| 1. |
- Acosta-Herrera, M, et al.
(författare)
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Genome-wide meta-analysis reveals shared new loci in systemic seropositive rheumatic diseases
- 2019
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Ingår i: Annals of the rheumatic diseases. - : BMJ. - 1468-2060 .- 0003-4967. ; 78:3, s. 311-319
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Tidskriftsartikel (refereegranskat)abstract
- Immune-mediated inflammatory diseases (IMIDs) are heterogeneous and complex conditions with overlapping clinical symptoms and elevated familial aggregation, which suggests the existence of a shared genetic component. In order to identify this genetic background in a systematic fashion, we performed the first cross-disease genome-wide meta-analysis in systemic seropositive rheumatic diseases, namely, systemic sclerosis, systemic lupus erythematosus, rheumatoid arthritis and idiopathic inflammatory myopathies.MethodsWe meta-analysed ~6.5 million single nucleotide polymorphisms in 11 678 cases and 19 704 non-affected controls of European descent populations. The functional roles of the associated variants were interrogated using publicly available databases.ResultsOur analysis revealed five shared genome-wide significant independent loci that had not been previously associated with these diseases: NAB1, KPNA4-ARL14, DGQK, LIMK1 and PRR12. All of these loci are related with immune processes such as interferon and epidermal growth factor signalling, response to methotrexate, cytoskeleton dynamics and coagulation cascade. Remarkably, several of the associated loci are known key players in autoimmunity, which supports the validity of our results. All the associated variants showed significant functional enrichment in DNase hypersensitivity sites, chromatin states and histone marks in relevant immune cells, including shared expression quantitative trait loci. Additionally, our results were significantly enriched in drugs that are being tested for the treatment of the diseases under study.ConclusionsWe have identified shared new risk loci with functional value across diseases and pinpoint new potential candidate loci that could be further investigated. Our results highlight the potential of drug repositioning among related systemic seropositive rheumatic IMIDs.
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| 3. |
- Gallud, A, et al.
(författare)
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Cationic gold nanoparticles elicit mitochondrial dysfunction: a multi-omics study
- 2019
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1, s. 4366-
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Tidskriftsartikel (refereegranskat)abstract
- Systems biology is increasingly being applied in nanosafety research for observing and predicting the biological perturbations inflicted by exposure to nanoparticles (NPs). In the present study, we used a combined transcriptomics and proteomics approach to assess the responses of human monocytic cells to Au-NPs of two different sizes with three different surface functional groups, i.e., alkyl ammonium bromide, alkyl sodium carboxylate, or poly(ethylene glycol) (PEG)-terminated Au-NPs. Cytotoxicity screening using THP-1 cells revealed a pronounced cytotoxicity for the ammonium-terminated Au-NPs, while no cell death was seen after exposure to the carboxylated or PEG-modified Au-NPs. Moreover, Au-NR3+ NPs, but not the Au-COOH NPs, were found to trigger dose-dependent lethality in vivo in the model organism, Caenorhabditis elegans. RNA sequencing combined with mass spectrometry-based proteomics predicted that the ammonium-modified Au-NPs elicited mitochondrial dysfunction. The latter results were validated by using an array of assays to monitor mitochondrial function. Au-NR3+ NPs were localized in mitochondria of THP-1 cells. Moreover, the cationic Au-NPs triggered autophagy in macrophage-like RFP-GFP-LC3 reporter cells, and cell death was aggravated upon inhibition of autophagy. Taken together, these studies have disclosed mitochondria-dependent effects of cationic Au-NPs resulting in the rapid demise of the cells.
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| 6. |
- Backlund, J., et al.
(författare)
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C57BL/6 mice need MHC class II Aq to develop collagen-induced arthritis dependent on autoreactive T cells
- 2013
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Ingår i: Annals of the Rheumatic Diseases. - : BMJ. - 0003-4967 .- 1468-2060. ; 72:7, s. 1225-1232
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Tidskriftsartikel (refereegranskat)abstract
- INTRODUCTION: Collagen-induced arthritis (CIA) has traditionally been performed in MHC class II A(q)-expressing mice, whereas most genetically modified mice are on the C57BL/6 background (expressing the b haplotype of the major histocompatibility complex (MHC) class II region). However, C57BL/6 mice develop arthritis after immunisation with chicken-derived collagen type II (CII), but arthritis susceptibility has been variable, and the immune specificity has not been clarified. OBJECTIVE: To establish a CIA model on the C57BL/6 background with a more predictable and defined immune response to CII. RESULTS: Both chicken and rat CII were arthritogenic in C57BL/6 mice provided they were introduced with high doses of Mycobacterium tuberculosis adjuvant. However, contaminating pepsin was strongly immunogenic and was essential for arthritis development. H-2(b)-restricted T cell epitopes on chicken or rat CII could not be identified, but expression of A(q) on the C57BL/6 background induced T cell response to the CII260-270 epitope, and also prolonged the arthritis to be more chronic. CONCLUSIONS: The putative (auto)antigen and its arthritogenic determinants in C57BL/6 mice remains undisclosed, questioning the value of the model for addressing T cell-driven pathological pathways in arthritis. To circumvent this impediment, we recommend MHC class II congenic C57BL/6N.Q mice, expressing A(q), with which T cell determinants have been thoroughly characterised.
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| 7. |
- Fortino, V, et al.
(författare)
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Biomarkers of nanomaterials hazard from multi-layer data
- 2022
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 13:1, s. 3798-
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Tidskriftsartikel (refereegranskat)abstract
- There is an urgent need to apply effective, data-driven approaches to reliably predict engineered nanomaterial (ENM) toxicity. Here we introduce a predictive computational framework based on the molecular and phenotypic effects of a large panel of ENMs across multiple in vitro and in vivo models. Our methodology allows for the grouping of ENMs based on multi-omics approaches combined with robust toxicity tests. Importantly, we identify mRNA-based toxicity markers and extensively replicate them in multiple independent datasets. We find that models based on combinations of omics-derived features and material intrinsic properties display significantly improved predictive accuracy as compared to physicochemical properties alone.
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