| 1. |
- Barrenäs, Fredrik, 1981-
(författare)
-
Bioinformatic identification of disease associated pathways by network based analysis
- 2012
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Many common diseases are complex, meaning that they are caused by many interacting genes. This makes them difficult to study; to determine disease mechanisms, disease-associated genes must be analyzed in combination. Disease-associated genes can be detected using high-throughput methods, such as mRNA expression microarrays, DNA methylation microarrays and genome-wide association studies (GWAS), but determining how they interact to cause disease is an intricate challenge. One approach is to organize disease-associated genes into networks using protein-protein interactions (PPIs) and dissect them to identify disease causing pathways. Studies of complex disease can also be greatly facilitated by using an appropriate model system. In this dissertation, seasonal allergic rhinitis (SAR) served as a model disease. SAR is a common disease that is relatively easy to study. Also, the key disease cell types, like the CD4+ T cell, are known and can be cultured and activated in vitro by the disease causing pollen.The aim of this dissertation was to determine network properties of disease-associated genes, and develop methods to identify and validate networks of disease-associated genes. First, we showed that disease-associated genes have distinguishing network properties, one being that they co-localize in the human PPI network. This supported the existence of disease modules within the PPI network. We then identified network modules of genes whose mRNA expression was perturbed in human disease, and showed that the most central genes in those network modules were enriched for disease-associated polymorphisms identified by GWAS. As a case study, we identified disease modules using mRNA expression data from allergen-challenged CD4+ cells from patients with SAR. The case study identified and validated a novel disease-associated gene, FGF2 using GWAS data and RNAi mediated knockdown.Lastly, we examined how DNA methylation caused disease-associated mRNA expression changes in SAR. DNA methylation, but not mRNA expression profiles, could accurately distinguish allergic patients from healthy controls. Also, we found that disease-associated mRNA expression changes were associated with a low DNA methylation content and absence of CpG islands. Specifically within this group, we found a correlation between disease-associated mRNA expression changes and DNA methylation changes. Using ChIP-chip analysis, we found that targets of a known disease relevant transcription factor, IRF4, were also enriched among non CpG island genes with low methylation levels.Taken together, in this dissertation the network properties of disease-associated genes were examined, and then used to validate disease networks defined by mRNA expression data. We then examined regulatory mechanisms underlying disease-associated mRNA expression changes in a model disease. These studies support network-based analyses as a method to understand disease mechanisms and identify important disease causing genes, such as treatment targets or markers for personalized medication.
|
|
| 2. |
|
|
| 3. |
- Barrenäs, Fredrik, 1981, et al.
(författare)
-
Network properties of complex human disease genes identified through genome-wide association studies.
- 2009
-
Ingår i: PloS one. - San Francisco, CA San Francisco, CA, United StatesUnited States : Public Library of Science (PLoS). - 1932-6203. ; 4:11
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Previous studies of network properties of human disease genes have mainly focused on monogenic diseases or cancers and have suffered from discovery bias. Here we investigated the network properties of complex disease genes identified by genome-wide association studies (GWAs), thereby eliminating discovery bias. PRINCIPAL FINDINGS: We derived a network of complex diseases (n = 54) and complex disease genes (n = 349) to explore the shared genetic architecture of complex diseases. We evaluated the centrality measures of complex disease genes in comparison with essential and monogenic disease genes in the human interactome. The complex disease network showed that diseases belonging to the same disease class do not always share common disease genes. A possible explanation could be that the variants with higher minor allele frequency and larger effect size identified using GWAs constitute disjoint parts of the allelic spectra of similar complex diseases. The complex disease gene network showed high modularity with the size of the largest component being smaller than expected from a randomized null-model. This is consistent with limited sharing of genes between diseases. Complex disease genes are less central than the essential and monogenic disease genes in the human interactome. Genes associated with the same disease, compared to genes associated with different diseases, more often tend to share a protein-protein interaction and a Gene Ontology Biological Process. CONCLUSIONS: This indicates that network neighbors of known disease genes form an important class of candidates for identifying novel genes for the same disease.
|
|
| 4. |
- Benson, Mikael, 1954, et al.
(författare)
-
A haplotype in the inducible T-cell tyrosine kinase is a risk factor for seasonal allergic rhinitis.
