Inflammation Driven Vascular Dysregulation in Chronic Rhinosinusitis

Abstract

Background:

Altered neovascularity is typically observed in chronic inflammatory diseases with overlapping pathophysiology to that observed in chronic rhinosinusitis (CRS). However, the characterization of these inflammatory-induced vascular mediated changes in CRS is limited. Understanding the underlying vascular changes in CRS will allow for strategic design and development of new drug delivery technologies that exploit vascular permeability for increased extravasation into the target sinonasal tissues.

Methods:

Patients with CRS with nasal polyps (CRSwNP) and without (CRSsNP), in addition to non-CRS controls were enrolled into a prospective observational study. The extent of angiogenesis in tissue was characterized using immunohistochemical and multiplex gene expression analyses. Vascular permeability, interendothelial junction structures, and endothelial barrier morphology were evaluated using transmission electron microscopy.

Results:

Sinonasal vascularity was significantly increased in CRSsNP and CRSwNP (p<0.05) compared to controls, as assessed by enumerating the platelet endothelial cell adhesion molecule (PECAM-1)-positive blood vessels. Pro-angiogenic gene expression, including PECAM1 and platelet activating factor receptor, was significantly elevated in patients with CRSwNP compared to controls (p<0.05). The fenestration sizes between endothelial cells (17–280 nm) were larger in CRSwNP compared to CRSsNP (10–33 nm5) and controls (4–12 nm). Global thinning of the endothelial cell lining was observed in patients with CRS compared to controls.

Conclusion:

Significant increases in vascularity, pro-angiogenic gene and protein expression, and blood vessel morphogenesis were observed in patients with CRS compared to controls. Further, fenestration sizes between interendothelial junction structures were larger in CRS compared to controls, suggesting inflammation-driven vascular dysregulation in CRS pathology.

Introduction

Chronic rhinosinusitis (CRS) is a debilitating inflammatory disorder of the sinonasal mucosa. The underlying chronic inflammation results in multiple pathophysiological changes including tissue remodeling, tissue disruption, and subepithelial fibrosis ^1–5. Inflammation-induced vascular dysregulation has not been well characterized for CRS and the implications it may hold. Inflammation-induced vascular pathophysiology has been extensively studied in other chronic inflammatory disorders ^6–9 leading to the understanding and subsequent development of important systemic nano-scale drug delivery systems that are capable of delivering therapeutics to the inflamed site.

Chronic inflammation and angiogenesis are known to be tightly intertwined ^10,11. Such that many inflammatory mediators that accumulate at sites of inflammation stimulate pro-angiogenic signaling molecules such as adhesion molecules, growth factors, selectins and inflammatory cytokines. These pro-angiogenic mediators activate endothelial cells, which is the primary step of new blood vessel formation ¹². Although this relationship has been well described in the literature, pro-angiogenic gene expression and associated vascularity has not been well characterized in patients with CRS.

The endothelial vascular barrier is controlled by a strong network of intercellular junctions, which is regulated by adhesion molecules such as platelet endothelial cell adhesion molecule (PECAM-1). Inflammatory responses often result in the interruption and widening of these intercellular junctions, enabling leukocyte extravasation and increased blood protein and other macromolecule transport from blood vessels into local sites of tissue injury ¹³. These processes result in increased vascular permeability, allowing for therapeutic access and accumulation of systemically administered drugs with improved efficacy and decreased off-target toxicity ¹⁴. To design safer and more effective systemic drug delivery technologies, an improved understanding and characterization of endothelial barrier gap junctions, morphology and vascular pathophysiology in CRS is essential. Our objectives of this study were to further characterize the inflammation-driven vascular dysregulation in CRS.

Materials and Methods

Study subjects and demographics

Adult study participants with a diagnosis of refractory CRS with (CRSwNP) and without (CRSsNP) nasal polyps were enrolled into a prospective observational cohort using informed consent procedures from the University of Utah Sinus with approval from the University of Utah Institutional Review Board (IRB #61810). Inclusion criteria included a current diagnosis of refractory CRS for patients electing endoscopic sinus surgery after failing appropriate medical management as defined by the 2015 Adult Sinusitis Guidelines ¹⁵. All study participants provided their demographic information and medical history and underwent standard clinical examinations consisting of physical evaluations, computed tomography (CT) imaging of the sinuses, and sinonasal endoscopy. Patients known to have other systemic inflammatory components such as rheumatoid arthritis (RA), chronic obstructive pulmonary disease (COPD), systemic lupus erythematosus (SLE), multiple sclerosis (MS), cystic fibrosis (CF), fibromyalgia and those on oral steroids were excluded from the study to control for systemic inflammatory contributions. Patients enrolled for surgeries other than chronic or acute sinusitis were included as control patients. Similar to CRS patients, control patients with a history of RA, COPD, SLE, MS, CF and fibromyalgia were excluded from the study.

