@article{DurrenbergerGruenblattFernandoetal.2012, author = {Durrenberger, Pascal F. and Gr{\"u}nblatt, Edna and Fernando, Francesca S. and Monoranu, Camelia Maria and Evans, Jordan and Riederer, Peter and Reynolds, Richard and Dexter, David T.}, title = {Inflammatory Pathways in Parkinson's Disease; A BNE Microarray Study}, series = {Parkinson's Disease}, volume = {2012}, journal = {Parkinson's Disease}, number = {214714}, doi = {10.1155/2012/214714}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-124380}, year = {2012}, abstract = {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.}, language = {en} } @article{GerlachMaetzlerBroichetal.2012, author = {Gerlach, Manfred and Maetzler, Walter and Broich, Karl and Hampel, Harald and Rems, Lucas and Reum, Torsten and Riederer, Peter and St{\"a}ffler, Albrecht and Streffer, Johannes and Berg, Daniela}, title = {Biomarker candidates of neurodegeneration in Parkinson's disease for the evaluation of disease-modifying therapeutics}, series = {Journal of Neural Transmission}, volume = {119}, journal = {Journal of Neural Transmission}, number = {1}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-125375}, pages = {39-52}, year = {2012}, abstract = {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.}, language = {en} } @article{MolochnikovRabeyDobronevskyetal.2012, author = {Molochnikov, Leonid and Rabey, Jose M. and Dobronevsky, Evgenya and Bonuccelli, Ubaldo and Ceravolo, Roberto and Frosini, Daniela and Gr{\"u}nblatt, Edna and Riederer, Peter and Jacob, Christian and Aharon-Peretz, Judith and Bashenko, Yulia and Youdim, Moussa B. H. and Mandel, Silvia A.}, title = {A molecular signature in blood identifies early Parkinson's disease}, series = {Molecular Neurodegeneration}, volume = {7}, journal = {Molecular Neurodegeneration}, number = {26}, doi = {10.1186/1750-1326-7-26}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-134508}, year = {2012}, abstract = {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.}, language = {en} }