[Characterization of genetic variants in children with refractory epilepsy].

OBJECTIVE: To analyze the characteristics of genetic variants among children with refractory epilepsy (RE). METHODS: One hundred and seventeen children with RE who had presented at the Affiliated Jinhua Hospital of Zhejiang University School of Medicine from January 1, 2018 to November 21, 2019 were selected as the study subjects. The children were divided into four groups according to their ages of onset: < 1 year old, 1 ~ 3 years old, 3 ~ 12 years old, and >= 12 years old. Clinical data and results of trio-whole exome sequencing were retrospectively analyzed. RESULTS: In total 67 males and 50 females were included. The age of onset had ranged from 4 days to 14 years old. Among the 117 patients, 33 (28.21%) had carried pathogenic or likely pathogenic variants. The detection rates for the < 1 year old, 1 ~ 3 years old and >= 3 years old groups were 53.85% (21/39), 12.00% (3/25) and 16.98% (9/53), respectively, with a significant difference among the groups (χ2 = 19.202, P < 0.001). The detection rates for patients with and without comorbidities were 33.33% (12/36) and 25.93% (21/81), respectively (χ2 = 0.359, P = 0.549). Among the 33 patients carrying genetic variants, 27 were single nucleotide polymorphisms (SNPs) or insertion/deletions (InDels), and 6 were copy number variations (CNVs). The most common mutant genes were PRRT2 (15.15%, 5/33) and SCN1A (12.12%, 4/33). Among children carrying genetic variants, 72.73% (8/11) had attained clinical remission after adjusting the medication according to the references. CONCLUSION: 28.21% of RE patients have harbored pathogenic or likely pathogenic variants or CNVs. The detection rate is higher in those with younger age of onset. PRRT2 and SCN1A genes are more commonly involved. Adjusting medication based on the types of affected genes may facilitate improvement of the remission rate.

EasyAmplicon: An easy-to-use, open-source, reproducible, and community-based pipeline for amplicon data analysis in microbiome research.

It is difficult for beginners to learn and use amplicon analysis software because there are so many software tools to choose from, and all of them need multiple steps of operation. Herein, we provide a cross-platform, open-source, and community-supported analysis pipeline EasyAmplicon. EasyAmplicon has most of the modules needed for an amplicon analysis, including data quality control, merging of paired-end reads, dereplication, clustering or denoising, chimera detection, generation of feature tables, taxonomic diversity analysis, compositional analysis, biomarker discovery, and publication-quality visualization. EasyAmplicon includes more than 30 cross-platform modules and R packages commonly used in the field. All steps of the pipeline are integrated into RStudio, which reduces learning costs, keeps the flexibility of the analysis process, and facilitates personalized analysis. The pipeline is maintained and updated by the authors and editors of WeChat official account "Meta-genome." Our team will regularly release the latest tutorials both in Chinese and English, read the feedback from users, and provide help to them in the WeChat account and GitHub. The pipeline can be deployed on various platforms, and the installation time is less than half an hour. On an ordinary laptop, the whole analysis process for dozens of samples can be completed within 3 h. The pipeline is available at GitHub (https://github.com/YongxinLiu/EasyAmplicon) and Gitee (https://gitee.com/YongxinLiu/EasyAmplicon).

Sudden Hypotension and Increased Serum Interferon-γ and Interleukin-10 Predict Early Macrophage Activation Syndrome in Patients with Systemic Juvenile Idiopathic Arthritis.

