juvenile idiopathic arthritis ( jia ) is one of the most common inflammatory disorder with unknown etiology , presenting in children younger than 16 years of age . the incidence and prevalence is 0.07 to 4.01 per 1,000 children varying by geography and ethnicity . the treatment of jia is time - consuming and frequently causes complications after managed with drugs . previous studies reported the composition of phospholipid fatty acids , and immunological investigations   in children with juvenile chronic arthritis . identifying differentially expressed genes ( deg ) and dysregulated pathways using high - throughput experimental data between normal and jia disease groups can provide insights . the deg and pathways are easy to understand high - level functions that can be used to infer potential molecular and functional insights . recent reports claimed that gene expression patterns could identify biomarkers of arthritis , and highlighted the relevance of pjia through dysregulated pathways [ 1013 ] . pathway databases , such as kyoto encyclopedia of genes and genomes ( kegg ) , can exploit useful pathway topology information . it is well known that kauffman attractor can find many well - defined ensembles of model networks whose statistical features matched those of real cells and organisms . reported that attract could be a new approach that leverages both existing deg and pathways among three different cell phenotypes . we employed attract to screen differentially expressed pathways for the purpose of narrowing the number of correlated dysregulated pathways . however , they invariably focus on internal effects of a single pathway in isolation and fail to consider the inherent dependency inter - pathways . the construction of a pathway crosstalk network ( pcn ) inter - pathways is convenient to master the comprehensive interactions in pjia . in our study we used a scoring scheme to identify these pathways , taking into account both attractors of internal pathway effects and crosstalk inter - pathways . in our study what we want is significantly dysfunctional pathways with strong interactions which are related to pjia progression . the new method may be meaningful in seeking influential pathways by reinforcement of attractor and crosstalk , which served as therapy targeting markers . the transcription profile was obtained from embi - ebi arrayexpress . gene expression profiling of 61 children with pjia and the platform was a - affy-44 - affymetrix genechip human genome u133 plus 2.0 ( hg - u133_plus_2 ) . the linear models for microarray data ( limma )   was then used to preprocess data . background adjustment and quantile data normalization were performed by robust multi - array average . to protect against outlier probes we used a robust procedure , median polish , to estimate model parameters . to screen deg , p0.01 and |log fold change ( fc ) | 2 were set as the threshold levels . information from gene sets representing biological human pathways was obtained from kegg database , which provides copious pathway information . a set of pathways with gene set size > 100 or < 5 were filtered . after size cutoffs were set , 300 pathways were obtained for downstream analysis . the human protein - protein interaction ( ppi ) sets representing biological genes were obtained from the retrieval of interacting genes ( string ; v. 9.0 ) . after removing self - interactions , we had 787,896 ppi sets . based on attractor theory , attract was used to screen differentially expressed pathways related to pjia from 300 kegg pathways . to test data of 300 kegg pathways , gsea - anova was employed as a gene set enrichment algorithm ; which was different from other methods in multiple classes . the obtained differences among the expression profile of samples were identified as attractors . from the anova model , we compute the f - statistic for gene i : where mssi represents the mean treatment sum of squares , and captures the amount of variation due to group - specific effects : and rssi represents the residual sum of squares : where n is the total number of samples , and the overall mean is given by : the f - statistic captures the strength of different expression observed in genes of pjia . large values of the f - statistic mean a strong association with jia - specific expression changes . for pathway p consisting of gp genes , the t - statistic takes the following form : where g represents the total number of genes with a pathway annotation and the sample variances 
 sp2 and 
 sg2 are defined as : and the degrees of freedom are specified by the welch - satterwhaite equation : attractors were ranked according to the significance of difference . the pathway crosstalk network ( pcn ) of the control group the value of weight of the background pcn was defined as the number of ppi sets . fish exact test was performed to evaluate gene overlap between any pair of 300 pathways . the number of ppi sets was counted between any pair of pathways . for each pathway pair , count was for all interactions after removing genes shared in both pathways . when a gene in the pathway had interactions , it was considered as crosstalk between pathways . first , we count the number of genes it interacts with , and randomly draws a gene from the ppi database which interacts with a similar number of genes . once both pathways were randomized , step 2 was performed to count the number of interactions between them . the one - sided fisher exact test on all pathway pairs was performed using the 22 contingency table . p - values of fisher exact test were adjusted using fdr bh procedure and empirical p - value was calculated by counting the number of permutations in which the count of random interactions was higher than or equal to that of true interactions . all pathway pairs with adjusted fisher p<0.05 were used to construct the pcn , where a node represented a pathway and an edge was crosstalk between two pathways . to clean up the network , two types of redundant edges were removed : ( a ) edges with significant gene overlap identified in step 1 were removed from the network ; ( b ) the two edges between two overlapping pathways were considered redundant . base on the original method of crosstalk , the network of pjia could be constructed . in step 3 , we modified it to narrow the number of edges in the network . a gene in the pathway had interactions when it met one of the two conditions : ( 1 ) spearman correlation coefficients of every ppi set were calculated in the control and normal group . when the absolute value of the different value between them was > 0.7 , the edge remained . geometric mean of the absolute value was defined as the value of the weight between the two pathways ( 2 ) the two genes in an interaction were degs . the p<0.01 and |log fold change ( fc ) | > 1 were set as the threshold levels for the identification of deg . outer means the degree of interactions from crosstalk analysis and p represents the p - value of the attractor . rp - value was used to evaluate the comprehensive identified ability within pathways and between pathways . rank inter represents the ranking of attractor s p - value and rank outer means the ranking of interactions . the transcription profile was obtained from embi - ebi arrayexpress . gene expression profiling of 61 children with pjia and the platform was a - affy-44 - affymetrix genechip human genome u133 plus 2.0 ( hg - u133_plus_2 ) . the linear models for microarray data ( limma )   was then used to preprocess data . background adjustment and quantile data normalization were performed by robust multi - array average . to protect against outlier probes we used a robust procedure , median polish , to estimate model parameters . to screen deg , p0.01 and |log fold change ( fc ) | 2 were set as the threshold levels . information from gene sets representing biological human pathways was obtained from kegg database , which provides copious pathway information . a set of pathways with gene set size > 100 or < 5 were filtered . the human protein - protein interaction ( ppi ) sets representing biological genes were obtained from the retrieval of interacting genes ( string ; v. 9.0 ) . after removing self - interactions based on attractor theory , attract was used to screen differentially expressed pathways related to pjia from 300 kegg pathways . to test data of 300 kegg pathways , gsea - anova was employed as a gene set enrichment algorithm ; which was different from other methods in multiple classes . the obtained differences among the expression profile of samples were identified as attractors . from the anova model , we compute the f - statistic for gene i : where mssi represents the mean treatment sum of squares , and captures the amount of variation due to group - specific effects : and rssi represents the residual sum of squares : where n is the total number of samples , and the overall mean is given by : the f - statistic captures the strength of different expression observed in genes of pjia . large values of the f - statistic mean a strong association with jia - specific expression changes . for pathway p consisting of gp genes , the t - statistic takes the following form : where g represents the total number of genes with a pathway annotation and the sample variances 
 sp2 and 
 sg2 are defined as : and the degrees of freedom are specified by the welch - satterwhaite equation : attractors were ranked according to the significance of difference . the pathway crosstalk network ( pcn ) of the control group was constructed using the li et al .   method . the value of weight of the background pcn was defined as the number of ppi sets . fish exact test was performed to evaluate gene overlap between any pair of 300 pathways . the number of ppi sets was counted between any pair of pathways . for each pathway pair , count was for all interactions after removing genes shared in both pathways . when a gene in the pathway had interactions , it was considered as crosstalk between pathways . first , we count the number of genes it interacts with , and randomly draws a gene from the ppi database which interacts with a similar number of genes . once both pathways were randomized , step 2 was performed to count the number of interactions between them . the one - sided fisher exact test on all pathway pairs was performed using the 22 contingency table . p - values of fisher exact test were adjusted using fdr bh procedure and empirical p - value was calculated by counting the number of permutations in which the count of random interactions was higher than or equal to that of true interactions . all pathway pairs with adjusted fisher p<0.05 were used to construct the pcn , where a node represented