Aspirin-exacerbated respiratory disease (AERD) is a nonallergic clinical syndrome characterized by a severe decline in forced expiratory volume in one second (FEV1) following the ingestion of non-steroidal anti-inflammatory drugs (NSAIDs) such as aspirin. The effects of genetic variants have not fully explained all of the observed individual differences to an aspirin challenge despite previous attempts to identify AERD-related genes. In the present study, we performed genome-wide association study (GWAS) and targeted association study in Korean asthmatics to identify new genetic factors associated with AERD. A total of 685 asthmatic patients without AERD and 117 subjects with AERD were used for the GWAS of the first stage, and 996 asthmatics without AERD and 142 subjects with AERD were used for a follow-up study. A total of 702 SNPs were genotyped using the GoldenGate assay with the VeraCode microbead. GWAS revealed the top-ranked variants in 3' regions of the HLA-DPB1 gene. To investigate the detailed genetic effects of an associated region with the risk of AERD, a follow-up targeted association study with the 702 single nucleotide polymorphisms (SNPs) of 14 genes was performed on 802 Korean subjects. In a case-control analysis, HLA-DPB1 rs1042151 (Met105Val) shows the most significant association with the susceptibility of AERD (p = 5.11 × 10(-7); OR = 2.40). Moreover, rs1042151 also shows a gene dose for the percent decline of FEV1 after an aspirin challenge (p = 2.82 × 10(-7)). Our findings show that the HLA-DPB1 gene polymorphism may be the most susceptible genetic factor for the risk of AERD in Korean asthmatics and confirm the importance of HLA-DPB1 in the genetic etiology of AERD.
Bioink based 3D bioprinting is a promising new technology that enables fabrication of complex tissue structures with living cells. The printability of the bioink depends on the physical properties such as viscosity. However, the high viscosity bioink puts shear stress on the cells and low viscosity bioink cannot maintain complex tissue structure firmly after the printing. In this work, we applied dual crosslinkable bioink using Kappa-carrageenan (κ-CA) to overcome existing shortcomings. κ-CA has properties such as biocompatibility, biodegradability, shear-thinning and ionic gelation but the difficulty of controlling gelation properties makes it unsuitable for application in 3D bioprinting. This problem was solved by synthesizing methacrylated Kappa-carrageenan (MA-κ-CA), which can be dual crosslinked through ionic and UV (Ultraviolet) crosslinking to form hydrogel using NIH-3T3 cells. Through MA substitutions, the rheological properties of the gel could be controlled to reduce the shear stress. Moreover, bioprinting using the cell-laden MA-κ-CA showed cell compatibility with enhanced shape retention capability. The potential to control the physical properties through dual crosslinking of MA-κ-CA hydrogel is expected to be widely applied in 3D bioprinting applications.
The aim of the present study was to develop a diagnostic set of single-nucleotide polymorphisms (SNPs) for discriminating aspirin-exacerbated respiratory disease (AERD) from aspirin-tolerant asthma (ATA) using the genome-wide association study (GWAS) data; the GWAS data were filtered according to p-values and odds ratios (ORs) using PLINK software, and the 10 candidate SNPs most closely associated with AERD were selected, based on 100 AERD and 100 ATA subjects. Using multiple logistic regression and receiver-operating characteristic (ROC) curve analysis, eight SNPs were chosen as the best model for distinguishing between AERD and ATA. The relative risk for AERD in each subject was calculated based on the relative risk of each of the eight SNPs. Ten of the original 109,365 SNPs highly associated (filtered with p<0.001 and ORs) with the risk for AERD were selected. A combination model of the eight SNPs among the 10 SNPs showed the highest area under the ROC curve of 0.9. The overall relative risk for AERD based on the eight SNPs was significantly different between the AERD and ATA groups (p=2.802E-21), and the sensitivity and specificity were 78% and 88%, respectively. The candidate set of eight SNPs may be useful in predicting the risk for AERD.
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