Allergy and Clinical Immunology and the American Academy of Allergy, Asthma &Immunology.J Allergy Clin Immunol. 2013; 131: 1479-1490Abstract Full Text Full Text PDF PubMed Scopus (418) Google Scholar The push for disease endotyping in CRS derives from the successful application of this method in asthma, a disease sharing many pathophysiologic features with CRS. Indeed, the presence of type 2 inflammation represents an important point of disease stratification, both in asthma and in CRS. In asthma, increased blood and tissue eosinophilia, IgE levels, and expression of type 2 inflammatory biomarkers, such as IL-4, IL-5, IL-13, and periostin, have been leveraged to endotype disease, develop novel biologic therapies, and monitor response to treatment.2Gauthier M. Ray A. Wenzel S.E. Evolving concepts of asthma.Am J Respir Crit Care Med. 2015; 192: 660-668Crossref PubMed Scopus (180) Google Scholar In this study, we characterized the expression patterns of several type 2 inflammatory cytokines of interest in different clinical subtypes of CRS. To this end, we use a top-down approach in the form of large-scale microarray gene profiling techniques in 130 patients representing different clinical subtypes of CRS: aspirin-exacerbated respiratory disease (AERD), allergic fungal rhinosinusitis (AFRS), healthy control (HC), chronic rhinosinusitis without nasal polyps (CRSsNP), and chronic rhinosinusitis with nasal polyps (CRSwNP). We believe that a study of this design is well-suited to elucidate patterns of differential gene expression between subtypes that may serve to advance disease endotyping in CRS. To date, this is the largest microarray study of its type in CRS. Table E1 in this article's Online Repository at www.jacionline.org summarizes the different disease subtypes enrolled in each group and relevant clinical characteristics. We first performed hierarchical cluster analysis using microarray data from 130 patients with different subtypes of CRS. This resulted in the identification of 500 distinct gene expression clusters that are illustrated in a heat map (see Fig E1 in this article's Online Repository at www.jacionline.org). Many gene clusters had differential expression patterns characterized by either highly upregulated (red signal) or highly downregulated (green signal) gene expression. Polyp subtypes AERD, AFRS, and CRSwNP demonstrated similar patterns of increased or decreased cluster expression and segregated from CRSsNP and HC on the basis of their differential cluster expression, supporting a clear molecular delineation between polyp and nonpolyp CRS phenotypes. Clusters containing the most differentially expressed sequences between HC and disease, or those of particular interest, were examined for differential expression between subtypes. In addition, data were analyzed to identify correlative and reciprocal relationships between these clusters, and with other biological pathways of interest, especially those involved in type 2 inflammation. Sequences with the highest differential expression between groups were between HC and AFRS or between HC and AERD. The single highest differential signal was from a sequence specific to the soluble form of IgE (Fig 1, A). This expression was significantly upregulated in all subtypes when compared with HC, with AERD and AFRS demonstrating increased local IgE levels when compared with other disease subtypes. IgE expression was higher in patients with CRSwNP with asthma in comparison to patients with CRSwNP without asthma (P < .001), while other subtypes showed no difference in tissue IgE expression when comparing those with and without asthma. We next analyzed the expression of several canonical type 2 inflammatory cytokines (IL-4, IL-5, IL-13) and IFN-γ by digital droplet quantitative PCR (Fig 1, B). We also measured the expression of type 2 cytokine gene clusters that commonly act downstream of these cytokines (CCL13 + CCL18 clusters, CCL26 + periostin clusters, Fig 1, C and D). The cytokines CCL13, CCL18, CCL26, and periostin are of particular interest in CRS because they have been shown to mediate localized eosinophilic inflammation.3Kato A. Immunopathology of chronic rhinosinusitis.Allergol Int. 2015; 64: 121-130Abstract Full Text Full Text PDF PubMed Scopus (170) Google Scholar, 4Wang M. Wang X. Zhang N. Wang N. Wang H. Li Y. et al.Association of periostin expression with eosinophilic inflammation in nasal polyps.J Allergy Clin Immunol. 