P<0.01. Using BMD genes from PLINK, we identified 38 significant KEGG pathways with adjusted P<0.01. Interestingly, 33 pathways are shared in both methods. In summary, we not only identified the known risk pathway such as Wnt signaling, in which the top GWAS variants are significantly enriched, but also highlight some new risk pathways. Interestingly, evidence from further supports the involvement of these pathways in MBD.Osteoporosis is a common human complex disease. It is mainly characterized by low bone mineral density (BMD) and low-trauma osteoporotic fractures (OF). Until now, a large proportion of heritability has yet to be explained. The existing large-scale genome-wide association studies (GWAS) provide strong support for the investigation of osteoporosis mechanisms using pathway analysis. Recent findings showed that different risk pathways may be involved in BMD in different tissues. Here, we conducted multiple pathway analyses of a large-scale lumbar spine BMD GWAS dataset  using two published gene-based analysis software including ProxyGeneLD and the PLINK. Using BMD genes from ProxyGeneLD, we identified 51 significant KEGG pathways with adjusted  Osteoporosis is a common human complex disease –2. It isIn 2012, Estrada et al. performed the largest meta-analysis to date on lumbar spine BMD  and femoral neck BMD , including 17 GWAS datasets from individuals of European and East Asian ancestry . HoweverPathway analyses of GWAS have been widely conducted in human complex diseases or phenotypes, such as Alzheimer's disease –8, rheumLee et al. performed a pathway analysis of hip BMD GWAS in 5,715 Europeans . They idAll these above findings show different risk pathways may be involved in BMD in different tissues. Here, we conducted multiple pathway analyses of a large-scale lumbar spine BMD GWAS using two published gene-based analysis methods including roxyGeneLD  and PLINP<0.05), we performed a pathway analysis. We identified 51 significant KEGG pathways (adjusted P<0.01). Based on the classifications of the KEGG pathways, these 51 pathways can be mainly divided into immune system and diseases (n=10), environmental information processing (n=10), cellular processes (n=8), cancers (n=6), and infectious diseases (n=3). These significant pathways were described in Table Using ProxyGeneLD, these 2,468,080 SNPs are assigned to 16898 genes, which include at least one adjusted SNP. Using the 1236 significant genes (unadjusted P<0.05), we performed a pathway analysis and identified 38 significant KEGG pathways (adjusted P<0.01). These 38 pathways can be mainly divided into immune system and diseases (n=10), cellular processes (n=8), environmental information processing (n=7), genetic and environmental information processing (n=3), infectious diseases (n=4). These significant pathways were described in Table Using PLINK, these 2,468,080 SNPs are assigned to 16543 genes, which include at least one SNP. Using the 824 significant genes , cellular processes (n=7), environmental information processing (n=7), infectious diseases (n=3), genetic and environmental information processing n=2). These shared pathways are highlighted in Table . These sOsteoporosis is a major public health problem. However, the specific genes or pathways influencing these phenotypic are largely unknown. Recently, two pathway analyses of MBD GWAS datasets have been conducted in wrist ultradistal radius and hip. Zhang et al. highlighted the regulation-of-autophagy pathway in wrist ultradistal radius BMD GWAS dataset . Lee et P = 3.26E-09) and 7th significant pathway (P = 1.00E-04) using genes from the “best SNP per gene” method and the meta-analysis method, respectively. It is reported that Wnt signaling plays major roles in almost all aspects of skeletal development and homeostasis. Promising effective therapeutic agents for bone diseases are being developed by targeting the Wnt signaling pathway [We further searched the PubMed and Google Scholar databases to verify our findings. Interestingly, evidence further supports the involvement of these pathways in MBD. Take the Wnt signaling (hsa04310) for example. We identified it to be the most significant pathway ( pathway . Wnt sig pathway .P < 5.00E-08) [P < 0.01) connections between genes in 18 loci in three key biological pathways: the RANK-RANKL-OPG pathway ; mesenchymal stem cell differentiation ; and Wnt signaling  [We further compared our results with previous GWAS , 18. In .00E-08) . They apIn addition to the Wnt signaling, there is also some literature evidence supporting the involvement of other risk pathways in BMD. More detailed information is described in Table P value was adjusted for the LD patterns in the human genome and gene length. PLINK SET SCREEN TEST is a meta-analysis method that combines P values across all the SNPs in genes and adjusts for the LD [Until now, there are kinds of software tools for pathway analysis of the GWAS dataset . Some tor the LD .Based on these different software tools for pathway analysis, we recognize some limitations using ProxyGeneLD and PLINK. First, the multiple testing corrections may not be sufficient to account for all biases in pathway analysis. The results from the BMD GWAS should be adjusted using a permutation test. However, the original SNP genotype data for each individual are not available to us now. When we get the SNP genotype data, we will further perform a pathway analysis using some available software such as SNP ratio test , GenGen In summary, we not only identified the known risk pathway such as Wnt signaling, in which the top GWAS SNPs are significantly enriched, but also highlight some new risk pathways. Interestingly, evidence from further supports the involvement of these pathways in MBD. We believe that our results advance our understanding of BMD mechanisms and will be very informative for future genetic studies in BMD. Further functional evaluation of this pathway to determine the mechanism by which it regulates BMD should be pursued to provide new insights into the pathogenesis of osteoporosis.The second lumbar spine BMD GWAS dataset used here comes from the summary results of a large-scale BMD GWAS conducted by Estrada et al , which iProxyGeneLD assigns SNPs to specific genes . This soP values across all the SNPs in genes and adjusts for LD [P-values obtained from independent tests of the same null hypothesis (each SNP is not associated with disease) [PLINK is used to test for the GWAS dataset by a meta-analysis of all the SNPs in genes . The sets for LD . It is rdisease) . We applp-value of K BMD-related genes in the pathway was calculated usingThe KEGG pathways in WebGestalt were used for pathway analysis  . For a gN is the total number of genes of interest, S is the number of all of the BMD-related genes, m is the number of genes in the pathway and K is the number of BMD-related genes in the pathway.where P<0.01 are considered to be significantly associated with BMD.In order to avoid testing overly narrow or broad pathways, we select WebGestalt KEGG pathways that contain at least 20 and at most 300 genes for subsequent analysis. The reference gene list is the entire entrez gene set. The minimum number of genes for a category is 5. The false discovery rate (FDR) method was used to correct for multiple testing. KEGG pathways with an adjusted


Activation of indirect pathway medium spiny neurons (MSNs) via promotion of cAMP production is the principal mechanism of action (MOA) of current antipsychotics with dopamine D2 receptor antagonism. Phosphodiesterase 10A (PDE10A) inhibitors activate both direct and indirect pathway MSNs by increasing both cAMP and cGMP levels by inhibiting their degradation, which might be expected to promote activation of intracellular signaling similar to that of D2 antagonists in the indirect pathway MSNs. Thus, the activation of the indirect MSN pathway through the distinct MOA of these compounds raises the possibility of augmented pharmacologic effects with combined treatment.In this study, we compared gene-regulation patterns in the indirect pathway MSNs induced by the PDE10A inhibitors T-773 and T-609, and the D2 antagonist haloperidol, using a cell-type-specific comprehensive gene expression analysis in Drd2-bacTRAP (translating ribosome affinity purification) mice. The pharmacologic effects of combined treatment with another PDE10A inhibitor, TAK-063, and clinically used antipsychotics, haloperidol (HAL) and olanzapine (OLA), were evaluated in multiple rodent models.Male ICR mice, Drd2-bacTRAP mice, and Sprague-Dawley rats were used. The indirect pathway MSN-specific gene expression changes by T-773, T-609, and HAL were investigated using RNA sequencing of striatal samples of Drd2-bacTRAP mice. The activation of MSNs in rats was evaluated by measuring glutamate receptor subunit 1 phosphorylation (pGluR1) levels. An in vitro electrophysiological study on the corticostrial pathway in rats was conducted in a slice preparation. The activation of each MSN pathway was assessed by inducing genes as pathway-specific markers: enkephalin for the indirect pathway and substance P for the direct pathway. Suppression of MK-801- or methamphetamine (METH)-induced hyperactivity was