Network analysis of single nucleotide polymorphisms in asthma

Renkonen, Jutta; Joenväära, Sakari; Parviainen, Ville; Mattila, Pirkko; Renkonen, Risto

doi:10.2147/jaa.s14459

Cited by 15 publications

(13 citation statements)

References 28 publications

(18 reference statements)

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“…Networks have been used to analyze a wide range of datasets, including gene–disease interactions [29] and disease–gene associations [30]. A molecular unipartite (single variable) association network of asthma with 129 SNP has been published by Renkonen et al [31]. Though asthma classification was not attempted, important associations between subgroups of protein classes like Toll-like receptors and chemokines were demonstrated.…”

Section: Network Analysis Methodsmentioning

confidence: 99%

Strategies for Molecular Classification of Asthma Using Bipartite Network Analysis of Cytokine Expression

Pillai

Divekar

Brasier

et al. 2012

Curr Allergy Asthma Rep

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Asthma is a chronic inflammatory disease of the airways that leads to various degrees of recurrent respiratory symptoms affecting patients globally. Specific subgroups of asthma patients have severe disease leading to increased healthcare costs and socioeconomic burden. Despite the overwhelming prevalence of the asthma, there are limitations in predicting response to therapy and identifying patients who are at increased risk of morbidity. This syndrome presents with common clinical signs and symptoms; however, awareness of subgroups of asthma patients with distinct characteristics has surfaced in recent years. Investigators attempt to describe the phenotypes of asthma to ultimately assist with diagnostic and therapeutic applications. Approaches to asthma phenotyping are multifold; however, it can be partitioned into 2 essential groups, clinical phenotyping and molecular phenotyping. Innovative techniques such as bipartite network analysis and visual analytics introduce a new dimension of data analysis to identify underlying mechanistic pathways.

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Section: Network Analysis Methodsmentioning

confidence: 99%

Strategies for Molecular Classification of Asthma Using Bipartite Network Analysis of Cytokine Expression

Pillai

Divekar

Brasier

et al. 2012

Curr Allergy Asthma Rep

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“…Therefore, we suspected an enrichment of asthma risk genes within the STAT6-regulated genes in Th2 cells compared to STAT4-regulated genes in Th1 cells. Indeed, the comparison of asthma risk genes (Renkonen et al, 2010) with the datasets of STAT6-regulated genes in Th2 cells and STAT4-regulated genes in Th1 cells showed an enrichment of asthma risk genes in the set of STAT6-regulated genes.…”

Section: Stat6-regulated Genes Are Associated With Asthma Risk Genesmentioning

confidence: 99%

“…A meta-analysis of SNPs by Renkonen et al (2010) identified 125 asthma-associated genes. Filtering these risk genes for TFs, cytokines, and cytokine receptors (microarray data for Th cells, Wei et al, 2009) yielded 33 asthma risk genes ( Figure 3B, red), which were integrated with the 100 STAT6-regulated genes in Th2 cells ( Figure 3B, green) and the 274 STAT4-regulated genes in Th1 cells ( Figure 3B, gray).…”

Section: Stat6-regulated Genes Are Associated With Asthma Risk Genesmentioning

confidence: 99%

“…Only 64 of the 100 STAT6-regulated genes were preferentially expressed in one cell subtype ( Figure 3A). The log2(fold change) values and corresponding expression preferences are listed in S3 Table. Asthma risk genes within the STAT6-regulated genes A list of 125 asthma risk genes was extracted by meta-analysis of SNPs from Renkonen et al (2010) and filtered for TFs, cytokines, and cytokine receptors (Wei et al, 2009) (S4 Table). The overlap of the 33 asthma risk genes encoding TFs, cytokines, or cytokine receptors with the 100 STAT6-regulated genes in Th2 cells and with the 274 STAT4-regulated genes in Th1 cells (Vahedi et al, 2012) is shown in Figure 3B.…”

Section: Gene Expression Preferences Of Stat6-regulated Genesmentioning

confidence: 99%

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Data integration for identification of important transcription factors of STAT6-mediated cell fate decisions

et al. 2016

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ABSTRACT. Data integration has become a useful strategy for uncovering new insights into complex biological networks. We studied whether this approach can help to delineate the signal transducer and activator of transcription 6 (STAT6)-mediated transcriptional network driving T helper (Th) 2 cell fate decisions. To this end, we performed an integrative analysis of publicly available RNA-seq data of Stat6-knockout mouse studies together with STAT6 ChIP-seq data and our own gene expression time series data during Th2 cell differentiation. We focused on transcription factors (TFs), cytokines, and cytokine receptors and delineated 59 positively and 41 negatively STAT6-regulated genes, which were used to construct a transcriptional network around STAT6. The network illustrates that important and well-known TFs for Th2 cell differentiation are positively regulated by STAT6 and act either as activators for Th2 cells (e.g., Gata3, Atf3, Satb1, Nfil3, Maf, and Pparg) or as suppressors for other Th cell subpopulations such as Th1 (e.g., Ar), Th17 (e.g., Etv6), or iTreg (e.g., Stat3 and Hif1a) cells. Moreover, our approach reveals 11 TFs (e.g., Atf5, Creb3l2, and Asb2) with unknown functions in Th cell differentiation. This fact together with the observed enrichment of asthma risk genes among those regulated by STAT6 underlines the potential value of the data integration strategy used here. Thus, our results clearly support the opinion that data integration is a useful tool to delineate complex physiological processes.

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“…In more advanced systems of the world, trend data flow and records of information feedback of asthma and allergy are different, but finally, all data from data sources starts and ends with National Asthma and Allergy Information System in the country (10). …”

Section: Discussionmentioning

confidence: 99%

Proposed Model for Iranian National System of Registration of Allergy and Asthma

Yazdanian¹,

Safdari²,

Mahsoori³

et al. 2013

Acta Inform Med

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Introduction:Asthma and allergies in addition to demanding social costs–the economic community, one of the major causes of morbidity and mortality in the world is considered. In the last decade in Iran despite the positive developments in many areas of health records into categories based asthma and allergy international standards, less attention has been paid. Improving the quality of care system, identifying groups at risk of asthma and allergies, control plan, prevention and assessment of asthma and allergies due to possible that when allergy and asthma information registration system and create the complete and timely data to be collected. Considering now an efficient national system of registration allergy and asthma that can meet the health needs can no need for this study was felt.Materials and Methods:This study, study–the comparison was done in the years 2010-2011. In this research, using library resources, information networks and consultations with experts inside the country gathered on the main axis and branches of national registration system, asthma and allergies in American countries–Australia and England were examined and given economic conditions, cultural and geographical themes for our records system, the axes were proposed objectives, structure, data elements, standard registration process? Data and classification systems are given.Results:The proposed model for national registration system, asthma and allergies in the country is shown in a table. In this table the proposed system based on six main “targets”, “structure”, “data elements”, “data collection process,” “registration criteria” and “classification system” is designed.Conclusion:The results and recommendations to the International Institute for asthma and allergies, reduction in low registers, and can increase the quality of the proposed model, including advantages in comparison with the existing system of the country noted.

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Network analysis of single nucleotide polymorphisms in asthma

Cited by 15 publications

References 28 publications

Strategies for Molecular Classification of Asthma Using Bipartite Network Analysis of Cytokine Expression

Strategies for Molecular Classification of Asthma Using Bipartite Network Analysis of Cytokine Expression

Data integration for identification of important transcription factors of STAT6-mediated cell fate decisions

Proposed Model for Iranian National System of Registration of Allergy and Asthma

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