2015; 136: 1700-1703Abstract Full Text Full Text PDF PubMed Scopus (46) Google Scholar No subtypes demonstrated increased expression of IFN-γ, a canonical type 1 inflammatory cytokine, which is consistent with other studies showing lack of increased IFN-γ in CRS subtypes, including CRSsNP, in Japanese, Chinese, and American populations.3Kato A. Immunopathology of chronic rhinosinusitis.Allergol Int. 2015; 64: 121-130Abstract Full Text Full Text PDF PubMed Scopus (170) Google Scholar All subtypes demonstrated relative increased expression of IL-13. Similarly, all subtypes exhibited increased expression of IL-5 when compared with HC. Only AFRS and CRSwNP subtypes demonstrated significant increases in IL-4 gene expression. Despite no differences detected between the mean copy of IL-13 and IL-4 among CRSwNP, AFRS, and CRSsNP samples, CRSwNP and AFRS had more samples expressing higher copies of IL-13 and IL-4 as compared with samples from patients with CRSsNP. Gene cluster expression analysis of CCL13 + CCL18 and CCL26 + periostin revealed overexpression in comparison to HC of these gene clusters in all CRS subtypes. Taken together, with the exception of IL-4, the expression of the above type 2 inflammatory markers did not separate clinical phenotypes but rather highlighted subgroups (possible endotypes) among the clinical phenotypes with different expression levels of these type 2 inflammatory markers when compared with HC. Because we could not readily delineate subtypes of CRS disease on the basis of relative expression of markers chosen in Fig 1, we explored additional components of type 2 inflammation that might be driving disease in CRS. The mast cell axis represents a central node of type 2 inflammation, capable of responding to both innate and adaptive immune arms to promote a type 2 response. Studies originating from the work of the senior author have found that mast cells are present at increased levels, independent of atopy, in polyp mucosa of patients with CRSwNP.5Shaw J.L. Ashoori F. Fakhri S. Citardi M.J. Luong A. Increased percentage of mast cells within sinonasal mucosa of chronic rhinosinusitis with nasal polyp patients independent of atopy.Int Forum Allergy Rhinol. 2012; 2: 233-240Crossref PubMed Scopus (32) Google Scholar We have also shown that inflamed mucosa of patients with CRSwNP harbor type 2 innate lymphoid cells expressing IL1RL1 (also known as ST2), a receptor for IL-33, and that these type 2 innate lymphoid cells secrete IL-13 in response to stimulation by IL-33.6Shaw J.L. Fakhri S. Citardi M.J. Porter P.C. Corry D.B. Kheradmand F. et al.IL-33-responsive innate lymphoid cells are an important source of IL-13 in chronic rhinosinusitis with nasal polyps.Am J Respir Crit Care Med. 2013; 188: 432-439Crossref PubMed Scopus (208) Google Scholar We wished to determine whether there existed a correlation between the expression of IL1RL1 and genes associated with mast cell activity, and, furthermore, assess whether these genes were exclusive to certain disease subtypes. We found that IL1RL1 transcripts were significantly overexpressed in polyp subtypes, AFRS and CRSwNP, when compared with CRSsNP and HC (Fig 2, A). In addition, the expression of IL1RL1 correlated with a cluster enriched for mast cell–related genes (tryptase cluster, Fig 2, B). We also found that IL1RL1 expression correlated with the expression of 21 genes associated with mast cell and eosinophil activity (see Table E2 in this article's Online Repository at www.jacionline.org). We performed an immunohistochemical analysis in a representative collection of surgically removed CRSwNP polyp tissue (Fig 2, C and D). IL-33 expression was evident in the epithelial cells and around vessels in all polyp samples (Fig 2, C). Immunohistochemistry indicated the presence of abundant eosinophils and mast cells, both known IL1RL1-expressing cells (Fig 2, D). Taken together, these results implicate an IL1RL1-mast cell signaling axis as a potential endotype marker and target for therapeutic intervention. Molecular pathways that drive disease in different CRS clinical phenotypes—so-called endotypes—need further clarification to facilitate the application of personalized therapies in CRS. Our top-down, microarray-based analysis allowed us to characterize the