assessed by measuring locomotor activity for 2 hours after administration of these stimulants to rats. Improvement of prepulse inhibition (PPI) was investigated in a MK-801-induced PPI deficit mouse model.Translational profiling in Drd2-bacTRAP mice treated with the PDE10A selective inhibitors, T-773 and T-609, and with HAL suggested regulatory of a largely overlapping signaling pathway by these compounds in the indirect pathway MSNs: 87% of the genes regulated by HAL were also regulated by both T-773 and T-609. Combined treatment with TAK-063 and either HAL or OLA produced an augmented effect on pGluR1 in the rat striatum. An electrophysiological study in rat brain slices indicated that TAK-063 enhanced synaptic responses to a similar extent in both direct and indirect pathway MSNs. Additional evaluation using MSN pathway-specific markers revealed that coadministration of TAK-063 with HAL or OLA additively activated the indirect pathway, but not the direct pathway. Combined treatment with TAK-063 (0.1 mg/kg p.o.) and either HAL (0.3 mg/kg p.o.) or OLA (3 mg/kg p.o.) at subeffective doses produced augmented effects on METH- or MK-801–induced hyperactivity in rats and MK-801–induced PPI deficits in mice. TAK-063 at 0.1 mg/kg did not affect plasma prolactin levels and cataleptic response induced by HAL or OLA in rats.PDE10A inhibitors and HAL showed similar patterns of gene regulation in indirect pathway MSNs in mice. Combined treatment with TAK-063 and either HAL or OLA at subeffective doses produced significant antipsychotic-like effects but no augmentation of the plasma prolactin level and cataleptic response. Although further preclinical and clinical studies will be needed, TAK-063 may provide a novel mechanism as a PDE10A inhibitor for use as combination therapy in schizophrenia.


Gene-based supervised machine learning classification models have been widely used to differentiate disease states, predict disease progression and determine effective treatment options. However, many of these classifiers are sensitive to noise and frequently do not replicate in external validation sets. For complex, heterogeneous diseases, these classifiers are further limited by being unable to capture varying combinations of genes that lead to the same phenotype. Pathway-based classification can overcome these challenges by using robust, aggregate features to represent biological mechanisms. In this work, we developed a novel pathway-based approach, PRObabilistic Pathway Score, which uses genes to calculate individualized pathway scores for classification. Unlike previous individualized pathway-based classification methods that use gene sets, we incorporate gene interactions using probabilistic graphical models to more accurately represent the underlying biology and achieve better performance. We apply our method to differentiate two similar complex diseases, ulcerative colitis (UC) and Crohn’s disease (CD), which are the two main types of inflammatory bowel disease (IBD). Using five IBD datasets, we compare our method against four gene-based and four alternative pathway-based classifiers in distinguishing CD from UC. We demonstrate superior classification performance and provide biological insight into the top pathways separating CD from UC.http://simtk.org/home/props or on Bioconductor.PROPS is available as a R package, which can be downloaded at Bioinformatics online. Advancements in statistical modeling combined with the ease of obtaining and generating gene expression data have led to multiple approaches to build regression and classification models to aid in diagnosis, prognosis, disease prediction, patient stratification and treatment selection . For claIBD is a complex and chronic inflammatory condition of the gastrointestinal tract, which affects over 1 in 200 people in the USA . IBD conFAM120A, GAS2L3, CPNE8, NQO2, HOXA10), which yielded a 79% accuracy using leave-one-out cross-validation on colonic biopsies from 28 patients. However, this classifier has not been validated in any additional IBD datasets. There have also been studies that identify differentially expressed genes in UC and CD versus healthy controls, which could be used to construct gene signatures for classification  . Lee et et al., as well as three additional gene-based approaches and four alternative pathway-based approaches. We demonstrate that our method produces superior performance in differentiating UC from CD and provides biological insight about the important pathways and the underlying molecular mechanisms driving these diseases.In this work, we present a new, generalizable approach for individualized pathway-based classification, PRObablistic Pathway Score (PROPS), which uses Gaussian Bayesian networks to create individualized features that reflect pathway activity. We apply these pathway-based features to distinguish CD from UC. We compare our method against that of Montero-Meléndez We curated five datasets containing CD and UC patients at baseline. The first four, GSE6731  and non-affected  areas of the small intestine and colon. For the 12 CD patients, there were a total of 42 non-lesional samples and 71 lesional samples. For the 13 UC patients, there were a total of 44 non-lesional samples and 75 lesional samples.affy package  and (iv) the top 257 significant genes (‘top 257’). We chose 257 to match the number of features used in the pathway-based models. The GSE36807 five genes were present in all studies except in GSE6731 and were thus evaluated only in the remaining three studies, including GSE36807 itself.For comparison, we implemented feature sets at the gene level, using the raw gene values. We created models using (i) all genes, (ii) all genes associated with a KEGG pathway (‘pathway genes’), (iii) the five genes from the classifier built by Montero-Meléndez For further comparison, we implemented four existing pathway-based feature engineering methods to compare against PROPS: LLR  and normLLR calculates the ratio between the conditional probability density functions of CD samples versus UC samples for each gene, where both are assumed to be conditional Gaussian distributions. Next, the ratio is normalized across all samples. The pathway activity is then represented by the sum of normalized LLRs for all genes in the given pathway  and adult samples  and performs well even with different proportions of CD to UC patients in the validation set, as in GSE9686. Gene-based approaches, in contrast, tend to overfit, for example when using the five genes isolated from GSE36807 and when using all the genes. By using pathways, we are implementing biologically driven regularization in order to improve performance by condensing gene features into relevant, aggregate pathway features. These pathway-based features tend to be more robust and less prone to overfitting.In addition to our novel methodology, our work also contributes biological insight into differentiating CD and UC. In distinguishing the two, we found that many of the top pathways are related to metabolism, as detailed below. Interestingly, pathways that are known to play a role in both diseases, such as immune-mediated and inflammatory pathways, do not appear to dominate this list. Such pathways likely have less discriminative power to separate these two diseases, since they are shared features. However, such pathways are important when examining UC samples that were misclassified as CD samples. These misclassified UC samples generally had higher log-likelihood values, differing on a few key IBD-related pathways from other UC samples. These samples may represent a difference in the disease state for these samples or a subtype of UC that more closely mimics CD at the molecular level.l-tyrosine in inflamed UC mucosa, but not in CD, non-inflamed UC or healthy controls. This is consistent with our finding of increased dysregulation of tyrosine in UC compared to CD. Nitrotyrosine has been implicated in damaging DNA and inflammation-mediated carcinogenesis (Tyrosine metabolism is the top pathway with the highest mean decrease in the Gini index, surpassing the second most important pathway by a large margin. Nitration of tyrosine increases in the context of oxidative stress and inflammatory conditions  and specogenesis , which mAside from tyrosine metabolism, several of the other top pathways have a known role in IBD. For example, sphingolipids have been implicated in many inflammatory conditions , includiIn this work, we introduce a novel approach, PROPS, to calculate individual pathway-based scores, using Bayesian networks to capture pathway topology. We apply our method to differentiate CD and UC in order to elucidate disease mechanisms by harnessing information from sites of active inflammation. In distinguishing these two complex diseases, we demonstrate that PROPS is superior in performance and more robust than existing IBD classifiers and alternative methods, and that even pathways that are known to be shared by UC and CD show differing activity, which is useful for differentiation.This work was supported by the National Institutes of Health  and Pfizer Inc. [IC2014-1387].Conflict of Interest: none declared.Supplementary DataClick here for additional data file.


