Original Article
Identification of therapeutic targets for childhood severe asthmatics with DNA microarray
a Department of Pediatrics, Shanghai East Hospital, Shanghai East Hospital of Tongji University, 200120 Shanghai, China
b Department of Pediatrics, Changzheng Hospital Affiliated to the SMMU, 200003 Shanghai, China
c Department of Clinical Pharmacy, College of Pharmacy, China Pharmaceutical University, 211198 Nanjing, China
d Department of Pediatrics, Zhabei District Central Hospital, 200070 Shanghai, China
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DRESS. Positive LTT for phenytoin. <span class="elsevierStyleItalic">X</span> axis: phenytoin and PHA concentration in μg/mL. <span class="elsevierStyleItalic">Y</span> axis: SI (stimulation index: proliferation with drug/proliferation without drug). Positive LTT for phenytoin (SI<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>3 in two concentrations of drug).</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "M.T. Belver, A. Michavila, I. Bobolea, M. Feito, T. Bellón, S. Quirce" "autores" => array:6 [ 0 => array:2 [ "nombre" => "M.T." "apellidos" => "Belver" ] 1 => array:2 [ "nombre" => "A." "apellidos" => "Michavila" ] 2 => array:2 [ "nombre" => "I." "apellidos" => "Bobolea" ] 3 => array:2 [ "nombre" => "M." "apellidos" => "Feito" ] 4 => array:2 [ "nombre" => "T." "apellidos" => "Bellón" ] 5 => array:2 [ "nombre" => "S." "apellidos" => "Quirce" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0301054615000749?idApp=UINPBA00004N" "url" => "/03010546/0000004400000001/v1_201601070106/S0301054615000749/v1_201601070106/en/main.assets" ] "itemAnterior" => array:18 [ "pii" => "S0301054615000907" "issn" => "03010546" "doi" => "10.1016/j.aller.2015.04.004" "estado" => "S300" "fechaPublicacion" => "2016-01-01" "aid" => "691" "copyright" => "SEICAP" "documento" => "article" "crossmark" => 1 "subdocumento" => "fla" "cita" => "Allergol Immunopathol (Madr). 2016;44:66-75" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:2 [ "total" => 1228 "formatos" => array:3 [ "EPUB" => 12 "HTML" => 739 "PDF" => 477 ] ] "en" => array:12 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original Article</span>" "titulo" => "Induction of nasal polyps using house dust mite and <span class="elsevierStyleItalic">Staphylococcal</span> enterotoxin B in C57BL/6 mice" "tienePdf" => "en" "tieneTextoCompleto" => "en" "tieneResumen" => "en" "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "66" "paginaFinal" => "75" ] ] "contieneResumen" => array:1 [ "en" => true ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0015" "etiqueta" => "Figure 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 3239 "Ancho" => 2574 "Tamanyo" => 604256 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Representative sections of eosinophilic infiltration and total IgE production. (A–D) The presence of eosinophils was detected in groups B, C and D. Increased numbers of eosinophils were observed in groups C and D, with no significant difference in eosinophil distributions between groups C and D. (E) The numbers of eosinophils infiltrating the nasal mucosa were counted based on the Sirius red-stained sections. Data are expressed as means<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>SD. (F) The level of total IgE from serum was measured by enzyme-linked immunosorbent assay (ELISA). 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"apellidos" => "Kim" ] 3 => array:2 [ "nombre" => "J.-W." "apellidos" => "Park" ] 4 => array:2 [ "nombre" => "H.-W." "apellidos" => "Shin" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0301054615000907?idApp=UINPBA00004N" "url" => "/03010546/0000004400000001/v1_201601070106/S0301054615000907/v1_201601070106/en/main.assets" ] "en" => array:18 [ "idiomaDefecto" => true "cabecera" => "<span class="elsevierStyleTextfn">Original Article</span>" "titulo" => "Identification of therapeutic targets for childhood severe asthmatics with DNA microarray" "tieneTextoCompleto" => true "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "76" "paginaFinal" => "82" ] ] "autores" => array:1 [ 0 => array:3 [ "autoresLista" => "Y. Wu, J.-F. Zhang, T. Xu, L. Xu, J. Qiao, F. Liu, H. Shan, X. Jiang" "autores" => array:8 [ 0 => array:3 [ "nombre" => "Y." "apellidos" => "Wu" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 1 => array:4 [ "nombre" => "J.