OBJECTIVE: To identify clinical and laboratory predictors for early macrophage activation syndrome (MAS) associated with systemic juvenile idiopathic arthritis (sJIA). STUDY DESIGN: This is a retrospective cohort study of 149 patients with sJIA, of whom 27 had 31 episodes of MAS. We evaluated the clinical and laboratory features of patients with sJIA and MAS and compared them with those without MAS. We focused our analysis on the overall process of MAS development, especially MAS onset. RESULTS: As shown in previous studies, we found a high percentage of fever, absence of arthritis, and central nervous system dysfunction at MAS onset in our study cohort. We also found that 35% of patients with MAS had hypotension although not shock, and 22.6% of patients with MAS had gastrointestinal involvement at MAS onset. Compared with patients with MAS without hypotension, patients with MAS and hypotension had greater rates of admission to the intensive care unit; presented with more arthritis, serositis, pneumonia, and gastrointestinal involvement; and had greater white blood cell and absolute neutrophil counts and serum bilirubin levels and lower serum total protein. We confirmed laboratory markers such as platelet counts, lactate dehydrogenase, and aspartate aminotransferase can help to identify early MAS and that ferritin/erythrocyte sedimentation rate ratio of approximately 20.0 had a high diagnostic sensitivity and specificity for MAS. In addition, we discovered that the combination of interferon-γ >17.1 pg/mL and interleukin-10 >7.8 pg/mL appeared to be a good cytokine pattern for the recognition of MAS onset. CONCLUSIONS: Sudden hypotension, elevated ferritin/erythrocyte sedimentation rate ratio, and the cytokine pattern of significantly increased interferon-γ and interleukin-10 levels are important markers for early identification of MAS in addition to the traditional characteristics of sJIA-associated MAS.

A practical guide to amplicon and metagenomic analysis of microbiome data.

Advances in high-throughput sequencing (HTS) have fostered rapid developments in the field of microbiome research, and massive microbiome datasets are now being generated. However, the diversity of software tools and the complexity of analysis pipelines make it difficult to access this field. Here, we systematically summarize the advantages and limitations of microbiome methods. Then, we recommend specific pipelines for amplicon and metagenomic analyses, and describe commonly-used software and databases, to help researchers select the appropriate tools. Furthermore, we introduce statistical and visualization methods suitable for microbiome analysis, including alpha- and beta-diversity, taxonomic composition, difference comparisons, correlation, networks, machine learning, evolution, source tracing, and common visualization styles to help researchers make informed choices. Finally, a step-by-step reproducible analysis guide is introduced. We hope this review will allow researchers to carry out data analysis more effectively and to quickly select the appropriate tools in order to efficiently mine the biological significance behind the data.

A guide to human microbiome research: study design, sample collection, and bioinformatics analysis.

The purpose of this review is to provide medical researchers, especially those without a bioinformatics background, with an easy-to-understand summary of the concepts and technologies used in microbiome research. First, we define primary concepts such as microbiota, microbiome, and metagenome. Then, we discuss study design schemes, the methods of sample size calculation, and the methods for improving the reliability of research. We emphasize the importance of negative and positive controls in this section. Next, we discuss statistical analysis methods used in microbiome research, focusing on problems with multiple comparisons and ways to compare ß-diversity between groups. Finally, we provide step-by-step pipelines for bioinformatics analysis. In summary, the meticulous study design is a key step to obtaining meaningful results, and appropriate statistical methods are important for accurate interpretation of microbiome data. The step-by-step pipelines provide researchers with insights into newly developed bioinformatics analysis methods.

Gut microbiota in children with juvenile idiopathic arthritis: characteristics, biomarker identification, and usefulness in clinical prediction.

BACKGROUND: Recent studies have suggested that the gut microbiota is altered in children with juvenile idiopathic arthritis (JIA). However, age, sex, and body mass index (BMI) were not matched in the previous studies, and the results are inconsistent. We conducted an age-, sex-, and BMI-matched cross-sectional study to characterize the gut microbiota in children with JIA, and evaluate its potential in clinical prediction. METHODS: A total of 40 patients with JIA and 42 healthy controls, ranging from 1 to 16 years, were enrolled in this study. Fecal samples were collected for 16S rDNA sequencing. The data were analyzed using QIIME software and R packages. Specifically, the random forest model was used to identify biomarkers, and the receiver operating characteristic curve and the decision curve analysis were used to evaluate model performance. RESULTS: A total of 39 fecal samples from patients with JIA, and 42 fecal samples from healthy controls were sequenced successfully. The Chao 1 and Shannon-Wiener index in the JIA group were significantly lower than those in the control group, and the Bray-Curtis dissimilarity also differed significantly between the two groups. The relative abundance of 4 genera, Anaerostipes, Dialister, Lachnospira, and Roseburia, decreased significantly in the JIA group compared to those in the control group. The 4 genera included microbes that produce short-chain fatty acids (SCFAs) and were negatively correlated with some rheumatic indices. Moreover, 12 genera were identified as potential biomarkers by using the nested cross-validation function of the random forest. A random forest model constructed using these genera was able to differentiate the patients with JIA from the healthy controls, and the area under the receiver operating characteristic curve was 0.7975. The decision curve analysis indicated that the model had usefulness in clinical practice. CONCLUSIONS: The gut microbiota in patients with JIA is altered and characterized by a decreased abundance of 4 SCFA-producing genera. The decreases in the 4 genera correlated with more serious clinical indices. Twelve genera could be used as biomarkers and predictors in clinical practice. TRIAL REGISTRATION: The study is registered online at the Chinese Clinical Trial Registry on 11 May 2018 (registration number: ChiCTR1800016110).