We aimed to identify risk pathways for postmenopausal osteoporosis (PMOP) via establishing an microRNAs- (miRNA-) regulated pathway network (MRPN). Firstly, we identified differential pathways through calculating gene- and pathway-level statistics based on the accumulated normal samples using the individual pathway aberrance score (iPAS). Significant pathways based on differentially expressed genes (DEGs) using DAVID were extracted, followed by identifying the common pathways between iPAS and DAVID methods. Next, miRNAs prediction was implemented via calculating TargetScore values with precomputed input (log fold change (FC), TargetScan context score (TSCS), and probabilities of conserved targeting (PCT)). An MRPN construction was constructed using the common genes in the common pathways and the predicted miRNAs. Using false discovery rate (FDR) < 0.05, 279 differential pathways were identified. Using the criteria of FDR < 0.05 and |logFC| ≥ 2, 39 DEGs were retrieved, and these DEGs were enriched in 64 significant pathways identified by DAVID. Overall, 27 pathways were the common ones between two methods. Importantly, MAPK signaling pathway and PI3K-Akt signaling pathway were the first and second significantly enriched ones, respectively. These 27 common pathways separated PMOP from controls with the accuracy of 0.912. MAPK signaling pathway and PI3K/Akt signaling pathway might play crucial roles in PMOP. Estrogen plays a crucial role in keeping healthy bones. Estrogen deficiency has significantly negative effect on bone cell functions . Postmen ESR2 [ HLA-B [ OPG [In recent years, previous studies have demonstrated that there are powerful genetic effects on the etiology of osteoporosis (OP) in postmenopausal women –6. For e ESR2 , HLA-B [ [ HLA-B , and OPG-B [ OPG . Neverth-B [ OPG . miRNAs -B [ OPG , 12. Gro-B [ OPG . Moreove-B [ OPG . Moreove-B [ OPG  have dem-B [ OPG  have sugHence, we aimed to detect the risk pathways regulated by PMOP-related miRNAs through establishing an miRNA-regulated pathway network (MRPN). Then, we analyzed the topological characteristics of the MRPN, and we also determined how the miRNAs regulated PMOP risk pathways. The results of our study may provide a novel viewpoint with respect to the mechanism and treatment of PMOP.The current analysis was comprised of the following steps-data selection : pathway identification through calculating gene-level statistics and pathway-level statistics based on the accumulated normal samples using individual pathway aberrance score (iPAS), finding differentially expressed genes (DEGs) and significant pathways based on DEGs using DAVID software, identification of the common pathways of these two methods, miRNAs prediction based on the common genes via calculating TargetScores, MRPN construction, and the topological properties for MRPN. The detailed information of each step was described in To reveal the molecular mechanisms of PMOP, microarray analyses of monocytes were performed using Affymetrix HG-133A arrays in 80 females, including 40 pre- and 40 postmenopausal subjects. These data were deposited in the E-GEOD-56815 of the ArrayExpress database . Probe Ihttp://www.reactome.org/) [All biological pathways of humans were retrieved from REACTOME database (me.org/) . Then, sHerein, accumulated premenopausal samples were used as a reference and the expression level of genes was computed by comparing one postmenopause sample with many accumulated premenopause samples according to robust multichip average . In detaZ method to calculate the pathway activity. Specifically, the gene-level statistics of all genes in each pathway were measured and summarized, following by transforming the mean value of gene-level into the pathway statistics of this pathway. The pathway statistics was calculated using the following formula:We used the average Zi represents the gene-level statistics of ith gene, and m denotes the count of genes enriched in this given pathway.In this formula, iPAS is the expression status of a pathway, t-test was used to measure the pathway statistics of each pathway in all samples of the two groups. All the premenopause samples for the reference were compared one by one with reference to output the null distribution of pathway statistics. On the basis of the comparison between an individual postmenopause sample and the null distribution, we obtained the raw P value. Subsequently, the P values were corrected for multiple hypothesis testing based on false discovery rate (FDR) control using Benjamini and Hochberg (BH). Pathways with a FDR value of less than 0.05 were considered significantly differential.With the goal of analyzing the changes of pathways in PMOP and control samples, Gitools  was utilP values by means of Benjamini et al. [In our study, LIMMA package  of R lani et al.  method uP < 0.05 were regarded to be significant pathways.To further reveal the biological roles of DEGs, DAVID  was usedTo evaluate whether the iPAS method was feasible, the method proposed in the current study was compared with traditional DAVID software. The common pathways between the two methods were identified. In an attempt to evaluate the classification capacity of the common pathways, the hierarchical clustering analysis was implemented for the common pathways using Gitools .κ was determined as the threshold when little overlap between the two distributions when TargetScore = κ existed. Furthermore, the miRNA-regulated pathways were achieved using their target gene sets. Next, we constructed an MRPN consisting of miRNAs, genes, and their common pathways. Cytoscape 2.8.3 was used to visualize the MRPN, and the topological properties of the MRPN were analyzed based on the Network Analysis plugin [In detail, TargetScan context score (TSCS) is a sequence-based score for the individual target site, which was computed using TargetScan . Probabis plugin .t-test was used for measuring the pathway statistics of each pathway in control and PMOP samples. Moreover, FDR approach was applied to correct significance levels  for multiple hypothesis testing. Using the criteria of FDR < 0.05, a total of 279 pathways were extracted between the two groups. Cluster analysis was conducted to explore the changes of these 279 pathways. The heatmap of the 279 pathways was shown in After the gene-level statistics of all genes was transformed into the pathway-level statistics value of each pathway,  PTGES2, HAB1, SCT, ASNSD1, and TUT1.Before pathway analysis, DEGs between the two groups were firstly identified. Using the criteria of FDR < 0.05 and |logFC| ≥ 2, a total of 39 DEGs were retrieved. Specific information about DEGs was exhibited in To evaluate whether the iPAS method was feasible, the method proposed in the current study was compared with traditional DAVID software. It was observed that a total of 27 pathways were the common ones obtained from the iPAS approach