| 1. |
- Buzzao, Davide, et al.
(författare)
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TOPAS, a network-based approach to detect disease modules in a top-down fashion
- 2022
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Ingår i: NAR Genomics and Bioinformatics. - : Oxford University Press (OUP). - 2631-9268. ; 4:4
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Tidskriftsartikel (refereegranskat)abstract
- A vast scenario of potential disease mechanisms and remedies is yet to be discovered. The field of Network Medicine has grown thanks to the massive amount of high-throughput data and the emerging evidence that disease-related proteins form ‘disease modules’. Relying on prior disease knowledge, network-based disease module detection algorithms aim at connecting the list of known disease associated genes by exploiting interaction networks. Most existing methods extend disease modules by iteratively adding connector genes in a bottom-up fashion, while top-down approaches remain largely unexplored. We have created TOPAS, an iterative approach that aims at connecting the largest number of seed nodes in a top-down fashion through connectors that guarantee the highest flow of a Random Walk with Restart in a network of functional associations. We used a corpus of 382 manually selected functional gene sets to benchmark our algorithm against SCA, DIAMOnD, MaxLink and ROBUST across four interactomes. We demonstrate that TOPAS outperforms competing methods in terms of Seed Recovery Rate, Seed to Connector Ratio and consistency during module detection. We also show that TOPAS achieves competitive performance in terms of biological relevance of detected modules and scalability.
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| 2. |
- Castresana-Aguirre, Miguel, 1991-, et al.
(författare)
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Benefits and Challenges of Pre-clustered Network-Based Pathway Analysis
- 2022
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Ingår i: Frontiers in Genetics. - : Frontiers Media SA. - 1664-8021. ; 13
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Tidskriftsartikel (refereegranskat)abstract
- Functional analysis of gene sets derived from experiments is typically done by pathway annotation. Although many algorithms exist for analyzing the association between a gene set and a pathway, an issue which is generally ignored is that gene sets often represent multiple pathways. In such cases an association to a pathway is weakened by the presence of genes associated with other pathways. A way to counteract this is to cluster the gene set into more homogenous parts before performing pathway analysis on each module. We explored whether network-based pre-clustering of a query gene set can improve pathway analysis. The methods MCL, Infomap, and MGclus were used to cluster the gene set projected onto the FunCoup network. We characterized how well these methods are able to detect individual pathways in multi-pathway gene sets, and applied each of the clustering methods in combination with four pathway analysis methods: Gene Enrichment Analysis, BinoX, NEAT, and ANUBIX. Using benchmarks constructed from the KEGG pathway database we found that clustering can be beneficial by increasing the sensitivity of pathway analysis methods and by providing deeper insights of biological mechanisms related to the phenotype under study. However, keeping a high specificity is a challenge. For ANUBIX, clustering caused a minor loss of specificity, while for BinoX and NEAT it caused an unacceptable loss of specificity. GEA had very low sensitivity both before and after clustering. The choice of clustering method only had a minor effect on the results. We show examples of this approach and conclude that clustering can improve overall pathway annotation performance, but should only be used if the used enrichment method has a low false positive rate.
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| 3. |
- Guala, Dimitri, 1979-
(författare)
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Functional association networks for disease gene prediction
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Mapping of the human genome has been instrumental in understanding diseasescaused by changes in single genes. However, disease mechanisms involvingmultiple genes have proven to be much more elusive. Their complexityemerges from interactions of intracellular molecules and makes them immuneto the traditional reductionist approach. Only by modelling this complexinteraction pattern using networks is it possible to understand the emergentproperties that give rise to diseases.The overarching term used to describe both physical and indirect interactionsinvolved in the same functions is functional association. FunCoup is oneof the most comprehensive networks of functional association. It uses a naïveBayesian approach to integrate high-throughput experimental evidence of intracellularinteractions in humans and multiple model organisms. In the firstupdate, both the coverage and the quality of the interactions, were increasedand a feature for comparing interactions across species was added. The latestupdate involved a complete overhaul of all data sources, including a refinementof the training data and addition of new class and sources of interactionsas well as six new species.Disease-specific changes in genes can be identified using high-throughputgenome-wide studies of patients and healthy individuals. To understand theunderlying mechanisms that produce these changes, they can be mapped tocollections of genes with known functions, such as pathways. BinoX wasdeveloped to map altered genes to pathways using the topology of FunCoup.This approach combined with a new random model for comparison enables BinoXto outperform traditional gene-overlap-based methods and other networkbasedtechniques.Results from high-throughput experiments are challenged by noise and biases,resulting in many false positives. Statistical attempts to correct for thesechallenges have led to a reduction in coverage. Both limitations can be remediedusing prioritisation tools such as MaxLink, which ranks genes using guiltby association in the context of a functional association network. MaxLink’salgorithm was generalised to work with any disease phenotype and its statisticalfoundation was strengthened. MaxLink’s predictions were validatedexperimentally using FRET.The availability of prioritisation tools without an appropriate way to comparethem makes it difficult to select the correct tool for a problem domain.A benchmark to assess performance of prioritisation tools in terms of theirability to generalise to new data was developed. FunCoup was used for prioritisationwhile testing was done using cross-validation of terms derived fromGene Ontology. This resulted in a robust and unbiased benchmark for evaluationof current and future prioritisation tools. Surprisingly, previously superiortools based on global network structure were shown to be inferior to a localnetwork-based tool when performance was analysed on the most relevant partof the output, i.e. the top ranked genes.This thesis demonstrates how a network that models the intricate biologyof the cell can contribute with valuable insights for researchers that study diseaseswith complex genetic origins. The developed tools will help the researchcommunity to understand the underlying causes of such diseases and discovernew treatment targets. The robust way to benchmark such tools will help researchersto select the proper tool for their problem domain.
