31 research outputs found

    A Cross-Study Transcriptional Analysis of Parkinson's Disease

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    The study of Parkinson's disease (PD), like other complex neurodegenerative disorders, is limited by access to brain tissue from patients with a confirmed diagnosis. Alternatively the study of peripheral tissues may offer some insight into the molecular basis of disease susceptibility and progression, but this approach still relies on brain tissue to benchmark relevant molecular changes against. Several studies have reported whole-genome expression profiling in post-mortem brain but reported concordance between these analyses is lacking. Here we apply a standardised pathway analysis to seven independent case-control studies, and demonstrate increased concordance between data sets. Moreover data convergence increased when the analysis was limited to the five substantia nigra (SN) data sets; this highlighted the down regulation of dopamine receptor signaling and insulin-like growth factor 1 (IGF1) signaling pathways. We also show that case-control comparisons of affected post mortem brain tissue are more likely to reflect terminal cytoarchitectural differences rather than primary pathogenic mechanisms. The implementation of a correction factor for dopaminergic neuronal loss predictably resulted in the loss of significance of the dopamine signaling pathway while axon guidance pathways increased in significance. Interestingly the IGF1 signaling pathway was also over-represented when data from non-SN areas, unaffected or only terminally affected in PD, were considered. Our findings suggest that there is greater concordance in PD whole-genome expression profiling when standardised pathway membership rather than ranked gene list is used for comparison

    Biomarker candidates of neurodegeneration in Parkinsonā€™s disease for the evaluation of disease-modifying therapeutics

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    Reliable biomarkers that can be used for early diagnosis and tracking disease progression are the cornerstone of the development of disease-modifying treatments for Parkinsonā€™s disease (PD). The German Society of Experimental and Clinical Neurotherapeutics (GESENT) has convened a Working Group to review the current status of proposed biomarkers of neurodegeneration according to the following criteria and to develop a consensus statement on biomarker candidates for evaluation of disease-modifying therapeutics in PD. The criteria proposed are that the biomarker should be linked to fundamental features of PD neuropathology and mechanisms underlying neurodegeneration in PD, should be correlated to disease progression assessed by clinical rating scales, should monitor the actual disease status, should be pre-clinically validated, and confirmed by at least two independent studies conducted by qualified investigators with the results published in peer-reviewed journals. To date, available data have not yet revealed one reliable biomarker to detect early neurodegeneration in PD and to detect and monitor effects of drug candidates on the disease process, but some promising biomarker candidates, such as antibodies against neuromelanin, pathological forms of Ī±-synuclein, DJ-1, and patterns of gene expression, metabolomic and protein profiling exist. Almost all of the biomarker candidates were not investigated in relation to effects of treatment, validated in experimental models of PD and confirmed in independent studies

    Whole genome expression profiling of the medial and lateral substantia nigra in Parkinson's disease.

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    We have used brain tissue from clinically well-documented and neuropathologically confirmed cases of sporadic Parkinson's disease to establish the transcriptomic expression profile of the medial and lateral substantia nigra. In addition, the superior frontal cortex was analyzed in a subset of the same cases. DNA oligonucleotide microarrays were employed, which provide whole human genome coverage. A total of 570 genes were found to be differentially regulated at a high level of significance. A large number of differentially regulated expressed sequence tags were also identified. Levels of mRNA sequences encoded by genes of key interest were validated by means of quantitative real-time polymerase chain reaction (PCR). Comparing three different normalization procedures, results based on the recently published GeneChip Robust Multi Array algorithm were found to be the most accurate predictor of real-time PCR results. Several new candidate genes which map to PARK loci are reported. In addition, the DNAJ family of chaperones is discussed in the context of Parkinson's disease pathogenesis
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