- 2009
-
Ingår i: Allergy. - : Wiley. - 1398-9995 .- 0105-4538. ; 64:9, s. 1286-91
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Identification of disease-associated single nucleotide polymorphisms (SNPs) in seasonal allergic rhinitis (SAR) may be facilitated by focusing on genes in a disease-associated pathway. OBJECTIVE: To search for SNPs in genes that belong to the T-cell receptor (TCR) pathway and that change in expression in allergen-challenged CD4+ cells from patients with SAR. METHODS: CD4+ cells from patients with SAR were analysed with gene expression microarrays. Allele, genotype and haplotype frequencies were compared in 251 patients and 386 healthy controls. RESULTS: Gene expression microarray analysis of allergen-challenged CD4+ cells from patients with SAR showed that 25 of 38 TCR pathway genes were differentially expressed. A total of 62 SNPs were analysed in eight of the 25 genes; ICOS, IL4, IL5, IL13, CSF2, CTLA4, the inducible T-cell tyrosine kinase (ITK) and CD3D. Significant chi-squared values were identified for several markers in the ITK kinase gene region. A total of five SNPs were nominally significant at the 5% level. Haplotype analysis of the five significant SNPs showed increased frequency of a haplotype that covered most of the coding part of ITK. The functional relevance of ITK was supported by analysis of an independent material, which showed increased expression of ITK in allergen-challenged CD4+ cells from patients, but not from controls. CONCLUSION: Analysis of SNPs in TCR pathway genes revealed that a haplotype that covers a major part of the coding sequence of ITK is a risk factor for SAR.
|
|
| 5. |
- Chavali, Sreenivas, et al.
(författare)
-
MicroRNAs act complementarily to regulate disease-related mRNA modules in human diseases
- 2013
-
Ingår i: Rna-a Publication of the Rna Society. - : Cold Spring Harbor Laboratory. - 1355-8382 .- 1469-9001. ; 19:11, s. 1552-1562
-
Tidskriftsartikel (refereegranskat)abstract
- MicroRNAs (miRNAs) play a key role in regulating mRNA expression, and individual miRNAs have been proposed as diagnostic and therapeutic candidates. The identification of such candidates is complicated by the involvement of multiple miRNAs and mRNAs as well as unknown disease topology of the miRNAs. Here, we investigated if disease-associated miRNAs regulate modules of disease-associated mRNAs, if those miRNAs act complementarily or synergistically, and if single or combinations of miRNAs can be targeted to alter module functions. We first analyzed publicly available miRNA and mRNA expression data for five different diseases. Integrated target prediction and network-based analysis showed that the miRNAs regulated modules of disease-relevant genes. Most of the miRNAs acted complementarily to regulate multiple mRNAs. To functionally test these findings, we repeated the analysis using our own miRNA and mRNA expression data from CD4+ T cells from patients with seasonal allergic rhinitis. This is a good model of complex diseases because of its well-defined phenotype and pathogenesis. Combined computational and functional studies confirmed that miRNAs mainly acted complementarily and that a combination of two complementary miRNAs, miR-223 and miR-139-3p, could be targeted to alter disease-relevant module functions, namely, the release of type 2 helper T-cell (Th2) cytokines. Taken together, our findings indicate that miRNAs act complementarily to regulate modules of disease-related mRNAs and can be targeted to alter disease-relevant functions.
|
|
| 6. |
- Chavali, Sreenivas, et al.
(författare)
-
Network properties of human disease genes with pleiotropic effects
- 2010
-
Ingår i: BMC Systems Biology. - 1752-0509. ; 4
-
Tidskriftsartikel (refereegranskat)abstract
- The phenotypic consequence of a human disease gene is largely affected by the topological position of its protein product in the molecular interaction network. Here, we investigated the differences in properties of specific human disease genes that are associated with one phenotype and shared genes with pleiotropic effects in the context of molecular interaction networks. We find that the shared genes have an intermediate centrality between essential and specific genes. Shared genes causing phenotypically divergent diseases (phenodiv genes) are more central to those causing phenotypically similar diseases (phenosim genes). Shared genes had higher number of disease gene interactors compared to specific genes, implying a higher likelihood of finding a novel disease gene in the network neighborhood of shared genes. Specific genes are more co-expressed with their interactors than shared genes. Relatively restricted tissue co-expression with interactors appears to be a function of shared genes leading to pleiotropy. We demonstrate essential and phenodiv genes with comparable connectivities (degrees) are intra-modular and inter-modular hubs with the former highly co-expressed with their interactors contrary to the phenodiv genes. Essential genes are predominantly nuclear proteins with transcriptional regulator activities while phenodiv genes are cytoplasmic proteins involved in signal transduction. Our results demonstrate that the ability of a disease gene to influence the cellular network determines its role in manifesting different and divergent diseases.
|
|
| 7. |
- Hildebrandt, Franziska, 1994-, et al.
(författare)
-
scDual-Seq of Toxoplasma gondii-infected mouse BMDCs reveals heterogeneity and differential infection dynamics
- 2023
-
Ingår i: Frontiers in Immunology. - : Frontiers Media S.A.. - 1664-3224. ; 14
-
Tidskriftsartikel (refereegranskat)abstract
- Dendritic cells and macrophages are integral parts of the innate immune system and gatekeepers against infection. The protozoan pathogen, Toxoplasma gondii, is known to hijack host immune cells and modulate their immune response, making it a compelling model to study host-pathogen interactions. Here we utilize single cell Dual RNA-seq to parse out heterogeneous transcription of mouse bone marrow-derived dendritic cells (BMDCs) infected with two distinct genotypes of T. gondii parasites, over multiple time points post infection. We show that the BMDCs elicit differential responses towards T. gondii infection and that the two parasite lineages distinctly manipulate subpopulations of infected BMDCs. Co-expression networks define host and parasite genes, with implications for modulation of host immunity. Integrative analysis validates previously established immune pathways and additionally, suggests novel candidate genes involved in host-pathogen interactions. Altogether, this study provides a comprehensive resource for characterizing host-pathogen interplay at high-resolution.
|
|
| 8. |
- Nestor, Colm, et al.
