TY - JOUR A1 - Durrenberger, Pascal F. A1 - Grünblatt, Edna A1 - Fernando, Francesca S. A1 - Monoranu, Camelia Maria A1 - Evans, Jordan A1 - Riederer, Peter A1 - Reynolds, Richard A1 - Dexter, David T. T1 - Inflammatory Pathways in Parkinson’s Disease; A BNE Microarray Study JF - Parkinson's Disease N2 - The aetiology of Parkinson's disease (PD) is yet to be fully understood but it is becoming more and more evident that neuronal cell death may be multifactorial in essence. The main focus of PD research is to better understand substantia nigra homeostasis disruption, particularly in relation to the wide-spread deposition of the aberrant protein α-synuclein. Microarray technology contributed towards PD research with several studies to date and one gene, ALDH1A1 (Aldehyde dehydrogenase 1 family, member A1), consistently reappeared across studies including the present study, highlighting dopamine (DA) metabolism dysfunction resulting in oxidative stress and most probably leading to neuronal cell death. Neuronal cell death leads to increased inflammation through the activation of astrocytes and microglia. Using our dataset, we aimed to isolate some of these pathways so to offer potential novel neuroprotective therapeutic avenues. To that effect our study has focused on the upregulation of P2X7 (purinergic receptor P2X, ligand-gated ion channel, 7) receptor pathway (microglial activation) and on the NOS3 (nitric oxide synthase 3) pathway (angiogenesis). In summary, although the exact initiator of striatal DA neuronal cell death remains to be determined, based on our analysis, this event does not remain without consequence. Extracellular ATP and reactive astrocytes appear to be responsible for the activation of microglia which in turn release proinflammatory cytokines contributing further to the parkinsonian condition. In addition to tackling oxidative stress pathways we also suggest to reduce microglial and endothelial activation to support neuronal outgrowth. Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-124380 VL - 2012 IS - 214714 ER - TY - JOUR A1 - Gerlach, Manfred A1 - Maetzler, Walter A1 - Broich, Karl A1 - Hampel, Harald A1 - Rems, Lucas A1 - Reum, Torsten A1 - Riederer, Peter A1 - Stäffler, Albrecht A1 - Streffer, Johannes A1 - Berg, Daniela T1 - Biomarker candidates of neurodegeneration in Parkinson's disease for the evaluation of disease-modifying therapeutics JF - Journal of Neural Transmission N2 - Reliable biomarkers that can be used for early diagnosis and tracking disease progression are the cornerstone of the development of disease-modifying treatments for Parkinson’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 α-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. KW - disease progression KW - biomarkers KW - neuroprotection KW - disease-modifying therapies KW - Parkinson’s disease KW - surrogate endpoints KW - drug development Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-125375 VL - 119 IS - 1 ER - TY - JOUR A1 - Molochnikov, Leonid A1 - Rabey, Jose M. A1 - Dobronevsky, Evgenya A1 - Bonuccelli, Ubaldo A1 - Ceravolo, Roberto A1 - Frosini, Daniela A1 - Grünblatt, Edna A1 - Riederer, Peter A1 - Jacob, Christian A1 - Aharon-Peretz, Judith A1 - Bashenko, Yulia A1 - Youdim, Moussa B. H. A1 - Mandel, Silvia A. T1 - A molecular signature in blood identifies early Parkinson's disease JF - Molecular Neurodegeneration N2 - Background: The search for biomarkers in Parkinson's disease (PD) is crucial to identify the disease early and monitor the effectiveness of neuroprotective therapies. We aim to assess whether a gene signature could be detected in blood from early/mild PD patients that could support the diagnosis of early PD, focusing on genes found particularly altered in the substantia nigra of sporadic PD. Results: The transcriptional expression of seven selected genes was examined in blood samples from 62 early stage PD patients and 64 healthy age-matched controls. Stepwise multivariate logistic regression analysis identified five genes as optimal predictors of PD: p19 S-phase kinase-associated protein 1A (odds ratio [OR] 0.73; 95% confidence interval [CI] 0.60-0.90), huntingtin interacting protein-2 (OR 1.32; CI 1.08-1.61), aldehyde dehydrogenase family 1 subfamily A1 (OR 0.86; 95% CI 0.75-0.99), 19 S proteasomal protein PSMC4 (OR 0.73; 95% CI 0.60-0.89) and heat shock 70-kDa protein 8 (OR 1.39; 95% CI 1.14-1.70). At a 0.5 cut-off the gene panel yielded a sensitivity and specificity in detecting PD of 90.3 and 89.1 respectively and the area under the receiving operating curve (ROC AUC) was 0.96. The performance of the five-gene classifier on the de novo PD individuals alone composing the early PD cohort (n = 38), resulted in a similar ROC with an AUC of 0.95, indicating the stability of the model and also, that patient medication had no significant effect on the predictive probability (PP) of the classifier for PD risk. The predictive ability of the model was validated in an independent cohort of 30 patients at advanced stage of PD, classifying correctly all cases as PD (100% sensitivity). Notably, the nominal average value of the PP for PD (0.95 (SD = 0.09)) in this cohort was higher than that of the early PD group (0.83 (SD = 0.22)), suggesting a potential for the model to assess disease severity. Lastly, the gene panel fully discriminated between PD and Alzheimer's disease (n = 29). Conclusions: The findings provide evidence on the ability of a five-gene panel to diagnose early/mild PD, with a possible diagnostic value for detection of asymptomatic PD before overt expression of the disorder. KW - cerebrospina KW - magnetic-resonance-spectroscopy KW - protein KW - biomarkers KW - E3 ubiquitin ligase KW - SCF KW - SKP1 KW - heat shock protein Hsc-70 KW - early diagnosis KW - fluid KW - alpha-synuclein KW - dehydrogenases KW - Alzheimer's disease KW - sporadic Parkinson's disease KW - blood biomarker KW - CSF KW - multiple system atrophy KW - clinical diagnosis KW - substantia nigra KW - gene expression Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-134508 VL - 7 IS - 26 ER -