Tissue collection and tissue section preparation

During endoscopic sinus surgery, anterior ethmoid tissue (~4 mm²) was collected from each study participant (CRS and controls). The tissues were sectioned into four sections, each undergoing different preparation and storage conditions. Tissue sections were either (1) fixed in 4% paraformaldehyde and prepared for histological and immunohistochemical analysis, (2) placed in RNAlater and snap frozen to stabilize the in-vivo RNA profile for gene expression analysis or (3) fixed in a solution of 1% glutaraldehyde, 2.5% paraformaldehyde, 100 mM cacodylate buffer, 6 mM CaCl₂, and 4.8% sucrose, for transmission electron microscopy (TEM) imaging. Tissues for RNA determination were stored in −80°C until assayed. Tissues for histology were fixed in 4% paraformaldehyde for two days, trimmed, and submitted to the Huntsman Cancer Institute Biorepository and Molecular Pathology Core at the University of Utah Histology for embedding, sectioning, slide mounting, and hematoxylin and eosin (H&E) staining.

Messenger RNA extraction and gene expression analysis

Tissue specimens were homogenized using a Qiagen Tissuelyser LT (Qiagen, Hilden, Germany) by immersing the tissue in 0.6 mL of lysis buffer and a 5 mm stainless steel bead. RNA was isolated using the Qiagen AllPrep RNA microRNA (miRNA) Universal kit (Qiagen, Hilden, Germany) using the manufacturer’s protocol. A NanoDrop Spectrophotomer was used to quantify RNA by examining the A_260/280 and A_260/230 ratios. The samples were then analyzed using the nCounter system (Nanostring, Washington, USA). The Huntsman Cancer Institute Molecular Diagnostics Core at the University of Utah performed the gene expression profiling. Sample hybridization was performed by combining 5 μL of total RNA sample with 8 μL of nCounter reported probes in hybridization buffer and 2 μL of nCounter capture probes. The target genes were then quantified using an nCounter Digital Analyzer, and analysis was performed using the nSolver software. Fifteen housekeeping genes (ABCF1, ALAS1, EEF1G, G6PD, GAPDH, GUSB, HPRT1, OAZ1, POLR1B, POLR2A, PPIA, RPL19, SDHA, TBP, and TUBB) were used for normalization of the raw mRNA transcript counts for all samples. The ratio of difference in the means of the log-transformed normalized data to the square root of the sum of the variances of samples were reported. Genes of interest were then screened and reported by analyzing genes that are related to angiogenic or vascular signaling pathways.

PECAM-1 immunohistochemistry and sinonasal tissue imaging

Staining was performed by first deparaffinizing the tissues using Citrus Clearing Solvent (Richard Allan, California, USA), followed by systematic hydration with absolute ethanol, 95% ethanol, 80% ethanol, 70% ethanol, and double distilled water (ddH₂O). The slides were then subjected to heated-antigen retrieval for 20 minutes in tris-based buffer at pH 9.0 (Vector Labs, California, USA). The sections were then treated with 3% H₂O₂ in methanol for peroxidation. After washing the sections with TBS-TritonX-100 at pH 7.4, the sections were incubated with a background sniper (Biocare Medical, California, USA) for 12 minutes to reduce any nonspecific antibody binding. The sections were then washed with TBS-TritonX-100 at pH 7.4, followed by incubation with rabbit polyclonal anti-human PECAM1 (1:200 in 1% BSA in TBS at pH 7.4, Invitrogen Cat# PA5–16301, California, US) for 1 hour at room temperature in a humidifying chamber. The sections were washed with TBS at pH 7.4 and incubated with secondary antibody (MACH4 HRP, Biocare medical, California, USA) for 30 minutes at room temperature in a humidifying chamber. Tissues were stained with 3,3’-diaminobenzidine (DAB) (Biocare medical, California, USA) and hematoxylin (Vector labs, California, USA) as a counterstain, followed by systematic dehydration and mounting using Limonene mounting medium (Abcam, Cambridge, United Kingdom) and Fisherbrand™ superslip cover slips (Fisher Scientific, Massachusetts, USA).