A randomized controlled trial of a mobile application-assisted nurse-led model used to improve treatment outcomes in children with asthma.

AIM: To evaluate the effectiveness of a mobile application-assisted nurse-led management model in childhood asthma. BACKGROUND: Studies have shown that a nurse-led asthma management model can improve asthma outcomes. However, the role of a mobile application-assisted nurse-led model in paediatric asthma management has not been studied well. DESIGN: A multi-centre randomized clinical trial. METHODS: The trial was conducted between March 2017-March 2018. A total of 152 children (6 to 11.9 years old) were enrolled, with 77 children in the experimental group and 75 in the control group. All children received nurse-led asthma management and other routine treatment measures, including inhaled corticosteroids. Meanwhile, a mobile application was used to manage asthma only for children in the experimental group. Primary outcome was frequency of asthma exacerbations. All outcomes were evaluated twice a month for 12 months. RESULTS: Compared with the pre-enrollment period, frequency of asthma exacerbations decreased in the post-enrollment period in the two groups, with a greater decrease in the experimental group. Compared with children in the control group, children in the experimental group had better secondary outcomes, such as improved adherence, higher Childhood Asthma Control Test scores, decreased respiratory tract infections, days of antibiotic use, days of school absence, parental work loss, and medical expenses. CONCLUSION: A mobile application-assisted nurse-led management model decreased asthma exacerbations and improved secondary outcomes in children with asthma. Further research is needed to verify its validity in larger population samples. IMPACT: Children with asthma benefited from a nurse-led asthma management model when combined with mobile application. This trial suggested that computer and Internet technologies should be incorporated into nurse-led asthma strategy in paediatric asthma management. TRIAL REGISTRATION: The current trial was registered online with the Chinese Clinical Trial Registry (registration number: ChiCTR1800016726).

Association of STAT6 variants with asthma risk: a systematic review and meta-analysis.

A large number of studies have reported that the genetic variants in STAT6 gene may be implicated in susceptibility to asthma, but with inconsistent results. Therefore, the aim of this meta-analysis was to determine the likelihood of developing asthma for the individuals with different STAT6 variants. The database including Pubmed, Embase and CNKI (Chinese National Knowledge Infrastructure) were searched to find the relevant papers. Data were extracted by two independent reviewers and the odds radios (ORs) were pooled with 95% confidence intervals (CIs), using random effect or fixed effect models as appropriate, to indicate the risk of asthma for different STAT6 variants. The heterogeneity and bias were tested for each pooled result. Data from 19 studies were pooled that reported associations of rs324015, rs71802646 and rs324011 in STAT6 gene with asthma risk. The results demonstrated that 13GT and short GT in rs71802646 were both associated with increased risk of asthma in overall analysis (OR = 1.26 for 13GT and 1.30 for short GT). Further, subgroup analysis showed an increased risk of asthma in Asian population with 13GT (OR = 1.21), 14GT (OR = 1.97) and short GT (OR = 1.27). Besides, 13GT, 14GT and short GT all contributed to higher risk of atopic asthma, with OR 1.50, 2.21 and 1.65 respectively. However, rs324015 (G>A) appeared to be associated with decreased risk for atopic asthma (with OR = 0.83, 0.68 and 0.79 for A, AA and AA+AG respectively). Both overall and subgroup analyses indicated no effect of rs324011 on asthma risk. In conclusion, our meta-analyses suggest that short GT repeats of rs71802646 in STAT6 contribute to higher risk for asthma, while rs324015 may have a protective effect on atopic asthma.

[Association of single nucleotide polymorphisms in the promoter region of the TLR9 gene with childhood atopic asthma].