-F." "apellidos" => "Zhang" "email" => array:1 [ 0 => "jinfengzhangjfz@163.com" ] "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">*</span>" "identificador" => "cor0005" ] ] ] 2 => array:3 [ "nombre" => "T." "apellidos" => "Xu" "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">b</span>" "identificador" => "aff0010" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">**</span>" "identificador" => "cor0010" ] ] ] 3 => array:3 [ "nombre" => "L." "apellidos" => "Xu" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">c</span>" "identificador" => "aff0015" ] ] ] 4 => array:3 [ "nombre" => "J." "apellidos" => "Qiao" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 5 => array:3 [ "nombre" => "F." "apellidos" => "Liu" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 6 => array:3 [ "nombre" => "H." "apellidos" => "Shan" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">d</span>" "identificador" => "aff0020" ] ] ] 7 => array:3 [ "nombre" => "X." "apellidos" => "Jiang" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] ] "afiliaciones" => array:4 [ 0 => array:3 [ "entidad" => "Department of Pediatrics, Shanghai East Hospital, Shanghai East Hospital of Tongji University, 200120 Shanghai, China" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Department of Pediatrics, Changzheng Hospital Affiliated to the SMMU, 200003 Shanghai, China" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Department of Clinical Pharmacy, College of Pharmacy, China Pharmaceutical University, 211198 Nanjing, China" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Department of Pediatrics, Zhabei District Central Hospital, 200070 Shanghai, China" "etiqueta" => "d" "identificador" => "aff0020" ] ] ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0025" "etiqueta" => "Figure 5" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr5.jpeg" "Alto" => 2222 "Ancho" => 3203 "Tamanyo" => 343629 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Significant pathways enriched by common DEGs. Pink box is the differentially expressed genes.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Asthma is the most common chronic inflammatory disease in airways of children, and which has a significant effect on substantial daily lives of individuals.<a class="elsevierStyleCrossRef" href="#bib0220"><span class="elsevierStyleSup">1</span></a> Asthma can result in variable and recurring symptoms including airflow obstruction, bronchospasm, chest tightness and shortness of breath.<a class="elsevierStyleCrossRefs" href="#bib0225"><span class="elsevierStyleSup">2,3</span></a> The combination of genetic and environment factors has been documented to contribute to the onset of asthma.<a class="elsevierStyleCrossRef" href="#bib0235"><span class="elsevierStyleSup">4</span></a> The increasing trend in the prevalence of childhood asthma has been reported since 1980s.<a class="elsevierStyleCrossRef" href="#bib0240"><span class="elsevierStyleSup">5</span></a> It is reported that approximate 300 million people suffered asthma worldwide in 2011<a class="elsevierStyleCrossRef" href="#bib0245"><span class="elsevierStyleSup">6</span></a> and there are around 250,000–345,000 deaths attributable to this disease.<a class="elsevierStyleCrossRef" href="#bib0250"><span class="elsevierStyleSup">7</span></a> For the high mortality, hospitalization rates and health care costs, asthma has become a health problem all over the world.<a class="elsevierStyleCrossRefs" href="#bib0255"><span class="elsevierStyleSup">8,9</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">Currently, the main therapy for asthma is the use of daily, long-term controller and quick-relief medications. The quick-relief medications are primarily applied for acute symptom treatment and long-term control medicines are used to prevent exacerbation. Despite the potent positive effects of drugs are available for asthma patients, high dose or long-term use of medicine may remain adverse effects such as development of cataracts, impaired growth in children and decrease in bone mineral density.<a class="elsevierStyleCrossRefs" href="#bib0265"><span class="elsevierStyleSup">10,11</span></a> Numerous studies have been conducted to investigate the mechanism underlying asthma progression and explore the potential alternative therapies for asthma in children. A previous study shows that reactive oxygen species (ROS) generated in airway cells play key roles in enhancing the inflammation in the development of asthma.<a class="elsevierStyleCrossRef" href="#bib0275"><span class="elsevierStyleSup">12</span></a> Oxidative stress and gene transcription are targets in antioxidant therapy for asthma. In addition, some cytokines and proteins are determined to be therapeutic targets for asthma, such as Th2 cytokines, nterleukin-9, chemokine receptors, histone deacetylase.<a class="elsevierStyleCrossRefs" href="#bib0280"><span class="elsevierStyleSup">13–15</span></a> However, studies concerning the gene targets for asthma seem to be insufficient.