a pathway and an edge was crosstalk between two pathways . to clean up the network , two types of redundant edges were removed : ( a ) edges with significant gene overlap identified in step 1 were removed from the network ; ( b ) the two edges between two overlapping pathways were considered redundant . base on the original method of crosstalk , the network of pjia could be constructed . in step 3 , we modified it to narrow the number of edges in the network . a gene in the pathway had interactions when it met one of the two conditions : ( 1 ) spearman correlation coefficients of every ppi set were calculated in the control and normal group . when the absolute value of the different value between them was > 0.7 , the edge remained . geometric mean of the absolute value was defined as the value of the weight between the two pathways ( 2 ) the two genes in an interaction were degs . the p<0.01 and |log fold change ( fc ) | > 1 were set as the threshold levels for the identification of deg . the pathway crosstalk network ( pcn ) of the control group was constructed using the li et al .   method . the value of weight of the background pcn was defined as the number of ppi sets . fish exact test was performed to evaluate gene overlap between any pair of 300 pathways . the number of ppi sets was counted between any pair of pathways . for each pathway pair , count was for all interactions after removing genes shared in both pathways . when a gene in the pathway had interactions , it was considered as crosstalk between pathways . first , we count the number of genes it interacts with , and randomly draws a gene from the ppi database which interacts with a similar number of genes . once both pathways were randomized , step 2 was performed to count the number of interactions between them . the one - sided fisher exact test on all pathway pairs was performed using the 22 contingency table . p - values of fisher exact test were adjusted using fdr bh procedure and empirical p - value was calculated by counting the number of permutations in which the count of random interactions was higher than or equal to that of true interactions . all pathway pairs with adjusted fisher p<0.05 were used to construct the pcn , where a node represented a pathway and an edge was crosstalk between two pathways . to clean up the network , two types of redundant edges were removed : ( a ) edges with significant gene overlap identified in step 1 were removed from the network ; ( b ) the two edges between two overlapping pathways were considered redundant . base on the original method of crosstalk , the network of pjia could be constructed . in step 3 , we modified it to narrow the number of edges in the network . a gene in the pathway had interactions when it met one of the two conditions : ( 1 ) spearman correlation coefficients of every ppi set were calculated in the control and normal group . when the absolute value of the different value between them was > 0.7 , the edge remained . geometric mean of the absolute value was defined as the value of the weight between the two pathways ( 2 ) the two genes in an interaction were degs . the p<0.01 and |log fold change ( fc ) | > 1 were set as the threshold levels for the identification of deg . outer means the degree of interactions from crosstalk analysis and p represents the p - value of the attractor . rp - value was used to evaluate the comprehensive identified ability within pathways and between pathways . rank inter represents the ranking of attractor s p - value and rank outer means the ranking of interactions . the pcns of background and pjia were generated with gene expression profiling of 61 pjia patients and 59 controls , respectively . the crosstalk difference of background and pjia are shown in figure 1 . in the control group , the top three important pathways were hepatitis b ( kegg i d : 05161 ) , viral carcinogenesis ( kegg i d : 05203 ) , and pathways in cancer ( kegg i d : 05200 ) . 300 kegg pathways were evaluated comprehensively by kauffman attractor , impact factor and rp - value . there were 12 attractors with p<0.05 and 7 attractors with p<0.01 ( table 1 , figure 2 ) ; the 12 attractors were significantly different in the peripheral blood mononuclear cells ( pbmc ) . there were some molecular alterations in the pathways themselves related to pjia , which showed they were differentially expressed pathways . in terms of interactions inter - pathways , there were different values that varied from 0 to 150 , shown in figure 3 , which indicated that there were different degrees of interactions inter - pathways . rp - value was used to comprehensively assess 300 pathways , including within pathways and inter - pathways . there were 60 pathways with rp < 0.05 and 14 pathways with rp < 0.01 ( figure 2 ) . finally , screened from 12 attractors , two pathways matched with attractor p<0.05 , big value of impact factor and rp - value < 0.05 . they were the p53 signaling pathway ( kegg i d : 04115 ) and the non - alcoholic fatty liver disease ( nafld ) ( kegg i d : 04932 ) pathway , which were considered to be significantly dysfunctional pathways with strong interactions . these pathways might play more important roles in the development of pjia due to their dysfunctional expression and strong interactions . the pcns of background and pjia were generated with gene expression profiling of 61 pjia patients and 59 controls , respectively . the crosstalk difference of background and pjia are shown in figure 1 . in the control group , the top three important pathways were hepatitis b ( kegg i d : 05161 ) , viral carcinogenesis ( kegg i d : 05203 ) , and pathways in cancer ( kegg i d : 05200 ) . 