and DAVID software. These common pathways were shown in The clustering analysis was carried out to evaluate the classification capacity for microarray data samples using the common 27 pathways detected by iPAS and DAVID method . The claTargetScores were firstly calculated based on the combination of logFC values, and TSCS as well as PCT scores. Then, the distribution of TargetScores was obtained. According to the distribution of TargetScores, little overlap between the two distributions at TargetScore = 0.4 was found. Hence, TargetScore > 0.4 was selected as the threshold to filter out less confidence miRNAs. Using the TargetScore value > 0.4, a total of 39 genes, 50 miRNAs, and 145 miRNA-gene interactions were identified, and specific relationship was displayed in We then constructed an MRPN for PMOP, which was shown in We determined the topological characteristics of the network, including the degree distribution. The degree distribution followed a power law distribution using all of the nodes in the MRPN. Based on the degree distribution, we selected 5 nodes as hub nodes, including NXT2, has-miR-1285, GMFB, has-miR-530f, and RPRD1A.In our study, a novel method of extracting pathway-based biomarkers in PMOP was developed, by investigating the interactions among genes, miRNAs, and pathways associated with pathogenesis through constructing an MRPN. The results of our work identified 279 differential pathways between PMOP and normal samples, including MAPK signaling pathway and PI3K/Akt signaling pathway.MAPKs play crucial roles in cellular response to growth factors or cytokines . The musPrevious studies have suggested that PI3K-Akt signaling pathway is implicated in the regulation of cell growth, proliferation, and survival . OsteoblIn conclusion, we comprehensively collected the PMOP risk pathways and the miRNAs of PMOP to characterize the molecular mechanism and treatment strategy for PMOP. We then constructed an MRPN to better reveal the relationship among genes, pathways, and miRNAs and to develop promising drug candidates for PMOP. Based on the results, differential pathways, including MAPK signaling pathway and PI3K/Akt signaling pathway, were successfully identified. Moreover, these pathways-related miRNAs may be involved in the pathogenic process of PMOP. The findings of our study may be applied clinically for the diagnosis and treatment of PMOP patients.


P value < 0.05, RP values < 0.05, and IF values > 100, which were considered to be the most important pathways in colon cancer. In conclusion, the five pathways were identified in the center status of colon cancer, which may contribute to understanding the mechanism and development of colon cancer.Colon cancer is the third and second most common cancer form in men and women worldwide. It is generally accepted that colon cancer mainly results from diet. The aim of this study was to identify core pathways which elucidated the molecular mechanisms in colon cancer. The microarray data of E-GEOD-44861 was downloaded from ArrayExpress database. All human pathways were obtained from Kyoto Encyclopedia of Genes and Genomes database. In total, 135 differential expressed genes (DEG) were identified using Linear Models for Microarray Data package. Differential pathways were identified with the method of attractor after overlapping with DEG. Pathway cross talk network (PCN) was constructed by combining protein-protein interactions and differential pathways. Cross talks of all pathways were obtained in PCN. There were 65 pathways with RankProd (RP) values < 0.05 and 16 pathways with Impact Factors (IF) values > 100. Five pathways were satisfied with  Colon and rectal cancer are the third most common forms of cancer in the United States . Colon cModern molecular biology indicates that selective expression of genes controls the regulating mechanism in the biology. DEG that has significant difference at expression level between cancer tissues and normal tissues could conduce to analyzing cancer mechanism. Altered pathways between cancer tissue and normal tissue may help to understand the disease status and suggest anticancer therapies. Based on microarray data and Kyoto Encyclopedia of Genes and Genomes (KEGG) database, numerous researches have analyzed biological processes with genes and pathways by using a variety of statistical analysis strategies –10.Attractor is an analytical approach for identifying and annotating the gene sets that best discriminate between cell phenotypes . It can Protein-protein interactions (PPIs) provide valuable information about how genes perform functions. Network-based methods have been applied to gain insight into the mechanism from the interaction data . The patIn this study, we tried to explore colon cancer mechanism by analyzing pathways which not only were dysregulated in colon tissues when compared with normal group but also interacted with other pathways. To achieve this goal, gene expression profiles were downloaded from ArrayExpress database to detect differential expressed genes. Human-related pathways were downloaded from KEGG database and PPIs were downloaded from search tool for the retrieval of interacting genes/proteins (STRING) database to identify differential pathways and construct PCN.Microarray data of E-GEOD-44861 , along wMicroarray expression data should be preprocessed because they are measured as intensities. Linear Models for Microarray Data (LIMMA) package was chosen to reprocess data with the function of expresso . And theP value ≤ 0.01 were selected as the cut-off criteria.DEGs have become an important method in studying tumor-related genes. They contribute to illuminating mechanism of a tumor. In this study, LIMMA method was applied to screen DEG. The values of |log FC| ≥ 1.5 and http://www.kegg.jp/) [http://www.reactome.org/) [The common databases regarding biology are Kyoto Encyclopedia of Genes and Genomes (KEGG) database (egg.jp/)  and Reacme.org/) . In thisPPI data has become an important source of protein function and relationship information in microbiology, molecular biology, computational biology, and medicine. And it can provide valuable information regarding how genes carry out their biological functions . The PPITo screen differential pathways, attractor method was applied .Genes in normal group and disease group were treated with KEGG enrichment analysis. Attractors were obtained with GSEA-ANOVA, an analysis of variance-based implementation of a gene set enrichment algorithm.F-statistic of gene was figured out withi denotes the mean treatment sum of squaresi denotes the residual sum of squaresp consisting of gp genes, the T-statistic takes the following form:G denotes the total number of genes in a pathway and Sp2 and SG2 were defined as sample aberrances.From this model, T-test and adjusting by false discovery rate (FDR) of Benjamini-Hochberg [P values of each pathway were obtained.After