relative expression of several type 2 inflammatory gene clusters of interest in well-defined clinical subtypes of CRS, many of which take into account eosinophilic inflammation, comorbid asthma, aspirin sensitivity, fungal colonization, and atopy. Admittedly, we do not define specific endotypes in this study; however, we evaluated key type 2 inflammatory markers as a means of endotyping patients with CRS. We found that there were trends of elevated expression of certain type 2 inflammatory markers in clinical phenotypes but also found notable variation in expression within a given phenotype. One such marker, local IgE expression, was elevated in subgroups of patients with AERD, AFRS, and CRSwNP with asthma, clinical subtypes that characteristically exhibit increased local sinonasal eosinophilia. Our observations support previous studies that indicate a correlation between local sinonasal IgE expression and increased tissue eosinophilia.7Bachert C. Zhang N. Holtappels G. De Lobel L. van Cauwenberge P. Liu S. et al.Presence of IL-5 protein and IgE antibodies to staphylococcal enterotoxins in nasal polyps is associated with comorbid asthma.J Allergy Clin Immunol. 2010; 126: 962-968Abstract Full Text Full Text PDF PubMed Scopus (293) Google Scholar, 8Tomassen P. Vandeplas G. Van Zele T. Cardell L.O. Arebro J. Olze H. et al.Inflammatory endotypes of chronic rhinosinusitis based on cluster analysis of biomarkers.J Allergy Clin Immunol. 2016; 137: 1449-1456Abstract Full Text Full Text PDF PubMed Scopus (612) Google Scholar, 9Bachert C. van Steen K. Zhang N. Holtappels G. Cattaert T. Maus B. et al.Specific IgE against Staphylococcus aureus enterotoxins: an independent risk factor for asthma.J Allergy Clin Immunol. 2012; 130: 376-381Abstract Full Text Full Text PDF PubMed Scopus (137) Google Scholar, E1De Schryver E. Devuyst L. Derycke L. Dullaers M. Van Zele T. Bachert C. et al.Local immunoglobulin E in the nasal mucosa: clinical implications.Allergy Asthma Immunol Res. 2015; 7: 321-331Crossref PubMed Scopus (69) Google Scholar Interestingly, with the exception of IL-4, all CRS subtypes demonstrated increased expression of several canonical type 2 inflammatory markers (Fig 1). The observed increase in these measured type 2 inflammatory markers in CRSsNP may in part be due to the high prevalence of comorbid allergic rhinitis in this patient population; however, multiple studies have suggested that atopic sinonasal inflammation represents a distinct process from that observed in CRS.E2Fritz S.B. Terrell J.E. Conner E.R. Kukowska-Latallo J.F. Baker J.R. Nasal mucosal gene expression in patients with allergic rhinitis with and without nasal polyps.J Allergy Clin Immunol. 2003; 112: 1057-1063Abstract Full Text Full Text PDF PubMed Scopus (54) Google Scholar, E3Wu J. Bing L. Jin H. Jingping F. Gene expression profiles of nasal polyps associated with allergic rhinitis.Am J Otolaryngol. 2009; 30: 24-32Abstract Full Text Full Text PDF PubMed Scopus (17) Google Scholar, E4Plager D.A. Kahl J.C. Asmann Y.W. Nilson A.E. Palanch J.F. Friedman O. et al.Gene transcription changes in asthmatic chronic rhinosinusitis with nasal polyps and comparison to those in atopic dermatitis.PLoS One. 2010; 5: e11450Crossref PubMed Scopus (61) Google Scholar Our findings complement those of Tomassen et al,8Tomassen P. Vandeplas G. Van Zele T. Cardell L.O. Arebro J. Olze H. et al.Inflammatory endotypes of chronic rhinosinusitis based on cluster analysis of biomarkers.J Allergy Clin Immunol. 2016; 137: 1449-1456Abstract Full Text Full Text PDF PubMed Scopus (612) Google Scholar which showed the presence of type 2 inflammation in both polyp and nonpolyp clinical subtypes, and highlight the complexity of the inflammatory milieu in CRS mucosa. Together, these findings prompt a need to investigate additional type 2 inflammatory pathways that better separate disease subtypes. Studies in asthma and CRS have highlighted multiple different mechanisms that can promote type 2 inflammation, including an adaptive immune component and a recently identified innate type 2 inflammatory component. Epithelial-derived cytokines, such as IL-25, IL-33, thymic stromal lymphopoietin, and mast cells, may play important roles in mediating type 2 inflammatory disease independent of adaptive immunity. Indeed, elevation of the IL-33 receptor, IL1RL1, in CRSwNP is not a novel finding; nonetheless, our results add credence to preceding studies that have shown the importance of this pathway in the pathogenesis of CRSwNP.E4Plager D.A. Kahl J.C. Asmann Y.W. Nilson A.E. Palanch J.F. Friedman O. et al.Gene transcription changes in asthmatic chronic rhinosinusitis with nasal polyps and comparison to those in atopic dermatitis.PLoS One. 2010; 5: e11450Crossref PubMed Scopus (61) Google Scholar, E5Baba S. Kondo K. Kanaya K. Suzukawa K. Ushio M. Urata S. et al.Expression of IL-33 and its receptor ST2 in chronic rhinosinusitis with nasal polyps.Laryngoscope. 