@phdthesis{Stoessel2018,
  author    = {St{\"o}ßel, Daniel},
  title     = {Biomarker Discovery in Multiple Sclerosis and Parkinson's disease},
  school      = {Universit{\"a}t Potsdam},
  pages     = {135},
  year      = {2018},
  abstract  = {Neuroinflammatory and neurodegenerative diseases such as Parkinson's (PD) and multiple sclerosis (MS) often result in a severe impairment of the patient´s quality of life. Effective therapies for the treatment are currently not available, which results in a high socio-economic burden. Due to the heterogeneity of the disease subtypes, stratification is particularly difficult in the early phase of the disease and is mainly based on clinical parameters such as neurophysiological tests and central nervous imaging. Due to good accessibility and stability, blood and cerebrospinal fluid metabolite markers could serve as surrogates for neurodegenerative processes. This can lead to an improved mechanistic understanding of these diseases and further be used as "treatment response" biomarkers in preclinical and clinical development programs. Therefore, plasma and CSF metabolite profiles will be identified that allow differentiation of PD from healthy controls, association of PD with dementia (PDD) and differentiation of PD subtypes such as akinetic rigid and tremor dominant PD patients. In addition, plasma metabolites for the diagnosis of primary progressive MS (PPMS) should be investigated and tested for their specificity to relapsing-remitting MS (RRMS) and their development during PPMS progression. By applying untargeted high-resolution metabolomics of PD patient samples and in using random forest and partial least square machine learning algorithms, this study identified 20 plasma metabolites and 14 CSF metabolite biomarkers. These differentiate against healthy individuals with an AUC of 0.8 and 0.9 in PD, respectively. We also identify ten PDD specific serum metabolites, which differentiate against healthy individuals and PD patients without dementia with an AUC of 1.0, respectively. Furthermore, 23 akinetic-rigid specific plasma markers were identified, which differentiate against tremor-dominant PD patients with an AUC of 0.94 and against healthy individuals with an AUC of 0.98. These findings also suggest more severe disease pathology in the akinetic-rigid PD than in tremor dominant PD. In the analysis of MS patient samples a partial least square analysis yielded predictive models for the classification of PPMS and resulted in 20 PPMS specific metabolites. In another MS study unknown changes in human metabolism were identified after administration of the multiple sclerosis drug dimethylfumarate, which is used for the treatment of RRMS. These results allow to describe and understand the hitherto completely unknown mechanism of action of this new drug and to use these findings for the further development of new drugs and targets against RRMS. In conclusion, these results have the potential for improved diagnosis of these diseases and improvement of mechanistic understandings, as multiple deregulated pathways were identified. Moreover, novel Dimethylfumarate targets can be used to aid drug development and treatment efficiency. Overall, metabolite profiling in combination with machine learning identified as a promising approach for biomarker discovery and mode of action elucidation.},
  language  = {en}
}
@phdthesis{Genderjahn2018,
  author    = {Genderjahn, Steffi},
  title     = {Biosignatures of Present and Past Microbial Life in Southern African Geoarchives},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-410110},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XI, 166, xxii},
  year      = {2018},
  abstract  = {Global climate change is one of the greatest challenges of the 21st century, with influence on the environment, societies, politics and economies. The (semi-)arid areas of Southern Africa already suffer from water scarcity. There is a great variety of ongoing research related to global climate history but important questions on regional differences still exist. In southern African regions terrestrial climate archives are rare, which makes paleoclimate studies challenging. Based on the assumption that continental pans (sabkhas) represent a suitable geo-archive for the climate history, two different pans were studied in the southern and western Kalahari Desert. A combined approach of molecular biological and biogeochemical analyses is utilized to investigate the diversity and abundance of microorganisms and to trace temporal and spatial changes in paleoprecipitation in arid environments. The present PhD thesis demonstrates the applicability of pan sediments as a late Quaternary geo-archive based on microbial signature lipid biomarkers, such as archaeol, branched and isoprenoid glycerol dialkyl glycerol tetraethers (GDGTs) as well as phospholipid fatty acids (PLFA). The microbial signatures contained in the sediment provide information on the current or past microbial community from the Last Glacial Maximum to the recent epoch, the Holocene. The results are discussed in the context of regional climate evolution in southwestern Africa. The seasonal shift of the Innertropical Convergence Zone (ITCZ) along the equator influences the distribution of precipitation- and climate zones. The different expansion of the winter- and summer rainfall zones in southern Africa was confirmed by the frequency of certain microbial biomarkers. A period of increased precipitation in the south-western Kalahari could be described as a result of the extension of the winter rainfall zone during the last glacial maximum (21 ± 2 ka). Instead a period of increased paleoprecipitation in the western Kalahari was indicated during the Late Glacial to Holocene transition. This was possibly caused by a southwestern shift in the position of the summer rainfall zone associated to the southward movement of the ITCZ. Furthermore, for the first time this study characterizes the bacterial and archaeal life based on 16S rRNA gene high-throughput sequencing in continental pan sediments and provides an insight into the recent microbial community structure. Near-surface processes play an important role for the modern microbial ecosystem in the pans. Water availability as well as salinity might determine the abundance and composition of the microbial communities. The microbial community of pan sediments is dominated by halophilic and dry-adapted archaea and bacteria. Frequently occurring microorganisms such as, Halobacteriaceae, Bacillus and Gemmatimonadetes are described in more detail in this study.},
  language  = {en}
}