performing Hochberg , P valueTo analyze interactions between pathways, a PCN was constructed as described by Li et al. .It is assumed that cancer-associated gene's dysregulation of expression can lead to the differential expression of its interacting genes when there is no network rewiring. We used gene expression correlation to measure the dynamic action of the PPIs.Eij is the PPI between gene Vi and gene Vj; k is the kth sample; xjk is the rank of Vi of kth sample; xik is the rank of Vj of kth sample; Vi and Vj in the samples, respectively:rEij1and rEij2 represent the Spearman coefficients of Eij in compared samples, respectively.In both disease group and background group, Spearman correlation coefficient of each PPI was calculated with the following formula :(5)rEij=rEij| ≥ 0.5. If |ΔrEij| < 0.5 but the two genes belong to differential expressed genes, they are also considered to have strong interactions and should be reserved.The gene pairs are considered to interact intensively if |ΔWeight represents the number of PPI in the network . Only geBy analysis of the topological characteristics in the network, all node degrees were obtained. The degree ratio was defined as the degree of a node in disease-related PCN to that in background PCN.We introduced a concept of pathway score to examine the pathway status in the disease. The formula was shown as P value of a pathway and outer indicated degree of a pathway.For a comprehensive analysis of disease-related genes and pathways, we introduced nonparametric rank product (RankProd) approach  to find An impact factor (IF) concept was also introduced to examine the significance of a pathway, which was shown asP value ≤ 0.01 by using the method of LIMMA.Based on the microarray data of E-GEOD-44861, 135 DEGs between colon cancer tissues and normal tissues were screened out with |log FC| ≥ 1.5 and P value < 0.05 were obtained in the cancer group as shown in P value < 0.01) were identified, which were significantly different between normal group and cancer group.Compared with normal group, a total of 18 differential pathways with http://dx.doi.org/10.1155/2016/2619828) and cross talks test groups were shown in Supplemental Data 2.Pathways and protein interactions were integrated to a global PCN. In the network, nodes represented as pathways and edges denoted cross talk between pathways. We analyzed node degrees of the network, which indicated the connections among pathways. Cross talks in background were shown in Supplemental Data 1  and progress to invasive tumors or arise as invasive tumors. Low-grade papillary tumors frequently show a constitutive activation of the receptor tyrosine kinase-Ras pathway, exhibiting activating mutations in the HRAS and fibroblast growth factor receptor 3 (FGFR3) genes. In contrast, CIS and invasive tumors frequently show alterations in the TP53 and RB genes and pathways. Invasion and metastases are promoted by several factors that alter the tumor microenvironment, including the aberrant expression of E-cadherins (E-cad), matrix metalloproteinases (MMPs), and angiogenic factors such as vascular endothelial growth factor (VEGF) .“Alcoholism” pathway is a chronic relapsing disorder related pathway. Alcoholism is progressive and has serious detrimental health outcomes. As one of the primary mediators of the rewarding effects of alcohol, dopaminergic ventral tegmental area (VTA) projections to the nucleus accumbens (NAc) have been identified. Acute exposure to alcohol stimulates dopamine release into the NAc, which activates D1 receptors, stimulating PKA signaling and subsequent CREB-mediated gene expression, whereas chronic alcohol exposure leads to an adaptive downregulation of this pathway, in particular, of CREB function. The decreased CREB function in the NAc may promote the intake of drugs of abuse to achieve an increase in reward and thus may be involved in the regulation of positive affective states of addiction. PKA signaling also affects NMDA receptor activity and may play an important role in neuroadaptation in response to chronic alcohol exposure .2+-dependent and Ca2+-independent mechanisms, DA influences neuronal activity, synaptic plasticity, and behavior. Presynaptically localized D2Rs regulate synthesis and release of DA as the main autoreceptor of the dopaminergic system [“Dopaminergic synapse” pathway is correlated with nervous system. Dopamine (DA) is an important and prototypical slow neurotransmitter in the mammalian brain, where it controls a variety of functions including locomotor activity, motivation and reward, learning and memory, and endocrine regulation. Once released from presynaptic axonal terminals, DA interacts with at least five receptor subtypes in the central nervous system (CNS). Through diverse cAMP- and Cac system , 30.“MicroRNAs in cancer” pathway is involved in a cluster of small nonencoding RNA molecules of 21–23 nucleotides in length, which controls gene expression posttranscriptionally via either the degradation of target mRNAs or the inhibition of protein translation. Using high-throughput profiling, dysregulation of miRNAs has been widely observed in different stages of cancer. The upregulation of specific miRNAs could result in the repression of tumor suppressor gene expression, and conversely the downregulation of specific miRNAs could lead to an increase of oncogene expression; both these situations result in tumor growth and progress. The miRNA signatures of cancer observed in various studies differ significantly. These inconsistencies result from the differences in the study populations and methodologies , 32.“Cell cycle” pathway functions in response to DNA damage by activating signaling pathways that promote cell cycle arrest and DNA repair. When responding to DNA damage, the checkpoint kinase ATM phosphorylates and activates Chk2, which in turn directly phosphorylates and activates p53 tumor suppressor protein. p53 and its transcriptional targets play an important role in both G1 and G2 checkpoints . ATR-ChkBesides, some identified pathways were involved in the regulation of NADPH, such as “fatty acid metabolism” and “oxidative phosphorylation,” which was similar to the results of Ryan et al. .Still, there are limitations in the paper. The results were generated from bioinformatics analysis, which still need clinical data to be verified.In this study, we concentrated on exploring important pathways that reflected mechanism of the occurrence and development of colon cancer. We identified DEG and differential pathways by comparing colon cancer tissues and normal tissues. After comparing PCN between cancer and normal, we identified 5 important pathways, which may give new insights into the underlying biological mechanisms driving the progression of colon cancer and should be paid close attention to in further research.The crosstalks between pathways were presented in count list.


