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1.
Sci Data ; 6(1): 151, 2019 08 14.
Article in English | MEDLINE | ID: mdl-31413325

ABSTRACT

Alzheimer's disease and other types of dementia are the top cause for disabilities in later life and various types of experiments have been performed to understand the underlying mechanisms of the disease with the aim of coming up with potential drug targets. These experiments have been carried out by scientists working in different domains such as proteomics, molecular biology, clinical diagnostics and genomics. The results of such experiments are stored in the databases designed for collecting data of similar types. However, in order to get a systematic view of the disease from these independent but complementary data sets, it is necessary to combine them. In this study we describe a heterogeneous network-based data set for Alzheimer's disease (HENA). Additionally, we demonstrate the application of state-of-the-art graph convolutional networks, i.e. deep learning methods for the analysis of such large heterogeneous biological data sets. We expect HENA to allow scientists to explore and analyze their own results in the broader context of Alzheimer's disease research.


Subject(s)
Alzheimer Disease/genetics , Deep Learning , Epistasis, Genetic , Gene Expression , Humans , Protein Interaction Mapping , Two-Hybrid System Techniques
2.
Sci Rep ; 7(1): 7553, 2017 08 08.
Article in English | MEDLINE | ID: mdl-28790368

ABSTRACT

Psoriasis is a chronic inflammatory disease that affects skin and is associated with systemic inflammation and many serious comorbidities ranging from metabolic syndrome to cancer. Important discoveries about psoriasis pathogenesis have enabled the development of effective biological treatments blocking the T helper 17 pathway. However, it has not been settled whether psoriasis is a T cell-mediated autoimmune disease or an autoinflammatory disorder that is driven by exaggerated innate immune signalling. Our comparative gene expression and hierarchical cluster analysis reveal important gene circuits involving innate receptors. Innate immune activation is indicated by increased absent in melanoma 2 (AIM2) inflammasome gene expression and active caspase 1 staining in psoriatic lesional skin. Increased eomesodermin (EOMES) expression in lesional and non-lesional skin is suggestive of innate-like virtual memory CD8+ T cell infiltration. We found that signs of systemic inflammation were present in most of the patients, correlated with the severity of the disease, and pointed to IL-6 involvement in the pathogenesis of psoriatic arthritis. Among the circulating T cell subpopulations, we identified a higher proportion of terminally differentiated or senescent CD8+ T cells, especially in patients with long disease duration, suggesting premature immunosenescence and its possible implications for psoriasis co-morbidities.


Subject(s)
Immunity, Innate/immunology , Immunosenescence/immunology , Psoriasis/immunology , Skin/immunology , Adult , Case-Control Studies , Cytokines/blood , Cytokines/genetics , Cytokines/metabolism , Female , Gene Expression/immunology , Humans , Immunity, Innate/genetics , Immunosenescence/genetics , Inflammation/genetics , Inflammation/immunology , Male , Middle Aged , Psoriasis/blood , Psoriasis/genetics , Skin/metabolism , Skin/pathology , T-Lymphocyte Subsets/immunology , T-Lymphocyte Subsets/metabolism , Young Adult
3.
Neurotoxicology ; 50: 56-70, 2015 Sep.
Article in English | MEDLINE | ID: mdl-26238599

ABSTRACT

Functional assays, such as the "migration inhibition of neural crest cells" (MINC) developmental toxicity test, can identify toxicants without requiring knowledge on their mode of action (MoA). Here, we were interested, whether (i) inhibition of migration by structurally diverse toxicants resulted in a unified signature of transcriptional changes; (ii) whether statistically-identified transcript patterns would inform on compound grouping even though individual genes were little regulated, and (iii) whether analysis of a small group of biologically-relevant transcripts would allow the grouping of compounds according to their MoA. We analyzed transcripts of 35 'migration genes' after treatment with 16 migration-inhibiting toxicants. Clustering, principal component analysis and correlation analyses of the data showed that mechanistically related compounds (e.g. histone deacetylase inhibitors (HDACi), PCBs) triggered similar transcriptional changes, but groups of structurally diverse toxicants largely differed in their transcriptional effects. Linear discriminant analysis (LDA) confirmed the specific clustering of HDACi across multiple separate experiments. Similarity of the signatures of the HDACi trichostatin A and suberoylanilide hydroxamic acid to the one of valproic acid (VPA), suggested that the latter compound acts as HDACi when impairing neural crest migration. In conclusion, the data suggest that (i) a given functional effect (e.g. inhibition of migration) can be associated with highly diverse signatures of transcript changes; (ii) statistically significant grouping of mechanistically-related compounds can be achieved on the basis of few genes with small regulations. Thus, incorporation of mechanistic markers in functional in vitro tests may support read-across procedures, also for structurally un-related compounds.


Subject(s)
Cell Movement/drug effects , Hazardous Substances/pharmacology , Histone Deacetylase Inhibitors/pharmacology , Neural Crest/drug effects , Transcription, Genetic/drug effects , Cell Line, Transformed , Discriminant Analysis , Gene Expression Profiling , Green Fluorescent Proteins/genetics , Green Fluorescent Proteins/metabolism , Human Embryonic Stem Cells , Humans , Hydroxamic Acids/pharmacology , Oligonucleotide Array Sequence Analysis , Time Factors , Toxicity Tests , Transfection , Up-Regulation/drug effects , Vorinostat
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