Images were recorded using a Nikon Optiphot 2 microscope (Nikon, Minato, Japan) at 10X and 20X magnification and NIS elements software (Nikon, Minato, Japan) with an exposure of 50 mS, resolution quality of 3 × 8 bit 2880 X 2048, analog gain of 1.0X, and live acceleration of 1.0X. The images were white balanced and dynamic-corrected using a gamma value of 1.6.

Sinonasal tissue imaging by transmission electron microscopy (TEM)

Sinonasal tissues placed in 1% glutaraldehyde, 2.5% paraformaldehyde, 100 mM cacodylate buffer (pH 7.4), 6 mM CaCl₂, and 4.8% sucrose were fixed overnight at 4°C. Samples were then subsequently washed three times for 10 minutes using a 100 mM cacodylate buffer (pH 7.4), followed by secondary fixation in 2% osmium tetroxide for 1 hour at room temperature. Samples were then washed for 5 minutes using 100 mM cacodylate buffer and distilled water. The tissue specimens were then stained with saturated uranyl acetate for 1 hour at room temperature, followed by systematic dehydration with increasing concentration of ethanol (30%, 50%, 70%, 2 × 95%, and 4 × 100% for 15 minutes each). A further dehydration step using acetone (3 × 10 minutes) was performed, and the samples were then infiltrated with Epon epoxy resin using increasing concentration: 30% (5 hours), 70% (overnight), 100% (3 × 8 hours), and 100% fresh resin for embedding. The resin was then polymerized for 48 hours at 60°C. Ultracut sectioning of 70-nm thick tissues was performed using a Leica UC 6 ultratome (Leica Microsystems, Illinois, USA), followed by mounting in EMS200-Cu 200 mesh copper grids (Electron Microscopy Sciences, Pennsylvania, USA), staining with saturated uranyl acetate for 20 minutes, and staining with lead citrate for 10 minutes. Imaging was performed using an accelerating voltage of 120 kV in a JEOL-1400 plus (JEOL, Akishima, Japan) transmission electron microscope equipped with a CCD Gatan camera (Gatan, California, USA). Images were acquired by clicking on Start Acquire button in the Gatan Ultrascan 1000 software. The inbuilt function ‘Cal line’ was used to annotate lines and measure the distances. The ‘Cal line’ tool automatically measures distances.

Blood vessel quantification analysis

For sinonasal tissue sections, three subepithelial areas demonstrating prominent inflammation were randomly selected for vascularity evaluation using PECAM-1 as an endothelial cell/blood vessel marker at 20X magnification. The surface area was then measured (mm²), and all PECAM-1-positive blood vessels were annotated with a green counter within all circled areas. Before being counted, each blood vessel was histologically assessed for degenerative changes to the lumen, vessel wall, and endothelial lining, and as well as for blood content within the lumen. All inflammatory cells and epithelial cells nonspecifically labeled with PECAM-1 were disregarded for blood vessel counts. Blood vessels that appeared tangentially sectioned or showed irregular counter annotation were carefully evaluated to ensure appropriate enumeration. Of note, PECAM-1 cross-reactivity with lymphatic channels could not be excluded, and thus, lymphatic channels were included in the overall blood vessel counts. For quantification, the total number of blood vessels were counted in each subepithelial area that was randomly selected and was divided by the area of the respective subepithelial area measured in mm². All the three values of $\frac{total number of blood vessels per subepithelial area}{subepithelial area in m{m}^2}$ were averaged for each sample. This gave us the number of blood vessels per mm² of tissue for 1 sample. This was done for 8 different samples within each cohort and mean ± SD were plotted on the graph for n=8.

Statistics

Data were processed in GraphPad Prism Version 8.0. If a comparison between two groups were made, the data were analyzed using an unpaired two-tailed t-test. If a comparison between three or more groups were made, the data were analyzed using one-way analysis of variance (ANOVA), followed by post-hoc Tuckey’s tests for multiple comparison. The threshold of significance was p<0.05.

Results

Study participant demographics

A total of 63 patients were prospectively enrolled. For histologic analysis patients with CRSsNP (n=8), CRSwNP (n=8) and non-CRS (n=8) controls were enrolled. No significance was found between the groups (Table 1). For pro-angiogenic gene-expression analysis using the nCounter system (Nanostring, Washington, USA), patients with CRSsNP (n=17), CRSwNP (n=14) and non-CRS (n=10) controls were enrolled (Table 1). Asthma was found to be significantly different between the groups (p=0.018).