</p><p id="par0015" class="elsevierStylePara elsevierViewall">In the present study, we explored the differentially expressed genes (DEGs) in children with severe asthma and mild asthma and healthy controls. The significant functions and pathways associated with DEGs were further investigated. The purpose of our study was to screen the potential gene targets for asthma treatment and provide new insight to the effective management of childhood asthma.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Materials and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Affymetrix microarray data</span><p id="par0020" class="elsevierStylePara elsevierViewall">The microarray data of GSE27011 was downloaded from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database (<a id="intr0005" class="elsevierStyleInterRef" href="http://www.ncbi.nlm.nih.gov/geo/">http://www.ncbi.nlm.nih.gov/geo/</a>). The gene expression patterns analyzed in this work were developed from 54 white blood cell samples, including 17 samples from children with severe therapy-resistant asthma, 19 from mild asthmatic children and 17 from healthy individuals. Patients with severe and mild asthma were confirmed by extensive clinical and immunological characterization. The array data was originally developed by Orsmark-Pietras et al.<a class="elsevierStyleCrossRef" href="#bib0295"><span class="elsevierStyleSup">16</span></a>. We downloaded the raw data and the annotation files for further analysis based on the platform of Affymetrix Human Gene 1.0 ST Array.</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Data process and DEGs analysis</span><p id="par0025" class="elsevierStylePara elsevierViewall">Based on the annotation files, a total of 33297 probes were corresponded to gene symbols. After the probe level data were converted to gene expression values, all the expression data were normalized using robust multiarray average (RMA)<a class="elsevierStyleCrossRef" href="#bib0300"><span class="elsevierStyleSup">17</span></a> algorithm. Differentially expressed genes (DEGs) between children with severe asthma and mild asthma (SA vs. MA) or healthy control (SA vs. HC) were analyzed by limma package in R programming language.<a class="elsevierStyleCrossRef" href="#bib0305"><span class="elsevierStyleSup">18</span></a> The Benjamini-Hochberg method was used to adjust for the false discovery rate.<a class="elsevierStyleCrossRef" href="#bib0310"><span class="elsevierStyleSup">19</span></a> DEGs were displayed with false discovery rate (FDR) and FDR<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05 was defined as the cut-off value. In addition, we used an interactive visualization method<a class="elsevierStyleCrossRef" href="#bib0315"><span class="elsevierStyleSup">20</span></a> to present the DEGs in both SA vs. MA and SA vs. HC group and those specific in SA vs. MA or SA vs. HC group.</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0055">Hierarchical clustering of DEGs</span><p id="par0030" class="elsevierStylePara elsevierViewall">Hierarchical clustering has been widely applied in analysing gene expression patterns.<a class="elsevierStyleCrossRefs" href="#bib0320"><span class="elsevierStyleSup">21,22</span></a> With hierarchical clustering, the most similar expression patterns can be clustered in a hierarchy of nested subsets. The expression-level data of mutual DEGs in both SA vs. MA and SA vs. HC group were collected based on the raw files. The hierarchical clustering analysis<a class="elsevierStyleCrossRefs" href="#bib0330"><span class="elsevierStyleSup">23,24</span></a> of the expression data was performed by pheatmap package in R (<a id="intr0010" class="elsevierStyleInterRef" href="http://cran.r-project.org/web/packages/pheatmap/index.html">http://cran.r-project.org/web/packages/pheatmap/index.html</a>) based on Euclidean distance.<a class="elsevierStyleCrossRef" href="#bib0340"><span class="elsevierStyleSup">25</span></a> Hierarchical clustering analysis of the expression data of common DEGs showed advantage in determining whether the screening DEGs had sample specificity or not. Results of hierarchical clustering were displayed by using heat map.</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0060">Function and pathway enrichment analysis of DEGs</span><p id="par0035" class="elsevierStylePara elsevierViewall">The Database for Annotation, Visualization and Integrated Discovery (DAVID) is a gene functional classification tool that provides a comprehensive set of functional annotation tools for investigators to understand biological meaning behind large list of genes.