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NeuroGeM, a knowledgebase of genetic modifiers in neurodegenerative diseases.

ABSTRACT: BACKGROUND:Neurodegenerative diseases (NDs) are characterized by the progressive loss of neurons in the human brain. Although the majority of NDs are sporadic, evidence is accumulating that they have a strong genetic component. Therefore, significant efforts have been made in recent years to not only identify disease-causing genes but also genes that modify the severity of NDs, so-called genetic modifiers. To date there exists no compendium that lists and cross-links genetic modifiers of different NDs. DESCRIPTION:In order to address this need, we present NeuroGeM, the first comprehensive knowledgebase providing integrated information on genetic modifiers of nine different NDs in the model organisms D. melanogaster, C. elegans, and S. cerevisiae. NeuroGeM cross-links curated genetic modifier information from the different NDs and provides details on experimental conditions used for modifier identification, functional annotations, links to homologous proteins and color-coded protein-protein interaction networks to visualize modifier interactions. We demonstrate how this database can be used to generate new understanding through meta-analysis. For instance, we reveal that the Drosophila genes DnaJ-1, thread, Atx2, and mub are generic modifiers that affect multiple if not all NDs. CONCLUSION:As the first compendium of genetic modifiers, NeuroGeM will assist experimental and computational scientists in their search for the pathophysiological mechanisms underlying NDs. http://chibi.ubc.ca/neurogem.

SUBMITTER: Na D

PROVIDER: S-EPMC3833180 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature

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NeuroGeM, a knowledgebase of genetic modifiers in neurodegenerative diseases.

Na Dokyun D Rouf Mushfiqur M O'Kane Cahir J CJ Rubinsztein David C DC Gsponer Jörg J

BMC medical genomics 20131114

<h4>Background</h4>Neurodegenerative diseases (NDs) are characterized by the progressive loss of neurons in the human brain. Although the majority of NDs are sporadic, evidence is accumulating that they have a strong genetic component. Therefore, significant efforts have been made in recent years to not only identify disease-causing genes but also genes that modify the severity of NDs, so-called genetic modifiers. To date there exists no compendium that lists and cross-links genetic modifiers of ...[more]

PMID: 24229347

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Project description:BackgroundAn array of experimental models have been developed in the small model organisms C. elegans, S. cerevisiae and D. melanogaster for the study of various neurodegenerative diseases including Alzheimer's disease, Parkinson's disease, and expanded polyglutamine diseases as exemplified by Huntington's disease (HD) and related ataxias. Genetic approaches to determine the nature of regulators of the disease phenotypes have ranged from small scale to essentially whole genome screens. The published data covers distinct models in all three organisms and one important question is the extent to which shared genetic factors can be uncovered that affect several or all disease models. Surprisingly it has appeared that there may be relatively little overlap and that many of the regulators may be organism or disease-specific. There is, however, a need for a fully integrated analysis of the available genetic data based on careful comparison of orthologues across the species to determine the real extent of overlap.ResultsWe carried out an integrated analysis using C. elegans as the baseline model organism since this is the most widely studied in this context. Combination of data from 28 published studies using small to large scale screens in all three small model organisms gave a total of 950 identifications of genetic regulators. Of these 624 were separate genes with orthologues in C. elegans. In addition, 34 of these genes, which all had human orthologues, were found to overlap across studies. Of the common genetic regulators some such as chaperones, ubiquitin-related enzymes (including the E3 ligase CHIP which directly links the two pathways) and histone deacetylases were involved in expected pathways whereas others such as the peroxisomal acyl CoA-oxidase suggest novel targets for neurodegenerative disease therapyConclusionsWe identified a significant number of overlapping regulators of neurodegenerative disease models. Since the diseases have, as an underlying feature, protein aggregation phenotypes it was not surprising that some of the overlapping genes encode proteins involved in protein folding and protein degradation. Interestingly, however, some of the overlapping genes encode proteins that have not previously featured in targeted studies of neurodegeneration and this information will form a useful resource to be exploited in further studies of potential drug-targets.

Project description:Neurodegenerative diseases of the central nervous system are characterised by pathogenetic cellular and molecular changes in specific areas of the brain that lead to the dysfunction and/or loss of explicit neuronal populations. Despite exhibiting different clinical profiles and selective neuronal loss, common features such as abnormal protein deposition, dysfunctional cellular transport, mitochondrial deficits, glutamate excitotoxicity and inflammation are observed in most, if not all, neurodegenerative disorders, suggesting converging pathways of neurodegeneration. We have generated comparative genome-wide gene expression data for Alzheimer’s disease, amyotrophic lateral sclerosis, Huntington’s disease, multiple sclerosis, Parkinson’s disease and schizophrenia using an extensive cohort of well characterised post-mortem CNS tissues. The analysis of whole genome expression patterns across these major disorders offers an outstanding opportunity not only to look into exclusive disease specific changes, but more importantly to uncover potential common molecular pathogenic mechanisms that could be targeted for therapeutic gain. Surprisingly, no dysregulated gene that passed our selection criteria was found in common across all 6 diseases using our primary method of analysis. However, 61 dysregulated genes were shared when comparing five and four diseases. Our analysis indicates firstly the involvement of common neuronal homeostatic, survival and synaptic plasticity pathways. Secondly, we report changes to immunoregulatory and immunomodulatory pathways in all diseases. Our secondary method of analysis confirmed significant up-regulation of a number of genes in diseases presenting degeneration and showed that somatostatin was downregulated in all 6 diseases. The latter is supportive of a general role for neuroinflammation in the pathogenesis and/or response to neurodegeneration. Unravelling the detailed nature of the molecular changes regulating inflammation in the CNS is key to the development of novel therapeutic approaches for these chronic conditions. A total of 113 cases were selected retrospectively on the basis of a confirmed clinical and neuropathological diagnosis and snap-frozen brain blocks were provided by various tissue banks within the BrainNet Europe network. Total RNA was extracted from dissected snap-frozen tissue (< 100 mg) by the individual laboratories according to a BNE optimised common protocol using the RNeasy(r) tissue lipid mini kit (Qiagen Ltd, Crawley, UK) according to the manufacturer's instructions, and was stored at -80C until further use. Gene expression analysis was performed on the RNA samples using the Illumina whole genome HumanRef8 v2 BeadChip (Illumina, London, UK). All the labelling and hybridisation of the samples was carried out in a single experiment by the Imperial College group to reduce the technical variability. RNA samples were prepared for array analysis using the Illumina TotalPrep(tm)-96 RNA Amplification Kit (Ambion/Applied Biosystems, Warrington, UK). Finally, the BeadChips we re scanned using the Illumina BeadArray Reader. The data was extracted using BeadStudio 3.2 (Illumina). Data normalisation and gene differential expression analyses were conducted using the Rosetta error models available in the Rosetta Resolver(r) system (Rosetta Biosoftware, Seattle, Wa, USA). Two samples presented very low signal expression most likely due to hybridization problems and did not pass the quality control test. They are not represented here. One of the 2 samples was a replicate, therefore there was loss of only 1 case bringing the grand total of cases used to 112 (total of samples of 118 including 6 replicates).

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NeuroGeM, a knowledgebase of genetic modifiers in neurodegenerative diseases.

Publications

NeuroGeM, a knowledgebase of genetic modifiers in neurodegenerative diseases.

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