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| 4. |
- Guala, Dimitri, 1979-, et al.
(författare)
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Network Crosstalk as a Basis for Drug Repurposing
- 2022
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Ingår i: Frontiers in Genetics. - : Frontiers Media SA. - 1664-8021. ; 13
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Tidskriftsartikel (refereegranskat)abstract
- The need for systematic drug repurposing has seen a steady increase over the past decade and may be particularly valuable to quickly remedy unexpected pandemics. The abundance of functional interaction data has allowed mapping of substantial parts of the human interactome modeled using functional association networks, favoring network-based drug repurposing. Network crosstalk-based approaches have never been tested for drug repurposing despite their success in the related and more mature field of pathway enrichment analysis. We have, therefore, evaluated the top performing crosstalk-based approaches for drug repurposing. Additionally, the volume of new interaction data as well as more sophisticated network integration approaches compelled us to construct a new benchmark for performance assessment of network-based drug repurposing tools, which we used to compare network crosstalk-based methods with a state-of-the-art technique. We find that network crosstalk-based drug repurposing is able to rival the state-of-the-art method and in some cases outperform it.
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| 5. |
- Jaervinen, Elina, et al.
(författare)
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Cultured lymphocytes' mitochondrial genome integrity is not altered by cladribine
- 2023
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Ingår i: Clinical and Experimental Immunology. - 0009-9104 .- 1365-2249. ; 214:3, s. 304-313
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Tidskriftsartikel (refereegranskat)abstract
- Cladribine tablets are a treatment for multiple sclerosis with effects on lymphocytes, yet its mode of action has not been fully established. Here, we analyzed the effects of cladribine on mitochondrial DNA integrity in lymphocytes. We treated cultured human T-cell lines (CCRF-CEM and Jurkat) with varying concentrations of cladribine to mimic the slow cell depletion observed in treated patients. The CCRF-CEM was more susceptible to cladribine than Jurkat cells. In both cells, mitochondrial protein synthesis, mitochondrial DNA copy number, and mitochondrial cytochrome-c oxidase-I mRNA mutagenesis was not affected by cladribine, while caspase-3 cleavage was detected in Jurkat cells at 100 nM concentration. Cladribine treatment at concentrations up to 10 nM in CCRF-CEM and 100 nM in Jurkat cells did not induce significant increase in mitochondrial DNA mutations. Peripheral blood mononuclear cells from eight multiple sclerosis patients and four controls were cultured with or without an effective dose of cladribine (5 nM). However, we did not find any differences in mitochondrial DNA somatic mutations in lymphocyte subpopulations (CD4+, CD8+, and CD19+) between treated versus nontreated cells. The overall mutation rate was similar in patients and controls. When different lymphocyte subpopulations were compared, greater mitochondrial DNA mutation levels were detected in CD8+ (P = 0.014) and CD4+ (P = 0.038) as compared to CD19+ cells, these differences were independent of cladribine treatment. We conclude that T cells have more detectable mitochondrial DNA mutations than B cells, and cladribine has no detectable mutagenic effect on lymphocyte mitochondrial genome nor does it impair mitochondrial function in human T-cell lines. Cultured leukemic human T-cell lines and cultured ex vivo human peripheral mononuclear cells from patients with multiple sclerosis and controls were treated with cladribine in vitro . In the T-cell lines mitochondrial protein synthesis, DNA copy number and mutagenesis were not affected by cladribine. In the ex vivo lymphocyte subpopulations (CD4+, CD8+, and CD19+), there were no significant differences in mitochondrial DNA mutations between treated versus nontreated cells. Graphical Abstract
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