<a class="elsevierStyleCrossRef" href="#bib0345"><span class="elsevierStyleSup">26</span></a> The Kyoto Encyclopedia of Genes and Genomes (KEGG) database is a collection of biochemical pathways, which connects the higher-level complexity of cellular processes and organism behavior with a large scale of genes.<a class="elsevierStyleCrossRefs" href="#bib0350"><span class="elsevierStyleSup">27,28</span></a></p><p id="par0040" class="elsevierStylePara elsevierViewall">The Gene Ontology (GO) annotation and KEGG pathway enrichment analysis for mutual DEGs in SA vs. MA and SA vs. HC group were performed using the functions of DAVID.<a class="elsevierStyleCrossRefs" href="#bib0360"><span class="elsevierStyleSup">29,30</span></a><span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05 was set as the cut-off value. The percentage of significantly enriched GO terms of DEG sets were visualized in three dimensional pie charts with the application of plotrix package in R.<a class="elsevierStyleCrossRef" href="#bib0370"><span class="elsevierStyleSup">31</span></a></p></span></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Results</span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Identification of DEGs</span><p id="par0045" class="elsevierStylePara elsevierViewall">After pre-processing, the obscuring variations in raw expression data were normalized (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>). Then we performed DEGs analysis by limma package. Using the threshold value of FDR<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.05, a total of 969 genes were determined to be differentially expressed, among which 319 DEGs were validated in SA vs. HC group and 650 in SA vs. MA group. As shown in <a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>, there are 81 common DEGs in SA vs. HC and SA vs. MA group. In addition, total 569 genes are specific DEGs in SA vs. MA group and 238 DEGs are only in SA vs. HC group.</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><elsevierMultimedia ident="fig0010"></elsevierMultimedia></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Hierarchical clustering of common DEGs</span><p id="par0050" class="elsevierStylePara elsevierViewall">In order to present the orderly choreography of expression program, we performed the hierarchical clustering for the expression data of common DEGs. As shown in <a class="elsevierStyleCrossRef" href="#fig0015">Fig. 3</a>, samples from SA, HC and MA group were relatively clearly distinguished based on the expression data of common DEGs, suggesting that the DEGs identified in our paper were significant.</p><elsevierMultimedia ident="fig0015"></elsevierMultimedia></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Function annotation and pathway enrichment analysis of common DEGs</span><p id="par0055" class="elsevierStylePara elsevierViewall">In order to investigate the common DEGs in functional level, we performed GO and KEGG enrichment analysis. Total 8 GO terms were significantly enriched by the common DEGs, such as pigment biosynthetic process, nucleoside monophosphate metabolic process and lipid biosynthetic process (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>). The percentages of overrepresented GO terms of DEGs were shown in <a class="elsevierStyleCrossRef" href="#fig0020">Fig. 4</a>. The lipid biosynthetic process accounted for the largest proportion (21.74%). Pigment biosynthetic process, pigment metabolic process, nucleoside monophosphate metabolic process and phospholipid biosynthetic process represented a proportion of 13.04%. Only one pathway was significantly enriched by DEGs such as <span class="elsevierStyleItalic">CD4</span> and <span class="elsevierStyleItalic">RFX</span>, which was named as antigen processing and presentation (<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.0038) (<a class="elsevierStyleCrossRef" href="#fig0025">Fig. 5</a>).</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><elsevierMultimedia ident="fig0020"></elsevierMultimedia><elsevierMultimedia ident="fig0025"></elsevierMultimedia></span></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Discussion</span><p id="par0060" class="elsevierStylePara elsevierViewall">The increasing prevalence of asthma affects public heath, especially the overall quality of life in children. Due to improper measures and delayed treatment time, a large cohort of asthmatic children developed to severe uncontrolled asthma.