(författare)
-
DNA Methylation Changes Separate Allergic Patients from Healthy Controls and May Reflect Altered CD4⁺ T-Cell Population Structure
- 2014
-
Ingår i: PLoS Genetics. - : Public Library of Science (PLoS). - 1553-7390 .- 1553-7404. ; 10:1
-
Tidskriftsartikel (refereegranskat)abstract
- Altered DNA methylation patterns in CD4+ T-cells indicate the importance of epigenetic mechanisms in inflammatory diseases. However, the identification of these alterations is complicated by the heterogeneity of most inflammatory diseases. Seasonal allergic rhinitis (SAR) is an optimal disease model for the study of DNA methylation because of its well-defined phenotype and etiology. We generated genome-wide DNA methylation (Npatients = 8, Ncontrols = 8) and gene expression (Npatients = 9, Ncontrols = 10) profiles of CD4+ T-cells from SAR patients and healthy controls using Illumina's HumanMethylation450 and HT-12 microarrays, respectively. DNA methylation profiles clearly and robustly distinguished SAR patients from controls, during and outside the pollen season. In agreement with previously published studies, gene expression profiles of the same samples failed to separate patients and controls. Separation by methylation (Npatients = 12, Ncontrols = 12), but not by gene expression (Npatients = 21, Ncontrols = 21) was also observed in an in vitro model system in which purified PBMCs from patients and healthy controls were challenged with allergen. We observed changes in the proportions of memory T-cell populations between patients (Npatients = 35) and controls (Ncontrols = 12), which could explain the observed difference in DNA methylation. Our data highlight the potential of epigenomics in the stratification of immune disease and represents the first successful molecular classification of SAR using CD4+ T cells.
|
|
| 9. |
- Pedicini, Marco, et al.
(författare)
-
Combining network modeling and gene expression microarray analysis to explore the dynamics of Th1 and Th2 cell regulation.
- 2010
-
Ingår i: PLoS computational biology. - : Public Library of Science (PLoS). - 1553-7358 .- 1553-734X. ; 6:12
-
Tidskriftsartikel (refereegranskat)abstract
- Two T helper (Th) cell subsets, namely Th1 and Th2 cells, play an important role in inflammatory diseases. The two subsets are thought to counter-regulate each other, and alterations in their balance result in different diseases. This paradigm has been challenged by recent clinical and experimental data. Because of the large number of genes involved in regulating Th1 and Th2 cells, assessment of this paradigm by modeling or experiments is difficult. Novel algorithms based on formal methods now permit the analysis of large gene regulatory networks. By combining these algorithms with in silico knockouts and gene expression microarray data from human T cells, we examined if the results were compatible with a counter-regulatory role of Th1 and Th2 cells. We constructed a directed network model of genes regulating Th1 and Th2 cells through text mining and manual curation. We identified four attractors in the network, three of which included genes that corresponded to Th0, Th1 and Th2 cells. The fourth attractor contained a mixture of Th1 and Th2 genes. We found that neither in silico knockouts of the Th1 and Th2 attractor genes nor gene expression microarray data from patients with immunological disorders and healthy subjects supported a counter-regulatory role of Th1 and Th2 cells. By combining network modeling with transcriptomic data analysis and in silico knockouts, we have devised a practical way to help unravel complex regulatory network topology and to increase our understanding of how network actions may differ in health and disease.
|
|
| 10. |
- Rohin Rajan, Meenu, et al.
(författare)
-
Comparative analysis of obesity-related cardiometabolic and renal biomarkers in human plasma and serum.
- 2019
-
Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1
-
Tidskriftsartikel (refereegranskat)abstract
- The search for biomarkers associated with obesity-related diseases is ongoing, but it is not clear whether plasma and serum can be used interchangeably in this process. Here we used high-throughput screening to analyze 358 proteins and 76 lipids, selected because of their relevance to obesity-associated diseases, in plasma and serum from age- and sex-matched lean and obese humans. Most of the proteins/lipids had similar concentrations in plasma and serum, but a subset showed significant differences. Notably, a key marker of cardiovascular disease PAI-1 showed a difference in concentration between the obese and lean groups only in plasma. Furthermore, some biomarkers showed poor correlations between plasma and serum, including PCSK9, an important regulator of cholesterol homeostasis. Collectively, our results show that the choice of biofluid may impact study outcome when screening for obesity-related biomarkers and we identify several markers where this will be the case.
|
|