Hiccups are occasionally experienced by most individuals. Although hiccups are not life-threatening, they may lead to a decline in quality of life. Previous studies showed that hiccups may occur as an adverse effect of certain medicines during chemotherapy. Furthermore, a male dominance in hiccups has been reported. However, due to the limited number of studies conducted on this phenomenon, debate still surrounds the few factors influencing hiccups. The present study aimed to investigate the influence of medicines and patient characteristics on hiccups using a large-sized adverse drug event report database and, specifically, the Japanese Adverse Drug Event Report (JADER) database. Cases of adverse effects associated with medications were extracted from JADER, and Fisher’s exact test was performed to assess the presence or absence of hiccups for each medication. In a multivariate analysis, we conducted a multiple logistic regression analysis using medication and patient characteristic variables exhibiting significance. We also examined the role of dexamethasone in inducing hiccups during chemotherapy. Medicines associated with hiccups included dexamethasone, levofolinate, fluorouracil, oxaliplatin, carboplatin, and irinotecan. Patient characteristics associated with hiccups included a male gender and greater height. The combination of anti-cancer agent and dexamethasone use was noted in more than 95% of patients in the dexamethasone-use group. Hiccups also occurred in patients in the anti-cancer agent-use group who did not use dexamethasone. Most of the medications that induce hiccups are used in chemotherapy. The results of the present study suggest that it is possible to predict a high risk of hiccups using patient characteristics. We confirmed that dexamethasone was the drug that has the strongest influence on the induction of hiccups. However, the influence of anti-cancer agents on the induction of hiccups cannot be denied. We consider the results of the present study to be helpful for the prevention and treatment of hiccups. Hiccups are occasionally experienced by most individuals and are mainly caused by diaphragmatic myoclonus . MyoclonA hiccup is an involuntary, spasmodic contraction of the diaphragm causing a beginning inspiration that is suddenly checked by closure of the glottis. The glossopharyngeal nerve , vagus nerve , nuclei of the solitary tract, nucleus ambiguus, and phrenic nerve are all involved in the afferent and efferent pathways of the hiccup reflex arc –4. HowevPrevious studies investigated hiccups-related drugs –12. FauzChemotherapy-induced hiccups were recently reported. A relationship was found between anti-cancer drugs and hiccups, and a large number of studies have described hiccups caused by cisplatin , 12. FurSince April 2004, PMDA has reported cases of adverse events associated with medications in JADER . A . A P valWe conducted a multiple logistic regression analysis. The data that we used for the multivariate analysis included 436,190 cases, except data with missing values in the patient backgrounds of 972,220 cases. The objective variable was set to hiccups. The explanatory variables were set to patient characteristics  and suspected medicines that significantly differed in the variable analysis. In this analysis, we used suspected medicines for which there were more than three reports of hiccups.P value in Fisher’s exact test. We also extracted data on the dexamethasone-use and anti-cancer drug-use groups in hiccups cases and investigated the involvement of suspected medicine, concomitant medicine, and interaction in each group.In order to investigate the influence of the different administration routes of dexamethasone on hiccups, we compiled a cross-tabulation table based on classifications: the presence or absence of hiccups and the administration route of choice. We calculated the P-value of <0.05 was considered significant. We estimated the internal correlation using the pairwise method. When the square of Spearman’s rank-order correlation coefficient [ρ2] was greater than 0.9, we concluded that there was an internal correlation. When there was no internal correlation, we treated these items as independent factors. All analyses were performed with JMP®Pro12 .Means (± standard deviation) were calculated for all continuous variables. A The drug information table included 2,503,892 cases, the REAC table included 600,264 cases, and the list of cases included 378,532 cases. The total number, as shown in the “all data table”, was 3,180,410. The “suspected medicine data table,” which only extracted suspected medications from the all data tables, totaled 972,220 cases.P values of each item. In the gender analysis, we calculated the P value using Fisher’s exact test. In the analysis of age, height, and weight, we calculated the P value using a t-test.In the “suspected medicine data table,” hiccups were reported in 160 cases. P = 0.1775). The results obtained showed that there were no significant effects of the reporting year on hiccups. We also compiled a scatter-plot (volcano plot) on adverse effects and gender  between hiccups and the reporting year  of Fisher’s exact test. The positive Y-axis direction represents a strong significant difference. In other words, for medications drawn in the upper right side, the ROR and significant difference were large. P value and ROR of the drugs for which the P value obtained using Fisher’s exact test was significant in more than three reports. Among the seven selected medications, dexamethasone and fluorouracil were the only ones available via multiple administration routes. Furthermore, the name of the medication registered with JADER may vary according to the administration route. We treated medicines with generic names associated with dexamethasone and fluorouracil to accurately evaluate the drug’s effects on hiccups.We cyclopedically produced a scatter plot on the relationship between the ROR and significant differences in order to examine medicines suspected of causing hiccups and other drugs . We usedThe total number of cases of hiccups reported in the “all data table” was 540. We removed a duplication case involving a patient with the same ID number and estimated the number of cases of hiccups. As a result, 83 cases of hiccups were reported. Of these cases, 17 patients (20%) were administered dexamethasone that was classified as the suspected medicines, the concomitant medicines, and the interaction medicines. Among the patients using dexamethasone, 16 (94%) were also using an anti-cancer drug. Sixty-six patients (80%) with hiccups were dexamethasone non-users, and twenty-four of these (36%) also used an anti-cancer drug .Among the 378,532 JADER adverse effect cases, there were 160 cases of hiccups with suspected medications. In a comparison with other adverse effect reports, this was a relatively small number of cases. We suggest that patients do not consider hiccups to be an adverse effect unless they are intractable. Therefore, we infer that reports of hiccups in this database are mostly refractory hiccups. By only analyzing suspected medicines reported in JADER, we may have limited the adequate identification of the causal drug. Therefore, we examined all data including the suspected medicine, concomitant medicine, and interaction for dexamethasone and anti-cancer drugs.The incidence of persistent or intractable hiccups is significantly higher in men. Lee et al. showed a male dominance in their meta-analysis. Our results supported these findings . Kitraki et al. reported the specificity of steroid receptors in the brain and pituitary gland in the rat based on gender . This maWe conducted an investigation into the relationship between hiccups and patient characteristics  included in JADER. The results obtained showed that an advanced age, greater height, and greater weight were all significant factors positively influencing the onset of hiccups. We also conducted a multiple logistic regression analysis to extract independent factors. Only a greater height was identified as an independent risk factor for hiccups . To the best of our knowledge, the relationship between hiccups and physical features has not yet been examined. This study is the first to show a relationship between height, weight, and hiccups. Therefore, we may be able to predict the onset of hiccups from medicines taken and patient characteristics. These results may assist in the choice of appropriate therapeutic medicines and preventive medicines for patients with an elevated risk of hiccups. Further clinical trials are required.The results of the present study showed that chemotherapy-related drugs induced hiccups. The multivariable analysis indicated that anti-cancer drugs and dexamethasone are independent risk factors for hiccups.Drug-induced hiccups are regarded as peripheral hiccups . The indOur investigation on dexamethasone administration routes and hiccups revealed a relationship between the intravenous route and induction of hiccups. Dexamethasone is often used as an antiemetic in chemotherapy . We wereWe then examined the effects of dexamethasone combined with other medicines. The suspected medicine, concomitant medicine, and interaction of the drug for the adverse event were selected by reporters in JADER. We often use medication data of the suspected medicine for an analysis in JADER. However, there is a large report bias associated with using only the data of the suspected medicine. Therefore, we conducted an examination of all data for the suspected medicine, concomitant medicine, and interaction. As a result, most of the reported cases of dexamethasone use in our study were in combination with an anti-cancer drug (16 out of 17). Among dexamethasone users, only one case did not use an anti-cancer drug; this was a case of an intravenous injection of medicine for asthma. In this case, there were no medicines that induced hiccups other than dexamethasone. Therefore, dexamethasone use alone appears to induce hiccups. This result suggests that dexamethasone is an important drug associated with the induction of hiccups.High-dose dexamethasone passes the blood-brain barrier and activates steroid receptors in the hypothalamic hippocampus . TherefoIn our examination, there were 66 cases of hiccups in patients who did not use dexamethasone. Of those, 23 patients were using anti-cancer drugs. This supports the results of the multivariable analysis showing that the use of anti-cancer drugs is one of the independent risk factors influencing the onset of hiccups. Anti-cancer agents, except for platinum anti-cancer drugs, were extracted as suspected hiccup-inducing medicines in our study. Further studies are needed in order to elucidate the mechanisms responsible for anti-cancer drug-induced hiccups.Since JADER is based on a self-reporting system, these cases are limited. Mild adverse effects are only occasionally reported, with severe cases being reported more often. This a known report bias, which is characteristic of a self-report database . This daThe results of the present study suggest that hiccups are more common in men than in women and in those who are tall than in those who are short. However, we need to introduce assumptions that the frequency of reporting adverse effects to JADER does not depend on either the sex or height of patients. Hiccups are more common among those intravenously administered dexamethasone, suggesting that the method of administration is independent of reporting. Neither of these assumptions may be plausible. Patients intravenously administered medicines are more likely to be seen by a physician and may be more likely to report an adverse effect. Furthermore, as a result of co-medications, reporting may be more frequent than in patients taking only one medication because of the differentiation of causality of physicians; this may result in bias in the multiple logistic regression analysis.We searched data on medications and patient characteristics associated with hiccups using the large JADER database. Our results suggest that not only medications, but also patient backgrounds are associated with hiccups. By using large-scale adverse effects report data, we were able to extract medications that induced the rare adverse effect of hiccups. The results of the present study will assist practitioners in the selection of appropriate therapeutic medicine, potentially avoid this adverse effect, and improve patient quality of life.S1 TableP values (P = 1) were omitted from this table.Drugs with the highest (DOCX)Click here for additional data file.