300 kegg pathways were evaluated comprehensively by kauffman attractor , impact factor and rp - value . there were 12 attractors with p<0.05 and 7 attractors with p<0.01 ( table 1 , figure 2 ) ; the 12 attractors were significantly different in the peripheral blood mononuclear cells ( pbmc ) . there were some molecular alterations in the pathways themselves related to pjia , which showed they were differentially expressed pathways . in terms of interactions inter - pathways , there were different values that varied from 0 to 150 , shown in figure 3 , which indicated that there were different degrees of interactions inter - pathways . rp - value was used to comprehensively assess 300 pathways , including within pathways and inter - pathways . there were 60 pathways with rp < 0.05 and 14 pathways with rp < 0.01 ( figure 2 ) . finally , screened from 12 attractors , two pathways matched with attractor p<0.05 , big value of impact factor and rp - value < 0.05 . they were the p53 signaling pathway ( kegg i d : 04115 ) and the non - alcoholic fatty liver disease ( nafld ) ( kegg i d : 04932 ) pathway , which were considered to be significantly dysfunctional pathways with strong interactions . these pathways might play more important roles in the development of pjia due to their dysfunctional expression and strong interactions . attractor theory is well known as a knowledge - driven analytical way to distinguish and annotate gene - sets . the results are more complete than traditional deg analysis due to narrowing the number of correlated dysregulated pathways . in our study , 12 attractors ( p<0.05 ) with statistically significant alterations were screened . while they were differentially expressed pathways in patients , the integral influence to the system was absent . from figure 2 , we can see that the variation trend of p - values of attractor were not absolutely consistent with that of rp - value . pathways with big impact factor values were considered to have strong contact with other pathways . we found that three attractors showed big impact factor values , but nine attractors did not ( impact factor < 80 ) . those pathways with p<0.05 and small impact factor values were considered to have small effects , which should be filtered . our results suggested attractors might fail to identify pathways effectively because of incomplete information on inherent interdependency inter - pathways . this is similar to the challenge faced by other pathway - identification methods that apply topological pathway information . after assessing the interactions inter - pathways by crosstalk , our novel approach enhanced attractors to identify dysregulated pathways . recently , methods to comprehensively identify dysregulated pathways have become a major focus of study . this novel method that combined attractor and crosstalk is hoped to be further applied to other diseases . we applied rp - values to evaluate the comprehensive identified ability both within pathways and inter - pathways . what we wanted was influential dysregulated pathways with attractor p<0.05 , big impact factor value and rp - value < 0.05 . from the screening of 12 attractors , the p53 signaling pathway ( kegg i d : 04115 ) is important in many diseases , in which p53 activation is induced by dna damage , oxidative stress , and activated oncogenes . the nafld ( kegg i d : 04932 ) has been identified as a significant pathway of pjia . therefore , these two pathways are likely to be important in the molecular mechanism of pjia . in our study , a novel approach that identified the dysregulated pathways of pjia was constructed . it was based on attractor of within - pathway effects and crosstalk inter - pathways .
backgroundjuvenile idiopathic arthritis ( jia ) is one of the most common inflammatory disorders of unknown etiology . 
 we introduced a novel method to identify dysregulated pathways associated with polyarticular jia ( pjia).material / methodsgene expression profiling of 61 children with pjia and 59 healthy controls were collected from e - geod-13849 ; 300 pathways were obtained from kyoto encyclopedia of genes and genomes ( kegg ) database and 787,896 protein - protein interaction sets were gathered from the retrieval of interacting genes . 
 attractor and crosstalk were designed to complement each other to increase the integrity of pathways assessment . 
 then , impact factor was used to assess the interactions inter - pathways , and rp - value was used to evaluate the comprehensive influential ability of attractors.resultsthere were seven attractors with p<0.01 and 14 pathways with rp<0.01 . 
 finally , two significantly dysfunctional pathways were found , which were related to pjia progression : p53 signaling pathway ( kegg i d : 04115 ) and non - alcoholic fatty liver disease ( nafld ) ( kegg i d : 04932).conclusionsa novel approach that identified the dysregulated pathways in pjia was constructed based on attractor and crosstalk . 
 the new process is expected to be efficient in the upcoming era of medicine .