2014; 124: E115-E122Crossref PubMed Scopus (52) Google Scholar, E6Endo Y. Hirahara K. Iinuma T. Shinoda K. Tumes D.J. Asou H.K. et al.The interleukin-33-p38 kinase axis confers memory T helper 2 cell pathogenicity in the airway.Immunity. 2015; 42: 294-308Abstract Full Text Full Text PDF PubMed Scopus (162) Google Scholar, 6Shaw J.L. Fakhri S. Citardi M.J. Porter P.C. Corry D.B. Kheradmand F. et al.IL-33-responsive innate lymphoid cells are an important source of IL-13 in chronic rhinosinusitis with nasal polyps.Am J Respir Crit Care Med. 2013; 188: 432-439Crossref PubMed Scopus (208) Google Scholar In addition, to our knowledge, we present novel findings correlating IL1RL1 expression with mast cell activity in polyp subtypes and we extend these findings to the AFRS clinical subtype. We noted a trend toward increased IL1RL1 expression in the AERD clinical subtype (Fig 2, A); however, the small sample size of this group likely precluded achieving statistical significance. Taken together, our results implicate an IL1RL1-mast cell signaling axis as a potential disease marker, a mediator of type 2 inflammation and a potential target for therapeutic intervention. The study presented herein illustrates the complexity of the inflammatory makeup in CRS. Although features of type 2 inflammation appear active in many clinical subtypes of CRS, they may culminate in a type 2 inflammatory response via different mechanisms, including infection, barrier disruption, and allergy. In addition, the degree of type 2 inflammatory activation may be an important factor in differentiating disease endotypes. As clinical trials that test the efficacy of novel therapies in CRS progress, a better understanding of the specific molecular pathways that drive a patient's disease will aid in identifying those who will benefit most from these novel treatment strategies. We acknowledge Kim Merriam and Ken Ganley for their help with immunohistochemistry. Patients undergoing medically indicated functional endoscopic sinus surgery consented to having sinonasal tissue, which was removed as a standard of their surgery, collected and analyzed for gene expression. The Institutional Review Board at the University of Texas Health Science Center at Houston approved the study protocol. Patients were grouped into CRSwNP, CRSsNP, AERD, or AFRS according to criteria set forth in the European Position Paper on Rhinosinusitis and Nasal Polyps.E7Fokkens W.J. Lund V.J. Mullol J. Bachert C. Alobid I. Baroody F. et al.European Position Paper on Rhinosinusitis and Nasal Polyps 2012.Rhinol Suppl. 2012; : 1-298Google Scholar Patients were grouped into CRSwNP or CRSsNP on the basis of presence or absence of polyps on nasal endoscopy. Polyps documented by an ENT physician on nasal endoscopy at any time categorized a patient as CRSwNP subtype. Patients with CRSwNP were diagnosed with AFRS if there was evidence of eosinophil-rich mucus with noninvasive fungal hyphae, hypersensitivity to fungi, and characteristic radiographic findings.E8Bent J.P. Kuhn F.A. Diagnosis of allergic fungal sinusitis.Otolaryngol Head Neck Surg. 1994; 111: 580-588Crossref PubMed Scopus (586) Google Scholar AERD was characterized by the presence of asthma, the presence or documented history of nasal polyps, and history of intake of aspirin or nonsteroid anti-inflammatory drug inciting worsening respiratory symptoms. Patients classified as asthmatic had a previous diagnosis of asthma by a pulmonologist, allergist, and/or positive pulmonary function testing. In this study, CRSwNP excludes patients with AERD and AFRS. HCs were defined as patients with no history of atopy or asthma symptoms. These patients were undergoing sinus surgery as a component of surgical approach to the skull base for removal of benign