Table 1.

Demographic information of study participants.

Histologic Analysis	Control (n=8)	CRSwNP (n=8)	CRSsNP (n=8)	p-value
Gender, n (%)				0.818
Male	5 (83.33)	3 (50)	4 (66.67)
Female	1 (16.67)	3 (50)	2 (33.33)
Age, Mean ± SD	57 ± 15.34	49.33 ± 17.68	45.17 ± 17.93	0.491
Race, n (%)				1.000
White	6 (100)	6 (100)	6 (100)
Asthma, n (%)	2 (33.33)	1 (16.67)	3 (5)	0.818
Allergy, n (%)	4 (66.67)	4 (66.67)	2 (33.33)	0.589
GERD, n (%)	2 (33.33)	1 (16.67)	2 (33.33)	1.000
Diabetes, n (%)	0 (0)	1 (16.67)	0 (0)	1.000
NanoString Analysis	Control (n=10)	CRSwNP (n=14)	CRSsNP (n=17)
Gender, n (%)				0.508
Male	7 (70)	8 (57.14)	8 (47.06)
Female	3 (30)	6 (42.86)	9 (52.94)
Age, Mean ± SD	46.1 ± 15.34	44.71 ± 19.08	49.71 ± 17.01	0.710
Race, n (%)				0.204
White	9 (90)	14 (100)	17 (100)
Asthma, n (%)	1 (10)	0 (0)	0 (0)	0.018
Allergy, n (%)	1 (10)	9 (64.29)	10 (58.82)	0.129
GERD, n (%)	3 (30)	3 (21.43)	5 (29.41)	0.636
Diabetes, n (%)	0 (0)	1 (7.14)	0 (0)	0.476

CRSwNP: chronic rhinosinusitis with nasal polyposis. CRSsNP: chronic rhinosinusitis without nasal polyposis. AERD: Aspirin-Exacerbated Respiratory Disease. GERD: Gastroesophageal Reflux Disease.

Sinonasal vascularity is significantly increased in CRS

Using PECAM-1 as a standardized marker of vascularity, immunohistochemistry was performed. PECAM-1-positive blood vessel counts were significantly increased in the sinonasal mucosa of patients with CRSsNP (p<0.01) and CRSwNP (p<0.05) compared to controls (Figure 1A and B). No significant difference was observed between blood vessel counts in CRSsNP and CRSwNP (Figure 1A and B).

Figure 1. Sinonasal vascularity is significantly increased in CRS.

PECAM-1 (CD31)-positive blood vessels (black arrows) are significantly increased in sinonasal tissues in CRSsNP and CRSwNP compared to controls, as demonstrated by (A) immunohistochemistry and (B) blood vessel quantification. Data represent the mean ± SD of three random tissue areas at 20X magnification for each patient group. *p<0.05, **p<0.01. CRSsNP: chronic rhinosinusitis without nasal polyposis. CRSwNP: chronic rhinosinusitis with nasal polyposis.

Pro-angiogenic gene expression is significantly increased in CRS

Angiogenesis and vascular signaling pathway-associated genes, including intracellular adhesion molecule 2 (ICAM2), intercellular adhesion molecule 3 (ICAM3), platelet endothelial cell adhesion molecule 1 (PECAM1), interleukin 1 receptor type 1 (IL1R1), and signaling lymphocytic activation molecule 7 (SLAMF7), were significantly elevated in anterior ethmoid tissues in CRSwNP compared to in CRSsNP (p<0.05) and controls (p<0.05). The expression of platelet activating factor receptor (PTAFR) (p<0.05) and tumor necrosis factor superfamily 12 (TNFSF12) (p<0.05) was significantly increased in both phenotypes of CRS compared to controls.

Fenestration sizes between endothelial cells are increased in sinonasal tissues in CRS

Based on our qualitative assessment, fenestration sizes were increased in ethmoid tissue from patients with CRSwNP compared to the ethmoid tissue of patients with CRSsNP and controls (Figure 3A). The fenestration sizes in the anterior ethmoid tissue in patients without CRS ranged from 2 to 13 nm compared to 2 to 33 nm in patients with CRSsNP. The tissue of patients with CRSwNP showed fenestration sizes as high as 140 nm. The fenestration sizes are reported as the mean fenestration size ± SEM for the different CRS phenotypes: control ethmoid tissue, 7.93 ± 4.35 nm; CRSsNP ethmoid tissue, 19.45 ± 7.68 nm, CRSwNP ethmoid tissue, 36.31 ± 33.48 nm (Figure 3B).

