Dataset Information

Combined Single Nucleotide Variants of ORAI1 and BLK in a Child with Refractory Kawasaki Disease.

ABSTRACT: Kawasaki disease (KD) is a systemic vasculitis with an unknown etiology affecting young children. Although intravenous immunoglobulin (IVIG) plus acetylsalicylic acid is effective in most cases, approximately 10-20% of patients do not respond to this therapy. An 8-month-old boy was admitted to a local hospital with the presumptive diagnosis of KD. He received IVIG twice and four series of methylprednisolone pulse therapy from the third to the tenth day of illness. Despite these treatments, his fever persisted with the development of moderate dilatations of the coronary arteries. A diagnosis of refractory KD was made, and infliximab with oral prednisolone was administered without success. Defervescence was finally achieved by cyclosporine A, an inhibitor of the signaling pathway of the calcineurin/nuclear factor of activated T cells (NFAT). Whole-genome sequencing of his deoxyribonucleic acid samples disclosed two single nucleotide variants (SNVs) in disease-susceptibility genes in Japanese KD patients, ORAI1 (rs3741596) and BLK (rs2254546). In summary, the refractory nature of the present case could be explained by the presence of combined SNVs in susceptibility genes associated with upregulation of the calcineurin/NFAT signaling pathway. It may provide insights for stratifying KD patients based on the SNVs in their susceptibility genes.

SUBMITTER: Kanda S

PROVIDER: S-EPMC8224368 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

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Publications

Combined Single Nucleotide Variants of <i>ORAI1</i> and <i>BLK</i> in a Child with Refractory Kawasaki Disease.

Kanda Saki S Fujii Yoshimitsu Y Hori Shin-Ichiro SI Ohmachi Taichi T Yoshimura Ken K Higasa Koichiro K Kaneko Kazunari K

Children (Basel, Switzerland) 20210521 6

Kawasaki disease (KD) is a systemic vasculitis with an unknown etiology affecting young children. Although intravenous immunoglobulin (IVIG) plus acetylsalicylic acid is effective in most cases, approximately 10-20% of patients do not respond to this therapy. An 8-month-old boy was admitted to a local hospital with the presumptive diagnosis of KD. He received IVIG twice and four series of methylprednisolone pulse therapy from the third to the tenth day of illness. Despite these treatments, his f ...[more]

PMID: 34064199

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Project description:BackgroundIn recent years the number of human genetic variants deposited into the publicly available databases has been increasing exponentially. The latest version of dbSNP, for example, contains ~50 million validated Single Nucleotide Variants (SNVs). SNVs make up most of human variation and are often the primary causes of disease. The non-synonymous SNVs (nsSNVs) result in single amino acid substitutions and may affect protein function, often causing disease. Although several methods for the detection of nsSNV effects have already been developed, the consistent increase in annotated data is offering the opportunity to improve prediction accuracy.ResultsHere we present a new approach for the detection of disease-associated nsSNVs (Meta-SNP) that integrates four existing methods: PANTHER, PhD-SNP, SIFT and SNAP. We first tested the accuracy of each method using a dataset of 35,766 disease-annotated mutations from 8,667 proteins extracted from the SwissVar database. The four methods reached overall accuracies of 64%-76% with a Matthew's correlation coefficient (MCC) of 0.38-0.53. We then used the outputs of these methods to develop a machine learning based approach that discriminates between disease-associated and polymorphic variants (Meta-SNP). In testing, the combined method reached 79% overall accuracy and 0.59 MCC, ~3% higher accuracy and ~0.05 higher correlation with respect to the best-performing method. Moreover, for the hardest-to-define subset of nsSNVs, i.e. variants for which half of the predictors disagreed with the other half, Meta-SNP attained 8% higher accuracy than the best predictor.ConclusionsHere we find that the Meta-SNP algorithm achieves better performance than the best single predictor. This result suggests that the methods used for the prediction of variant-disease associations are orthogonal, encoding different biologically relevant relationships. Careful combination of predictions from various resources is therefore a good strategy for the selection of high reliability predictions. Indeed, for the subset of nsSNVs where all predictors were in agreement (46% of all nsSNVs in the set), our method reached 87% overall accuracy and 0.73 MCC. Meta-SNP server is freely accessible at http://snps.biofold.org/meta-snp.

Dataset Information

Combined Single Nucleotide Variants of ORAI1 and BLK in a Child with Refractory Kawasaki Disease.

Publications

Combined Single Nucleotide Variants of <i>ORAI1</i> and <i>BLK</i> in a Child with Refractory Kawasaki Disease.

Similar Datasets

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