We have analyzed the pathway networks of ischemia-affected and remote myocardial areas after repetitive ischemia/reperfusion (r-I/R) injury without ensuing myocardial infarction (MI) to elaborate a spatial- and chronologic model of cardioprotective gene networks to prevent left ventricular (LV) adverse remodeling. Domestic pigs underwent three cycles of 10/10 min r-I/R by percutaneous intracoronary balloon inflation/deflation in the mid left anterior descending artery, without consecutive MI. Sham interventions (n = 8) served as controls. Hearts were explanted at 5 h (n = 6) and 24 h (n = 6), and transcriptomic profiling of the distal (ischemia-affected) and proximal (non-affected) anterior myocardial regions were analyzed by next generation sequencing (NGS) and post-processing with signaling pathway impact and pathway network analyses. In ischemic region, r-I/R induced early activation of Ca-, adipocytokine and insulin signaling pathways with key regulator STAT3, which was also upregulated in the remote areas together with clusterin (CLU) and TNF-alpha. During the late phase of cardioprotection, antigen immunomodulatory pathways were activated with upregulation of STAT1 and CASP3 and downregulation of neprilysin in both zones, suggesting r-I/R induced intrinsic remote conditioning. The temporo-spatially differently activated pathways revealed a global myocardial response, and neprilysin and the STAT family as key regulators of intrinsic remote conditioning for prevention of adverse remodeling. While IPC (with AMI) represents the warm-up angina followed by ST-segment elevation myocardial infarction (STEMI), r-I/R corresponds to a stable angina in humans.To date, high-throughput gene analyses have not yet been used for dissecting the effects of IPC or r-I/R in a closed-chest, catheter-based setting in a clinically relevant large animal model, without the masking effect of infarction7Here we analyzed the effects of the r-I/R stimulus without subsequent infarction-related injury in a porcine model using next generation sequencing (NGS) combined with pathway network analysis. Our aim was to reveal the complex transcriptomic response that is involved in cardioprotection in ischemic and ischemia-unaffected regions of the heart, and to identify novel genes and networks that are responsible for protection of the heart against I/R. We analyzed the relevant genes and pathways at an early time point after r-I/R injury  and 24 h later , and elucidated the time-sequence of the activation of pathways and genes with conditioning function in the ischemic and the ischemia non-affected region, termed “intrinsic remote conditioning” responsible for prevention of LV adverse remodeling.in vitro models lack the pathophysiological complexity of the organism. Our assumption, that the typical 30 sec myocardial r-I/R cycles used in rodents for mimicking r-I/R or IPC, would be inadequate in provoking a sustained ischemic response in either pigs or humans, was evidence-based from our previous work showing that indications of adaptive mechanisms can be observed after a minimum of 5 min coronary occlusion in pigsIn contrast to our translational model, small animal open-chest models, with high heart rates differ substantially from the biological scenario presented by the human transient ischemic heart attack. Furthermore, The results of hemodynamic measurements, both invasive and non-invasive, at baseline, directly after the r-I/R stimulus and at follow-up are shown in The r-I/R stimulus failed to change plasma levels of troponin I, myoglobin or CK . HistoloThe comparison of the groups r-I/R [5 h] and r-I/R [24 h] with the control group showed that a total of 13758 genes were retrieved by NGS. PCA showed good discriminatory power between the three experimental groups with adequate similarity within the r-I/R groups even though originating from different anterior wall myocardial regions . The expVenn diagrams showed significantly altered gene expression between control and r-I/R animals (regardless of the time) and between r-I/R -induced early and late changes for proximal (ischemia-unaffected), mid (border) and distal (ischemia-affected) anterior regions . RemarkaIn the distal anterior wall region, a total of 1328 and 1762 genes were differentially expressed at 5 h and at 24 h, respectively. In the mid anterior region (border zone of ischemia/reperfusion), 1617 and 1087 genes were deregulated 5 h and 24 h post r-I/R, respectively. Regarding the proximal anterior wall region, 1451 and 1276 genes showed differential expression at 5 h and 24 h post r-I/R.The key regulator STAT3 is overexpressed in the ischemic, but also in the border and non-ischemic areas at 5 h, and mediates the Ca-signaling, adipocytokine and insulin signaling pathways. It is involved in both the PI3K/Akt and the JAK-STAT pathways. Moreover, SHISA2 showed a striking upregulation in both the early and late phases, suggesting the involvement of Wnt-signaling in ischemic preconditioning-induced cardioprotectionActivation of PI3K and its downstream targets Akt and glycogen synthase kinase 3β (GSK3B), has been demonstrated to be essential for ischemic preconditioning-induced cardioprotection involved in the RISK pathwayThe recruitment of STAT3 and the activation of the JAK-STAT pathway play a major role in upregulation of cardioprotective and anti-apoptotic proteinsIn the late phase (24 h), expression of STAT1 was upregulated together with CASP3, both of which have a central role in the activated pathways and are promoting apoptosis. Transcription of CLU (a secreted chaperone that is protective against apoptosis) is significantly elevated both at 5 h and 24 h post r-I/R in ischemic and non-ischemic regions, with an even more pronounced increase at the later time point. CLU has been found to induce ischemic tolerance in neuronset al.Similarly to a previous experiment by El-Adawi Quantitative RT-PCR of selected targets confirmed the findings of the NGS analysis . The r-IIn order to prove the cardioprotective effect of the 3 × 10 min r-I/R stimulus, we have additionally induced AMI 26 h post r-I/R (SWOP phase) (group IPC-AMI) or sham I/R (group AMI). The AMI was induced by 90 min catheter-based occlusion of the mid left anterior descending coronary artery followed by reperfusion. The results of cardiac MRI measurements at 30 days are summarized in This is the first study investigating an r-I/R stimulus without subsequent MI in a translational large animal model by the means of NGS, able to retrieve all mRNA transcripts, to identify cardioprotective signaling and the de novo synthesized proteins mediating cardioprotection of the late window. Pathway network and gene expression analyses confirmed time-dependent reprogramming of the ischemic and ischemia non-affected LV gene expression in response to the r-I/R stimulus without MI, with activation of the Ca-signaling, adipocytokine and insulin signaling pathway in the ischemic region early after I/R, and the immunomodulatory pathways at the time of the induced cardioprotection, during the late window of protection. The pathway network analysis provides evidence of spatiotemporal changes in the activation of diverse pathways and complex gene expression profiles of ischemic and non-ischemia-affected zones of the LV. Our data demonstrate that the r-I/R stimulus triggers a distinct adaptive genomic response of the myocardium in a time-dependent manner. Spatiotemporal analysis suggested