Figure 3. The fenestration sizes between adjacent endotheial cells is increased in CRS.

Representative TEM images of sinonasal tissues demonstrating (A) endothelial cell junction structures or fenestration morphology, where the fenestration size is denoted in red text. (B) Bar graph depicting the mean ± SD of fenestration sizes in each patient group. CRSsNP: chronic rhinosinusitis without nasal polyposis. CRSwNP: chronic rhinosinusitis with nasal polyposis.

Blood vessel morphology is altered in CRSwNP

Damage to blood vessel morphology was observed in the sinonasal tissues of patients with CRSsNP and CRSwNP compared to controls (Figure 4), as demonstrated by thinning of both luminal and abluminal endothelial cell membranes around the blood vessels (Figure 4, yellow arrows). In contrast, sinonasal tissues from controls demonstrated a thick lining of endothelial cells around the blood vessels, tighter junction gaps, and a regular, consistent formation of all three layers of the blood vessel wall (Figure 4, red arrows).

Figure 4. Blood vessel morphology is altered in CRSsNP and CRSwNP.

TEM imaging demonstrates damage to blood vessel morphology in the form of lining thinning (yellow arrows) in ethmoid tissue from patients with CRSsNP and CRSwNP whereas controls demonstrate an entact morphology of the blood vessels walls. (red arrows). CRSsNP: chronic rhinosinusitis without nasal polyposis. CRSwNP: chronic rhinosinusitis with nasal polyposis. IEJs: interendothelial junctions.

Discussion

At a physiological resting state, vascular and endothelial structures are responsible for controlling blood flow, homeostasis, and the exchange of proteins ¹⁶. During inflammation, the vascular system is activated by pro-inflammatory triggers that result in a myriad of effects such as neoangiogenesis, vascular morphogenesis, vasculature development, and differential expression of vascular and proangiogenic genes ^17,18. Inflammatory triggers and their involvement in inflammation ultimately leads to an increase in vascular permeability and dysregulation ^17,19,20. Inflammation and angiogenesis are interdependent functions that have been implicated in many inflammatory conditions such as osteoarthritis ⁶, atherosclerosis ⁸, retinal neovascular conditions ^21,22, ulcerative colitis and Chrohn’s disease ⁹ and RA ⁷. Although, inflammation-driven angiogenesis has been extensively studied little has been investigated in CRS ²³. Herein, we characterize inflammation-driven angiogenesis in CRS.

Inflammation-driven angiogenesis was assessed by examining neoangiogenesis, vascular permeability, blood vessel morphogenesis and angiogenic gene expression in sinonasal tissues and was characterized by (i) quantifying the blood vessels (neoangiogenesis), (ii) evaluating pro-angiogenic vascular genetic profiles (neoangiogenesis), (iii) measuring endothelial tight junction gap sizes (increase in vascular permeability), and (iv) evaluating the morphological changes to blood vessels (increase in blood vessel morphogenesis) in patients with CRSwNP and CRSsNP compared to controls (Figure 5).

Figure 5. Schematic illustrating inflammation-driven vascular dysregulation in CRS.

Inflammation results in dysregulation in the vasculature in patients with CRS in the form of increase in neoangiogenesis, vascular permeability and blood vessel morphogenesis.

Neoangiogenesis can be assessed at the tissue level using PECAM-1. PECAM-1 is a standard biomarker for endothelial cells and is commonly used to assess and quantify vascularity by calculating the PECAM-1-positive blood vessels within the tissue ^24,25. We demonstrated that PECAM-1 expression and blood vessel counts were significantly increased in the sinonasal mucosa of patients with CRSsNP and CRSwNP compared to controls, indicating an increase in neoangiogenesis in CRS (Figure 1). We posit the increase in number of blood vessels are attributed to either neovascularization (assembly of new vasculature structure) or neoangiogenesis (formation of new blood vessels) or even to their combinatorial effect. Although unclear on the mechanism, it is clear that chronic sinonasal inflammation is involved in the process of vascular dysregulation in the formation of increased PECAM-1 positive blood vessels. These data are consistent with the current understanding of the pathophysiology of inflammation-driven neovascularization in the airways. In the lower airway, a clear association exists between neovascularization (numbers of blood vessels) in the bronchial wall and the severity of inflammation ²⁶. In contrast, in control tissues, very little PECAM-1 expression was observed.