<a class="elsevierStyleCrossRef" href="#bib0375"><span class="elsevierStyleSup">32</span></a> Children with asthma are at high risk for influenza-related complications. The effective management guidelines for childhood asthmatics have been highlighted worldwide. In this work, we analyzed the microarray data of white blood samples from children with severe asthma, mild asthma and healthy controls. In this paper, we aimed to explore the mechanism of asthma progression and discovery the potential gene targets for childhood asthma treatment. Results showed that a total of 81 genes were differentially expressed in severe asthmatics compared with children with mild asthma and controls. The hierarchical cluster analysis of the 81 DEGs indicated that the DEGs were specific in childhood severe asthmatics that differed from those in children with SA and MA. To explore the potential biological function for 81 DEGs, we performed GO and pathway enrichment analysis.</p><p id="par0065" class="elsevierStylePara elsevierViewall">Our results revealed that antigen processing and presentation pathway (<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.0038) were significantly enriched by 81 DEGs. It is well documented that environment and gene factors are the main causes for the development of asthma.<a class="elsevierStyleCrossRef" href="#bib0380"><span class="elsevierStyleSup">33</span></a> In early childhood, it is common for children to present the initial sensitization to airborne environmental allergens.<a class="elsevierStyleCrossRef" href="#bib0385"><span class="elsevierStyleSup">34</span></a> Harmless inhaled antigens (allergens) are responsible for an asthmatic reaction that may progress to persistent atopic asthma for several years. The inhalation of allergens leads to the sensitization of T helper (Th) type 2 cells induced by dendritic cells (DCs).<a class="elsevierStyleCrossRef" href="#bib0390"><span class="elsevierStyleSup">35</span></a> A subtype of DCs took up antigens and played a critical role in antigen processing and presentation, which further stimulated T cells and inflammation response.<a class="elsevierStyleCrossRef" href="#bib0395"><span class="elsevierStyleSup">36</span></a> For allergen-induced airway hyperreactivity and chronic inflammation to be the primary characteristics in asthma development, antigen processing and presentation may be an critical event in the progression of persistent inflammation in the airway wall that leads to structural and functional changes in local tissues and symptom development.</p><p id="par0070" class="elsevierStylePara elsevierViewall">In addition, our results revealed that <span class="elsevierStyleItalic">CD4</span> and <span class="elsevierStyleItalic">RFX</span> were involved in antigen processing and presentation pathway (<a class="elsevierStyleCrossRef" href="#fig0025">Fig. 5</a>). <span class="elsevierStyleItalic">CD4</span> encoding CD4 molecules have been found to be associated with inflammation and cell immune response.<a class="elsevierStyleCrossRef" href="#bib0400"><span class="elsevierStyleSup">37</span></a> CD4 molecules are mainly expressed on helper T cells and have functions in helping T cell receptor to identify antigen and promoting signal transduction of T cell activation.<a class="elsevierStyleCrossRefs" href="#bib0405"><span class="elsevierStyleSup">38,39</span></a> Therapy targeting <span class="elsevierStyleItalic">CD4</span> expression may be potent in inhibiting antigen presentation and suppressing chronic inflammatory response. Regulatory factor X (RFX) transcription factors have been determined to be involved in the development of a large list of serious human diseases.<a class="elsevierStyleCrossRef" href="#bib0415"><span class="elsevierStyleSup">40</span></a> Although evidence concerning the key role of <span class="elsevierStyleItalic">RFX</span> in the development and progression of childhood asthma is rare, further studies of <span class="elsevierStyleItalic">RFX</span> may hold promise for gaining a novel insight to effective treatment of childhood asthma.</p><p id="par0075" class="elsevierStylePara elsevierViewall">Furthermore, the biological process of lipid biosynthetic process was found to be overrepresented by DEGs with the largest percentage (21.74%). As outlined in previous studies, lipid peroxidation was determined to be related with the severity of asthma in children.<a class="elsevierStyleCrossRef" href="#bib0420"><span class="elsevierStyleSup">41</span></a> Lipid peroxidation elicited by the increasing generation of reactive oxygen species in asthma contributed to the dysfunction of airway.