@article{SianHulsmannRiederer2021,
  author    = {Sian-Hulsmann, Jeswinder and Riederer, Peter},
  title     = {The nigral coup in Parkinson's Disease by α-synuclein and its associated rebels},
  series = {Cells},
  volume    = {10},
  journal   = {Cells},
  number    = {3},
  issn      = {2073-4409},
  doi       = {10.3390/cells10030598},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-234073},
  year      = {2021},
  abstract  = {The risk of Parkinson's disease increases with age. However, the etiology of the illness remains obscure. It appears highly likely that the neurodegenerative processes involve an array of elements that influence each other. In addition, genetic, endogenous, or exogenous toxins need to be considered as viable partners to the cellular degeneration. There is compelling evidence that indicate the key involvement of modified α-synuclein (Lewy bodies) at the very core of the pathogenesis of the disease. The accumulation of misfolded α-synuclein may be a consequence of some genetic defect or/and a failure of the protein clearance system. Importantly, α-synuclein pathology appears to be a common denominator for many cellular deleterious events such as oxidative stress, mitochondrial dysfunction, dopamine synaptic dysregulation, iron dyshomeostasis, and neuroinflammation. These factors probably employ a common apoptotic/or autophagic route in the final stages to execute cell death. The misfolded α-synuclein inclusions skillfully trigger or navigate these processes and thus amplify the dopamine neuron fatalities. Although the process of neuroinflammation may represent a secondary event, nevertheless, it executes a fundamental role in neurodegeneration. Some viral infections produce parkinsonism and exhibit similar characteristic neuropathological changes such as a modest brain dopamine deficit and α-synuclein pathology. Thus, viral infections may heighten the risk of developing PD. Alternatively, α-synuclein pathology may induce a dysfunctional immune system. Thus, sporadic Parkinson's disease is caused by multifactorial trigger factors and metabolic disturbances, which need to be considered for the development of potential drugs in the disorder.},
  language  = {en}
}
@article{PlumSteinbachAttemsetal.2016,
  author    = {Plum, Sarah and Steinbach, Simone and Attems, Johannes and Keers, Sharon and Riederer, Peter and Gerlach, Manfred and May, Caroline and Marcus, Katrin},
  title     = {Proteomic characterization of neuromelanin granules isolated from human substantia nigra by laser-microdissection},
  series = {Scientific Reports},
  volume    = {6},
  journal   = {Scientific Reports},
  number    = {37139},
  doi       = {10.1038/srep37139},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-167507},
  year      = {2016},
  abstract  = {Neuromelanin is a complex polymer pigment found primarily in the dopaminergic neurons of human substantia nigra. Neuromelanin pigment is stored in granules including a protein matrix and lipid droplets. Neuromelanin granules are yet only partially characterised regarding their structure and function. To clarify the exact function of neuromelanin granules in humans, their enrichment and in-depth characterization from human substantia nigra is necessary. Previously published global proteome studies of neuromelanin granules in human substantia nigra required high tissue amounts. Due to the limited availability of human brain tissue we established a new method based on laser microdissection combined with mass spectrometry for the isolation and analysis of neuromelanin granules. With this method it is possible for the first time to isolate a sufficient amount of neuromelanin granules for global proteomics analysis from ten 10 μm tissue sections. In total 1,000 proteins were identified associated with neuromelanin granules. More than 68\% of those proteins were also identified in previously performed studies. Our results confirm and further extend previously described findings, supporting the connection of neuromelanin granules to iron homeostasis and lysosomes or endosomes. Hence, this method is suitable for the donor specific enrichment and proteomic analysis of neuromelanin granules.},
  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}
}