OBJECTIVE: To investigate the distribution characteristics of the single nucleotide polymorphisms (SNPs) in the promoter region of the toll-like receptor 9 gene (TLR9) in Chinese Han children from Zhejiang province, and their associations with asthma susceptibility and phenotypes. METHODS: A case-control study was conducted. A total of 312 asthmatic children aged between 1.9 and 11.6 and 339 age matched healthy controls were enrolled in this study from April 2007 to November 2008. The -1486 C/T in rs187084 and -1237 C/T in rs5743836 loci of the TLR9 gene were genotyped by direct DNA sequencing of the PCR products. Serum levels of IFN gamma, IL-12 and IL-4 were detected by enzyme linked immunosorbent assay.Serum levels of total IgE were detected by chemiluminescence, and serum levels of antigen specific IgE antibodies were detected by fluoroenzymeimmunoassay. RESULTS: (1) The -1486 C/T polymorphism was identified in both groups. The genotype frequencies of TT, TC and CC at -1486 C/T were 41.0%, 44.3%, 14.7% in the healthy controls, and 38.8%, 48.4%, 12.8% in the asthmatic children. The -1237 C/T polymorphism was not detected in the population. (2) There were no statistically significant differences in the allele and genotype frequencies at the -1486 C/T locus between the two groups (P;>0.05). (3) Serum levels of IFN gamma and IL-4 differed significantly among the three genotypes at the -1486 C/T locus in asthmatic children (P<0.01). The CC genotype had the lowest levels of serum IFN gamma and the highest levels of serum IL-4 among the three genotypes. There were no significant differences in these cytokines among the healthy controls (P>0.05). No statistical differences of serum IL-12 were found among the three genotypes in the two groups (P>0.05). (4) There were no significant differences of total IgE (log-transformed) among the three genotypes in the asthmatic children (P>0.05). CONCLUSION: The -1237 C/T polymorphism of TLR9 gene was not detected in Chinese Han children in this study. The -1486 C/T polymorphism was associated with the levels of serum IFN gamma and IL-4 in children with asthma. However, there were no correlations between the -1486C/T polymorphism and serum IL-12 levels, total IgE levels or asthmatic susceptibility.

[Effects of montelukast and BCG-PSN on the expression of STAT5b mRNA and IL-4 mRNA in blood mononuclearcells of rats with asthma].

OBJECTIVE: To study the expression of signal transducer and activator of transcription 5b (STAT5b) mRNA and interleukin-4 (IL-4) mRNA in blood mononuclearcells in a rat model of asthma and the effect of montelukast (MK) and BCG-polysaccharide and nucleic acid injection (BCG-PSN) on STAT5b mRNA and IL-4 mRNA expression. METHODS: Fifty-two male Sprague-Dawley rats (weight:140-200 g) were randomly divided into four groups: asthma, MK treated and BCG-PSN-treated and control groups. Rat model of asthma was prepared by ovalbumin (OVA) sensitization. The rats were sacrificed 24 hrs after the last sensitization. Blood eosinophils (EOS) were counted. Plasma contens of IL-4 and interferon-gamma (IFN-gamma) were measured using ELISA. Expression of STAT5b mRNA and IL-4 mRNA in blood mononuclearcells was detected with SYBR GREEN I fluorescent quantitation PCR method. RESULTS: Blood contents of STAT5b mRNA and IL-4 mRNA in the untreated asthma group were significantly higher than those in the other three groups (<0.01). Blood EOS count and plasma IL-4 contents in the untreated asthma group significantly increased, while plasma IFN-gamma contents significantly decreased compared with the other three groups (<0.01). There were no significant differences in the parameters measured among the MK-treated, the BCG-PSNjtreated and the control groups. STAT5b mRNA expression was positively correlated to IL-4 mRNA expression, IL-4 content and EOS count (r=0.730,0.650, 0.664, respectively; <0.01), but negatively correlated to IFN-gamma content (r=-0.798; <0.01). CONCLUSIONS: STAT5b mRNA and IL-4 mRNA were strongly expressed in blood mononuclearcells in rats with asthma, and there was a positive correlation between them. MK and BCG-PSN had inhibitory effects on the expression of STAT5b mRNA and IL-4 mRNA, which might be contributed to suppression of airway inflammation in asthma.