protective responses in remote, non-ischemia-affected myocardial regions, which might be a target for prevention of ischemic LV remodeling. In contrast to previous experiments, which primarily examined selected genes or groups of related genes, the methods used here, i.e. NGS and pathway network modeling, allowed us to identify the complex responses to I/R in a more comprehensive manner. We analyzed the expressional changes of over 13000 genes by NGS mapping. The results confirmed the reprogramming of the LV in response to the r-I/R injury stimulus. Our data revealed that numerous cardioprotective proteins are necessary for the late windows of protection, which relies on de novo protein synthesis.We have identified different networks of pathways at the site of the ischemic injury that were activated sequentially, including Ca-signaling, adipocytokine and insulin signaling pathways at 5 h and several immunomodulatory pathways at 24 h. We found that altered gene expression and related pathway activation were more pronounced at 5 h than at 24 h after r-I/R, underlining the significance of early de-novo protein synthesis, reaching their full effectivity in the SWOP. STAT3 proved to be a key regulator of pathway networks in the early phase, while STAT1 and CASP3 are central nodes in the late phase of cardioprotection. We found an early upregulation of neprilysin both in the ischemic, but also in the non-ischemic region. This endopeptidase has recently been acknowledged as an important signaling molecule of heart insufficiency. Our data suggests also its active role in LV remodeling after I/R injury. In the remote myocardium, Ca-signaling and immunomodulatory pathways were activated at 5 h and at 24 h, indicating intrinsic remote conditioning, in contrast with the neurohumoral mechanism of the classic remote conditioning applying repetitive ischemia in the peripheral muscles. The complexity of the gene regulation patterns revealed in this study suggests that profound biological reactions are triggered by r-I/R and shows that powerful bioinformatics analyses of pathways, gene and protein interactions have the potential to reveal novel targets for therapeutic intervention for clinical relevance.During conditioning r-I/R cycles, the myocardium activates adaptive mechanisms in an attempt to maintain cell function during actual and delayed hypoxic conditions, and to counterbalance apoptotic signaling by limiting DNA-damage. Unaware of how long the ischemic event will last, the myocardium initially responds in an identical manner to that seen during sustained ischemia. Once a conditioning response is confirmed, the question is to determine the threshold of ischemic burden that will trigger conditioning-induced signaling (instilling ischemic memory) towards irreversible damage.all interconnected transcripts and interacting pathways, and their regulation with respect to activation, in the ischemic and in the non-ischemic myocardium. The discovery of several activated pathways and upregulated genes in the ischemia-affected and non-affected regions with yet unknown cardiovascular function may serve as a starting point for further research on mitigation of I/R injury and post-ischemic left ventricular remodeling.With reference to previous studies, our NGS data confirms the involvement of pathways and networks already known to be implicated in I/R, such as Ca-signaling, energy metabolism including mitochondrial respiratory chain proteins, myocyte and matrix structure proteins, and stress response proteins including cell fate effectors1217Taken together, our data indicates that complex cellular and molecular mechanisms are responsible for cardioprotection through r-I/R, and further regulatory pathways than just the SAFE and RISK pathways are triggered. A number of genes with yet unknown role in I/R have been identified and their precise role and mechanism in cardioprotection may be characterized by further investigations. The profound alterations of several distinct pathways indicate that a multi-targeted therapeutic approach may be feasible. Regarding the concept of systems pharmacology, the precise role of all involved pathways should be taken into account, including the resilience of individual targets to interventional strategies, in order to develop effective therapies. Clearly, I/R is difficult to implement in the clinic. Instead, the elucidation of the functional outcomes may direct the development of novel pharmacologic or gene therapies based on the molecular changes that are responsible for cardioprotection. In this regard, the insight generated by this study facilitates further target characterization and selection to prevent ischemic injury and reverse remodeling of the human heart.Indeed, r-I/R without subsequent infarction did not cause significant myocardial damage and did not elevate the cardiac markers. The 10 min duration of ischemia was selected based on the guidelines on the management of the stable coronary artery diseaseHere, IPC was performed on healthy animals, but atherosclerosis and other cardiovascular co-morbidities may attenuate cardioprotection by IPCWe demonstrate for the first time that r-I/R stimuli provokes sequential changes in pathway networks and gene expression profiles not only in ischemic but also in the non-ischemia-affected regions of the myocardium; we introduce the term “intrinsic remote conditioning”, describing an intrinsic protective mechanism against adverse LV remodeling. This experimental approach, using the current, clinically relevant animal model, provides a useful tool for the identification of early and late r-I/R-induced gene expression networks, and may reveal relevant pathways for targeted drug intervention. Concerning the complexity of the response, it is likely that the simultaneous regulation of multiple targets  is a viable strategy for induction of robust cardioprotection.Animal investigations were carried out in accordance with the “Position of the American Heart Association on Research Animal Use,” as adopted by the AHA on November 11, 1984. The study was approved by the Ethics Committee on Animal Experimentation at the University of Kaposvar, Hungary. The study design is displayed in Domestic pigs underwent cardiac catheterization . The r-ITo prove the effect of IPC in SWOP ten domestic pigs were randomized into two groups with  and without  IPC stimulus .To assess the time-dependent gene expression alterations as well as pathways and pathway networks that are crucial for triggering cardioprotection and protection in the late window (SWOP), twelve pigs underwent r-I/R, while animals undergoing sham intervention (n = 8) served as controls (group Control). Baseline echocardiography and invasive LV hemodynamic measurements via a pigtail catheter  were performed before the preconditioning stimulus. Animals with r-I/R were randomized to groups r-I/R [5 h] (n = 6), or r-I/R [24 h] (n = 6) according to sacrificing time points. At 5 h and 24 h post r-I/R or sham-r-I/R, echocardiography and LV hemodynamics measurements were repeated. Animals were then sacrificed and pig hearts were explanted . MyocardHow to cite this article: Pavo, N. et al. Sequential activation of different pathway networks in ischemia-affected and non-affected myocardium, inducing intrinsic remote conditioning to prevent left ventricular remodeling. Sci. Rep.7, 43958; doi: 10.1038/srep43958 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.