<a class="elsevierStyleCrossRef" href="#bib0425"><span class="elsevierStyleSup">42</span></a> The lipid metabolism was revealed to be changed in children with asthma after treatment by budesonide. Besides, lipid extract of New Zealand green-lipped mussel was found to be effective in treating asthma by inhibiting eicosanoids production.<a class="elsevierStyleCrossRef" href="#bib0430"><span class="elsevierStyleSup">43</span></a> All these implied that lipid played a crucial role in the pathogenesis of asthma but the lipid biosynthetic process needed to be further investigated in asthma progression.</p><p id="par0080" class="elsevierStylePara elsevierViewall">In summary, DEGs specific in childhood severe asthmatics were closely associated with the development of severe asthma. The antigen processing and presentation pathway and lipid biosynthetic process played a role in the pathogenesis of severe asthma. <span class="elsevierStyleItalic">CD4</span> and <span class="elsevierStyleItalic">RFX</span> may be potential therapeutic targets for asthma. Our paper provided new insights to discover the effective therapy for childhood asthma. However, a large number of studies should be conducted to confirm our results with sufficient experimental evidence.</p></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Conflict of interest</span><p id="par0085" class="elsevierStylePara elsevierViewall">All authors declare that they have no conflict of interests to state.</p></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Ethical disclosures</span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Protection of human subjects and animals</span><p id="par0090" class="elsevierStylePara elsevierViewall">The authors declare that no experiments were performed on humans or animals for this investigation.</p></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Patients’ data protection</span><p id="par0095" class="elsevierStylePara elsevierViewall">Confidentiality of Data. The authors declare that no patient data appears in this article.</p></span><span id="sec0080" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Right to privacy and informed consent</span><p id="par0100" class="elsevierStylePara elsevierViewall">The authors declare that no patient data appears in this article.</p></span></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:9 [ 0 => array:3 [ "identificador" => "xres594881" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Background" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec609809" "titulo" => "Keywords" ] 2 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 3 => array:3 [ "identificador" => "sec0010" "titulo" => "Materials and methods" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Affymetrix microarray data" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Data process and DEGs analysis" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "Hierarchical clustering of DEGs" ] 3 => array:2 [ "identificador" => "sec0030" "titulo" => "Function and pathway enrichment analysis of DEGs" ] ] ] 4 => array:3 [ "identificador" => "sec0035" "titulo" => "Results" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "sec0040" "titulo" => "Identification of DEGs" ] 1 => array:2 [ "identificador" => "sec0045" "titulo" => "Hierarchical clustering of common DEGs" ] 2 => array:2 [ "identificador" => "sec0050" "titulo" => "Function annotation and pathway enrichment analysis of common DEGs" ] ] ] 5 => array:2 [ "identificador" => "sec0055" "titulo" => "Discussion" ] 6 => array:2 [ "identificador" => "sec0060" "titulo" => "Conflict of interest" ] 7 => array:3 [ "identificador" => "sec0065" "titulo" => "Ethical disclosures" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "sec0070" "titulo" => "Protection of human subjects and animals" ] 1 => array:2 [ "identificador" => "sec0075" "titulo" => "Patients’ data protection" ] 2 => array:2 [ "identificador" => "sec0080" "titulo" => "Right to privacy and informed consent" ] ] ] 8 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2015-01-15" "fechaAceptado" => "2015-03-24" "PalabrasClave" => array:1 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec609809" "palabras" => array:4 [ 0 => "Childhood asthma" 1 => "Differentially expressed genes" 2 => "Hierarchical clustering" 3 => "Function and pathway enrichment" ] ] ] ] "tieneResumen" => true "resumen" => array:1 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Background</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">In this study, we aimed to discover potential gene targets for treating childhood asthmatics.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">With the microarray data downloaded from Gene Expression Omnibus (GEO) database, we explored the common differentially expressed genes (DEGs) in children with severe asthma and mild asthma (SA vs. MA) or healthy controls (SA vs. HC). Then we performed hierarchical clustering, function and pathway enrichment analysis for the common DEGs.