pituitary lesion or repair of anterior skull base cerebrospinal fluid leak. A table delineating the number of patients enrolled according to each clinical subtype, along with relevant clinical factors, has been presented in Table E1. No clinical subtype was treated in an exclusive manner, in that they did not receive any specific medical or surgical therapy that deviated from the standard of care delivered to other subtypes. Per study protocol, all topical and systemic corticosteroids were withheld at least 4 weeks before surgery when tissue was harvested. A fragment of inflamed ethmoid mucosa was removed during endoscopic sinus surgery, immediately wrapped in aluminum foil and flash frozen in liquid nitrogen. Frozen biopsies were placed in lysis buffer and homogenized with a Qiagen TissueRupter (Qiagen, Valencia, Calif). In instances in which a substantial amount of mucosa was harvested during surgery, tissue was separated and treated as independent samples. For microarray analysis, this was the case in a select group of patients: AFRS (45 patients yielded 51 samples), CRSwNP (38 patients, 45 samples), and HC (17 patients, 22 samples). For droplet digital PCR (described below), we included RNA from subsequent enrollees in addition to the index (n = 130, 147 samples) patient set: AERD (6 patients, 6 samples), AFRS (49 patients, 55 samples), HC (17 patients, 23 samples). RNA was prepared using the mirVana miRNA isolation kit (Applied Biosystems, Carlsbad, Calif), modified to include an on-column treatment with RNase-free DNase (Qiagen). RNA quality was assessed by RNA Integrity Number values from the BioAnalyzer 2100 (Agilent, Palo Alto, Calif). Fifty nanogram total RNA was amplified using the Ovation RNA Amplification System V2 and WB reagent (Nugen, Inc, San Carlos, Calif). Of the amplified cDNA, 4.4 μg was labeled using the FL Ovation cDNA Biotin Module V2 (Nugen, Inc) according to the manufacturer's recommendations. The labeled cDNA was hybridized onto Affymetrix human genome HG-U133_Plus_2 arrays (Affymetrix, Santa Clara, Calif) and processed according to Affymetrix technical protocols. The average intensity of each array was scaled to a target intensity of 500. Single genes were analyzed by droplet digital PCR on the BioRad (Hercules, Calif) QX100 system, in duplex mode. Target gene probe sets were labeled with FAM, and the RBM22 reference normalizer probe set was labeled with VIC. All probe sets were standard Applied Biosystems (Grand Island, NY) catalog probe sets (IL-4, Hs00174122_m1; IL-5, Hs01548712_g1; IL-13, Hs00174379_m1; IFNG, Hs00989291_m1). Raw Affymetrix. CEL files were preprocessed in Array Studio (OmicSoft, Cary, NC; http://www.omicsoft.com) using its default procedures including data normalization by Robust Multi-array Average approach. Microarray data were analyzed for different patterns of gene expression by hierarchical clustering analysis. To identify sets of genes with highly correlated expression patterns, a set of 32,719 sequences with coefficients of variation greater than 0.03 across all the samples was used. This method was used to identify (dis)similarities between data sets based on a measurement of Euclidean distance. These (dis)similarities between data sets were organized into discrete clusters that are visualized as a dendrogram (Fig E1). We used Ward's linkage method, which uses within-cluster sum of squares computations to group clusters of gene expression. Using these methods, we identified 500 clusters of differential gene expression and evaluated the separation of different subtypes qualitatively in Fig E1. Clusters containing the most differentially expressed sequences, or some of previously identified biological significance, were then examined for differential expression between the disease groups and their relationships with each other (Fig 1). Tissue sections from formalin-fixed, paraffin-embedded human nasal polyps from patients with CRS undergoing routine surgical removal (n = 9) were cut at 5 microns, baked at 65°C for 30 to 60 minutes, deparaffinized in xylene, and rehydrated through graded ethanol solutions. Serial sections were stained with hematoxylin and eosin following standard methodology and specific immunohistochemical staining was performed. Antigen retrieval for tissue sections stained for IL-33 and mast cell tryptase was accomplished by steaming