Predictive model based on gene and laboratory data for intravenous immunoglobulin resistance in Kawasaki disease in a Chinese population
Abstract Background Here, we investigated the predictive efficiency of a newly developed model based on single nucleotide polymorphisms (SNPs) and laboratory data for intravenous immunoglobulin (IVIG) resistance in Kawasaki disease (KD) in a Chinese population. Methods Data relating to children with...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2021-06-01
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| Series: | Pediatric Rheumatology Online Journal |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12969-021-00582-6 |
| _version_ | 1818441031367000064 |
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| author | Li Meng Zhen Zhen Qian Jiang Xiao-hui Li Yue Yuan Wei Yao Ming-ming Zhang Ai-jie Li Lin Shi |
| author_facet | Li Meng Zhen Zhen Qian Jiang Xiao-hui Li Yue Yuan Wei Yao Ming-ming Zhang Ai-jie Li Lin Shi |
| author_sort | Li Meng |
| collection | DOAJ |
| description | Abstract Background Here, we investigated the predictive efficiency of a newly developed model based on single nucleotide polymorphisms (SNPs) and laboratory data for intravenous immunoglobulin (IVIG) resistance in Kawasaki disease (KD) in a Chinese population. Methods Data relating to children with KD were acquired from a single center between December 2015 and August 2019 and used to screen target SNPs. We then developed a predictive model of IVIG resistance using previous laboratory parameters. We then validated our model using data acquired from children with KD attending a second center between January and December 2019. Results Analysis showed that rs10056474 GG, rs746994GG, rs76863441GT, rs16944 (CT/TT), and rs1143627 (CT/CC), increased the risk of IVIG-resistance in KD patients (odds ratio, OR > 1). The new predictive model, which combined SNP data with a previous model derived from laboratory data, significantly increased the area under the receiver-operator-characteristic curves (AUC) (0.832, 95% CI: 0.776-0.878 vs 0.793, 95%CI:0.734-0.844, P < 0.05) in the development dataset, and (0.820, 95% CI: 0.730-0.889 vs 0.749, 95% CI: 0.652-0.830, P < 0.05) in the validation dataset. The sensitivity and specificity of the new assay were 65.33% (95% CI: 53.5-76.0%) and 86.67% (95% CI: 80.2-91.7%) in the development dataset and 77.14% (95% CI: 59.9-89.6%) and 86.15% (95% CI: 75.3-93.5%) in the validation dataset. Conclusion Analysis showed that rs10056474 and rs746994 in the SMAD5 gene, rs76863441 in the PLA2G7 gene, and rs16944 or rs1143627 in the interleukin (IL)-1B gene, were associated with IVIG resistant KD in a Chinese population. The new model combined SNPs with laboratory data and improved the predictve efficiency of IVIG-resistant KD. |
| first_indexed | 2024-12-14T18:21:47Z |
| format | Article |
| id | doaj.art-8e8b53dd296845a3a727262a92f5e9eb |
| institution | Directory Open Access Journal |
| issn | 1546-0096 |
| language | English |
| last_indexed | 2024-12-14T18:21:47Z |
| publishDate | 2021-06-01 |
| publisher | BMC |
| record_format | Article |
| series | Pediatric Rheumatology Online Journal |
| spelling | doaj.art-8e8b53dd296845a3a727262a92f5e9eb2022-12-21T22:52:03ZengBMCPediatric Rheumatology Online Journal1546-00962021-06-0119111010.1186/s12969-021-00582-6Predictive model based on gene and laboratory data for intravenous immunoglobulin resistance in Kawasaki disease in a Chinese populationLi Meng0Zhen Zhen1Qian Jiang2Xiao-hui Li3Yue Yuan4Wei Yao5Ming-ming Zhang6Ai-jie Li7Lin Shi8Capital Institute of Pediatrics-Peking University Teaching HospitalDepartment of Cardiology, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s HealthDepartment of Genetics, Capital Institute of PediatricsCapital Institute of Pediatrics-Peking University Teaching HospitalDepartment of Cardiology, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s HealthDepartment of Cardiology, Children’s Hospital Capital Institute of PediatricsDepartment of Cardiology, Children’s Hospital Capital Institute of PediatricsDepartment of Cardiology, Children’s Hospital Capital Institute of PediatricsDepartment of Cardiology, Children’s Hospital Capital Institute of PediatricsAbstract Background Here, we investigated the predictive efficiency of a newly developed model based on single nucleotide polymorphisms (SNPs) and laboratory data for intravenous immunoglobulin (IVIG) resistance in Kawasaki disease (KD) in a Chinese population. Methods Data relating to children with KD were acquired from a single center between December 2015 and August 2019 and used to screen target SNPs. We then developed a predictive model of IVIG resistance using previous laboratory parameters. We then validated our model using data acquired from children with KD attending a second center between January and December 2019. Results Analysis showed that rs10056474 GG, rs746994GG, rs76863441GT, rs16944 (CT/TT), and rs1143627 (CT/CC), increased the risk of IVIG-resistance in KD patients (odds ratio, OR > 1). The new predictive model, which combined SNP data with a previous model derived from laboratory data, significantly increased the area under the receiver-operator-characteristic curves (AUC) (0.832, 95% CI: 0.776-0.878 vs 0.793, 95%CI:0.734-0.844, P < 0.05) in the development dataset, and (0.820, 95% CI: 0.730-0.889 vs 0.749, 95% CI: 0.652-0.830, P < 0.05) in the validation dataset. The sensitivity and specificity of the new assay were 65.33% (95% CI: 53.5-76.0%) and 86.67% (95% CI: 80.2-91.7%) in the development dataset and 77.14% (95% CI: 59.9-89.6%) and 86.15% (95% CI: 75.3-93.5%) in the validation dataset. Conclusion Analysis showed that rs10056474 and rs746994 in the SMAD5 gene, rs76863441 in the PLA2G7 gene, and rs16944 or rs1143627 in the interleukin (IL)-1B gene, were associated with IVIG resistant KD in a Chinese population. The new model combined SNPs with laboratory data and improved the predictve efficiency of IVIG-resistant KD.https://doi.org/10.1186/s12969-021-00582-6Kawasaki diseaseIntravenous immunoglobulin resistanceSingle nucleotide polymorphism |
| spellingShingle | Li Meng Zhen Zhen Qian Jiang Xiao-hui Li Yue Yuan Wei Yao Ming-ming Zhang Ai-jie Li Lin Shi Predictive model based on gene and laboratory data for intravenous immunoglobulin resistance in Kawasaki disease in a Chinese population Pediatric Rheumatology Online Journal Kawasaki disease Intravenous immunoglobulin resistance Single nucleotide polymorphism |
| title | Predictive model based on gene and laboratory data for intravenous immunoglobulin resistance in Kawasaki disease in a Chinese population |
| title_full | Predictive model based on gene and laboratory data for intravenous immunoglobulin resistance in Kawasaki disease in a Chinese population |
| title_fullStr | Predictive model based on gene and laboratory data for intravenous immunoglobulin resistance in Kawasaki disease in a Chinese population |
| title_full_unstemmed | Predictive model based on gene and laboratory data for intravenous immunoglobulin resistance in Kawasaki disease in a Chinese population |
| title_short | Predictive model based on gene and laboratory data for intravenous immunoglobulin resistance in Kawasaki disease in a Chinese population |
| title_sort | predictive model based on gene and laboratory data for intravenous immunoglobulin resistance in kawasaki disease in a chinese population |
| topic | Kawasaki disease Intravenous immunoglobulin resistance Single nucleotide polymorphism |
| url | https://doi.org/10.1186/s12969-021-00582-6 |
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