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">A total of 81 genes were identified to be differentially expressed in SA vs. MA and SA vs. HC group. Hierarchical clustering of the 81 DEGs could crudely separate the SA, MA and healthy individuals. The overrepresented GO terms of the common DEGs were related with lipid biosynthetic process (21.74%), pigment biosynthetic process (13.04%) and nucleoside monophosphate metabolic process (13.04%). Only one pathway was significantly enriched, which was the antigen processing and presentation pathway involved with CD4 and RFX gene.</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">The antigen processing and presentation pathway and lipid biosynthetic process may play roles in the pathogenesis of severe asthma. CD4 and RFX provide a therapeutic possibility for childhood asthma.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Background" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] ] "multimedia" => array:6 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1330 "Ancho" => 3040 "Tamanyo" => 351580 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Box plots of data normalization. The <span class="elsevierStyleItalic">x</span>-coordinate represents samples; <span class="elsevierStyleItalic">y</span>-coordinate represents gene expression values. The blue box plots are samples from healthy controls and the red ones are samples from patients with asthma. The black line in the box plots represent expression median.</p>" ] ] 1 => array:7 [ "identificador" => "fig0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1112 "Ancho" => 1338 "Tamanyo" => 58908 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Comparison of differentially expressed genes in SA vs. MA and SA vs. HC group.</p>" ] ] 2 => array:7 [ "identificador" => "fig0015" "etiqueta" => "Figure 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 3180 "Ancho" => 3167 "Tamanyo" => 593329 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Hierarchical clustering of the common DEGs. Red, green, black indicate high, low, or intermediate relative expression, respectively.</p>" ] ] 3 => array:7 [ "identificador" => "fig0020" "etiqueta" => "Figure 4" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr4.jpeg" "Alto" => 1422 "Ancho" => 2456 "Tamanyo" => 187050 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Three-dimensional pie chart of function enrichment analysis of differentially expressed genes.</p>" ] ] 4 => array:7 [ "identificador" => "fig0025" "etiqueta" => "Figure 5" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr5.jpeg" "Alto" => 2222 "Ancho" => 3203 "Tamanyo" => 343629 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Significant pathways enriched by common DEGs. Pink box is the differentially expressed genes.</p>" ] ] 5 => array:7 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Term \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Count \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Percentage \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">P</span> value \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Genes \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">GO:0046148∼pigment biosynthetic process \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.130434783 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.007415 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">NFE2L1, PAICS, PRPS1 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">GO:0042440∼pigment metabolic process \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.130434783 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.009782 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">NFE2L1, PAICS, PRPS1 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">GO:0009123∼nucleoside monophosphate metabolic process \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.130434783 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.020281 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">CNP, PAICS, PRPS1 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">GO:0008610∼lipid biosynthetic process \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.217391304 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.022045 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">SAMD8, ACBD3, CDIPT, DPAGT1, PTDSS1 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">GO:0009113∼purine base biosynthetic process \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.086956522 