the slides in DIVA buffer (Biocare Medical #DV2004, Concord, Calif) for 60 minutes. Endogenous protein was blocked with Background Sniper (Biocare Medical, #BS966), and then endogenous avidin and biotin were blocked (Biocare Medical #AB972). Antigen retrieval for tissue sections stained for eosinophil major basic protein was accomplished by incubating the sections with Pepsin for 30 minutes (Biocare Medical, Carezyme II # PEP956). Slides were then incubated with anti–IL-33 (Goat polyclonal, R&D Systems #AF3625), anti–mast cell tryptase (Rabbit polyclonal, Abcam #ab35118, Cambridge, Mass), or anti–eosinophil major basic protein (Mouse monoclonal, AbD Serotec #MCA 5751, Raleigh, NC) diluted in DaVinci Green diluent (Biocare Medical #PD900). Next, endogenous peroxidase was quenched (Biocare Medical #PX968). Slides stained for IL-33 were incubated with biotinylated anti-goat IgG (Vector PK6105, Vector Labs, Burlingame, Calif) followed by ABC-HRP (Vector PK6105, Vector Labs). Slides stained with mast cell tryptase were detected with goat anti-rabbit horseradish peroxidase–labeled polymer (Biocare Medical #RHRP520). Primary antibody against eosinophil major basic protein was detected using a goat anti-mouse horseradish peroxidase–labeled polymer (Biocare Medical #RMRP520). Slides were then developed with DAB chromogen (Biocare Medical #DCB859), rinsed in water, counterstained in hematoxylin, dehydrated, cleared, and mounted.Table E1Clinical phenotypes of patients with CRS and HCs enrolled in studyCRS subtype (n)HC (17)AERD (5)AFRS (45)CRSwNP (38)CRSsNP (25)Age (y), median5343265048Sex: Male/female10/71/425/2023/1515/10Asthma (%)0/17 (0)5/5 (100)12/45 (27)21/38 (55)5/25 (20)Inhalant allergy (%)0 (0)3 (60)45 (100)25 (66)12 (52)Aspirin sensitivity (%)0 (0)5 (100)0 (0)0 (0)0 (0) Open table in a new tab Table E2Mast cell– and eosinophil-related gene cluster and its correlation with IL1RL1 (ST2) expressionCorrelationRankGeneDescriptionProbe0.8852922IL1RL1ST2242809_PM_at0.7231863IL1RL1ST2207526_PM_s_at0.6858954IL10IL10207433_PM_at0.6760265SAMSN1(Nash1, mast cell nuclear adaptor protein)1555638_PM_a_at0.6709936SOCS1SOCS1213337_PM_s_at0.6625897CCL23CCL23 (eosinophil-enriched chemokine)210549_PM_s_at0.6542159LYVE1Lymphatic vessel endothelial hyaluronan receptor 1220037_PM_s_at0.65325110IL18R1IL18 receptor206618_PM_at0.64899411SRGNSerglycin (Mast cell protease-associated proteoglycan)201858_PM_s_at0.64887112ADORA3Adenosine A3 receptor (expressed by eosinophils and macrophages)206171_PM_at0.6376414IGHA1Immunoglobulin heavy locus217469_PM_at0.63023216ALOX5APArachidonate 5-lipoxygenase-activating protein (FLAP)204174_PM_at0.62687918C3AR1Complement component 3a receptor 1 (mast cells?)209906_PM_at0.62548319SOCS1SOCS1210001_PM_s_at0.61968820CCL18CCL18209924_PM_at0.61945621IL1R1IL1 receptor202948_PM_at0.61886422HPGDSProstaglandin D synthase (mast cells)206726_PM_at0.61683223PMCHPromelanin-concentrating hormone206942_PM_s_at0.61417524CCND2Cyclin D2200951_PM_s_at0.61363225NFIL3Nuclear factor, IL-3 regulated (IL4-induced, regulates IgE)203574_PM_at0.60820127SRGNSerglycin (Mast cell protease-associated proteoglycan)201859_PM_at0.60793528CTSGCathepsin G (Mast cell protease)205653_PM_at0.60694830PIM1Pim-1 oncogene209193_PM_at0.60225532PTGDR2Prostaglandin D2 receptor 2 (CRTH2) (expressed by eosinophils and type 2 innate lymphoid cells)206361_PM_atThe genes listed above were identified as highly correlated with one another as well as with the expression of IL1RL1. Data shown were generated from pooled expression values from all subtypes of CRS. Correlation coefficients (leftmost column) were generated using a Spearman's rank test and the IL1RL1 probe (234066_at). For all correlations, P < .001. Open table in a new tab The genes listed above were identified as highly correlated with one another as well as with the expression of IL1RL1. Data shown were generated from pooled expression values from all subtypes of CRS. Correlation coefficients (leftmost column) were generated using a Spearman's rank test and the IL1RL1 probe (234066_at). For all correlations, P < .001." @default.
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• W2551760472 title "Large-scale gene expression profiling reveals distinct type 2 inflammatory patterns in chronic rhinosinusitis subtypes" @default.
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