Intercellular adhesion molecules (ICAMs) play an important role in maintaining vascular integrity and are commonly upregulated in acute and chronic inflammation due to an accumulation of inflammatory signaling molecules, all of which can lead to vascular dysregulation ²⁷. The gene expression of pro-angiogenic adhesion molecules (ICAM2, ICAM3, and PECAM1) was significantly elevated in patients with CRS compared to controls (Figure 2). We similarly observed a significant increase in PTAFR expression, a well-known protein involved in inflammation and angiogenesis in patients with CRS (Figure 2) ^28–33. ICAM2, ICAM3 and PECAM1 are critical in regulating the tight junctions between endothelial cells ³⁴. When inflammation is induced, their expression levels go up and inflammatory precursors start disrupting the adhesion molecule interactions causing dysregulation in the natural vasculature development process. This results in the endothelial cells drifting apart from each other. The increase in vascularity in patients with CRS and the over-expression of pro-angiogenic genes corroborates the concept of increased neoangiogenesis and it also demonstrates and validates the concept of inflammation-driven neoangiogenesis in CRS.

Figure 2. Pro-angiogenic gene expression is significantly elevated in sinonasal tissues in CRSsNP and CRSwNP compared to controls.

Data represent the mean ± SD gene transcript copy number for each patient group. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. CRSsNP: chronic rhinosinusitis without nasal polyposis. CRSwNP: chronic rhinosinusitis with nasal polyposis. ICAM2: intercellular adhesion molecule 2. ICAM3: intercellular adhesion molecule 3. IL1R1: interlukin 1 receptor type 1. PDGFRB: platelet derived growth factor receptor beta. PECAM1: platelet endothelial cell adhesion molecule 1. PTAFR: platelet activating factor recpetor. SLAMF1: signaling lymphocytic activation molecule family member 1. TNFSF12: tumor necrosis factor superfamily 12

Vascular permeability is dynamically regulated by numerous intrinsic and extrinsic factors that may cause the disruption or widening of interendothelial junctions (IEJs). An increase in vascular permeability usually results in disruption of IEJs and widening of the gaps that are formed between endothelial cells to accommodate passive diffusion of macromolecules. This process is of great advantage in systemic therapeutic drug design, as nanoscale drug delivery systems can extravasate through these widened endothelial gaps to increase drug accumulation at the local tissue site. We are actively investigating inflammation-induced permeability for the precise design of tunable systemic drug extravasation and accumulation into target tissue ^14,35,36. Herein, we observed an increase in fenestration sizes or IEJs in the sinonasal mucosa of patients with CRSsNP and CRSwNP (19.45 ± 7.68 nm and 36.31 ± 33.48 nm, respectively) compared to controls (7.93 ± 4.35 nm) (Figure 3).

Vascular and endothelial integrity is highly dysregulated in chronic inflammatory conditions such as rheumatoid arthritis ⁷ and atherosclerosis ⁸ resulting in altered vascular morphogenesis ^20,37. Herein, we show key morphological changes to blood vessels in patients with CRS. All three layers of the blood vessels (tunica extrema, tunica media, and tunica intima) were damaged with respect to the endothelial barrier lining thinning, fractures to the basement membrane, and wider gaps between tight junctions in tissue obtained from a CRS patient. Contrastingly, the endothelial barrier was thick and dense in control tissues (Figure 4). Vasculature development is a highly fine-tuned process involving pathophysiological functions like signaling to induce new vessels, vessel fusion to other vessels, lumen formation, vessel remodeling and maturation. Inflammatory responses often lead to dysfunction of these processes ultimately leading to disruption and dysregulation of the vascular system. The vasculature’s morphogenesis in patients with CRS, is similarly affected by inflammatory triggers and responses where inflammation drives the process of vasculature development leading to neoangiogenesis, increase in vascular permeability and an increase in disruption of blood vessels.

There are several limitations that should be acknowledged. Sample size may contribute to sampling bias considering CRS is a complicated and heterogenous disease. The nanostring gene expression arrays have a limited amount of pro-angiogenic genes available. Future investigations using larger and more robust screening tools would enable screening a much larger number of pro-angiogenic genes.

Conclusion

Overall vascularity and increased expression of pro-angiogenic genes are significantly increased in patients with CRS compared to controls. These results help define the inflammation-driven neoangiogenesis observed in patients with CRS. Further, increased interendothelial junction gaps and increased morphological changes in the blood vessels of patients with CRS suggests increased vascular permeability in the sinonasal tissue. These data collectively help characterize the inflammation-driven vascular dysregulation observed in patients with CRS.