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.029551 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">PAICS, PRPS1 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">GO:0008654∼phospholipid biosynthetic process \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.130434783 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.045182 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">SAMD8, CDIPT, PTDSS1 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">GO:0006144∼purine base metabolic process \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.086956522 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.045598 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">PAICS, PRPS1 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">GO:0046112∼nucleobase biosynthetic process \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.086956522 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.045598 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">PAICS, PRPS1 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab972734.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Results of function enrichment analysis of differentially expression genes.</p>" ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:43 [ 0 => array:3 [ "identificador" => "bib0220" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Uniform definition of asthma severity, control, and exacerbations: document presented for the World Health Organization Consultation on Severe Asthma" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "J. 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| Year/Month | Html | Total | |
|---|---|---|---|
| 2024 November | 6 | 0 | 6 |
| 2024 October | 8 | 3 | 11 |
| 2024 September | 41 | 6 | 47 |
| 2024 August | 24 | 3 | 27 |
| 2024 July | 16 | 4 | 20 |
| 2024 June | 21 | 7 | 28 |
| 2024 May | 18 | 1 | 19 |
| 2024 April | 20 | 10 | 30 |
| 2024 March | 52 | 6 | 58 |
| 2024 February | 33 | 14 | 47 |
| 2024 January | 12 | 5 | 17 |
| 2023 December | 28 | 6 | 34 |
| 2023 November | 29 | 6 | 35 |
| 2023 October | 41 | 17 | 58 |
| 2023 September | 16 | 6 | 22 |
| 2023 August | 16 | 9 | 25 |
| 2023 July | 16 | 9 | 25 |
| 2023 June | 31 | 10 | 41 |
| 2023 May | 42 | 4 | 46 |
| 2023 April | 43 | 2 | 45 |
| 2023 March | 28 | 5 | 33 |
| 2023 February | 17 | 12 | 29 |
| 2023 January | 17 | 5 | 22 |
| 2022 December | 25 | 11 | 36 |
| 2022 November | 15 | 16 | 31 |
| 2022 October | 13 | 10 | 23 |
| 2022 September | 19 | 8 | 27 |
| 2022 August | 19 | 11 | 30 |
| 2022 July | 15 | 8 | 23 |
| 2022 June | 29 | 6 | 35 |
| 2022 May | 25 | 12 | 37 |
| 2022 April | 62 | 7 | 69 |
| 2022 March | 101 | 7 | 108 |
| 2022 February | 9 | 11 | 20 |
| 2022 January | 53 | 6 | 59 |
| 2021 December | 55 | 9 | 64 |
| 2021 November | 35 | 9 | 44 |
| 2021 October | 25 | 12 | 37 |
| 2021 September | 22 | 12 | 34 |
| 2021 August | 8 | 6 | 14 |
| 2021 July | 17 | 15 | 32 |
| 2021 June | 22 | 9 | 31 |
| 2021 May | 17 | 6 | 23 |
| 2021 April | 41 | 16 | 57 |
| 2021 March | 20 | 24 | 44 |
| 2021 February | 6 | 11 | 17 |
| 2021 January | 14 | 13 | 27 |
| 2020 December | 1 | 3 | 4 |
| 2020 November | 0 | 1 | 1 |
| 2020 October | 0 | 1 | 1 |
| 2020 September | 0 | 2 | 2 |
| 2020 July | 0 | 1 | 1 |
| 2020 May | 0 | 6 | 6 |
| 2020 April | 0 | 5 | 5 |
| 2020 March | 0 | 6 | 6 |
| 2020 February | 0 | 7 | 7 |
| 2020 January | 0 | 6 | 6 |
| 2019 December | 0 | 5 | 5 |
| 2019 November | 0 | 1 | 1 |
| 2019 October | 0 | 2 | 2 |
| 2019 September | 0 | 2 | 2 |
| 2019 August | 0 | 7 | 7 |
| 2019 July | 0 | 3 | 3 |
| 2019 June | 0 | 11 | 11 |
| 2019 May | 0 | 9 | 9 |
| 2019 April | 0 | 3 | 3 |
| 2019 March | 0 | 3 | 3 |
| 2019 February | 0 | 4 | 4 |
| 2019 January | 0 | 3 | 3 |
| 2018 December | 0 | 6 | 6 |
| 2018 November | 0 | 1 | 1 |
| 2018 August | 0 | 1 | 1 |
| 2018 March | 3 | 3 | 6 |
| 2018 February | 12 | 4 | 16 |
| 2018 January | 15 | 0 | 15 |
| 2017 December | 2 | 0 | 2 |
| 2017 November | 11 | 7 | 18 |
| 2017 October | 4 | 4 | 8 |
| 2017 September | 11 | 4 | 15 |
| 2017 August | 12 | 5 | 17 |
| 2017 July | 12 | 1 | 13 |
| 2017 June | 12 | 21 | 33 |
| 2017 May | 11 | 17 | 28 |
| 2017 April | 23 | 13 | 36 |
| 2017 March | 16 | 66 | 82 |
| 2017 February | 11 | 11 | 22 |
| 2017 January | 10 | 3 | 13 |
| 2016 December | 17 | 10 | 27 |
| 2016 November | 12 | 6 | 18 |
| 2016 October | 0 | 2 | 2 |
| 2016 September | 0 | 3 | 3 |
| 2016 August | 0 | 1 | 1 |
| 2016 July | 0 | 1 | 1 |
| 2016 June | 0 | 3 | 3 |
| 2016 May | 0 | 2 | 2 |
| 2016 April | 1 | 0 | 1 |
| 2016 March | 1 | 1 | 2 |
| 2016 February | 1 | 0 | 1 |
| 2016 January | 2 | 1 | 3 |
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