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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.
The transfer of particulate organic carbon from continents to the ocean is an important component of the global carbon cycle. Transfer to and burial of photosynthetically fixed biospheric organic carbon in marine sediments can effectively sequester atmospheric carbon dioxide over geological timescales. The exhumation and erosion of fossil organic carbon contained in sedimentary rocks, i.e. petrogenic carbon, can result in remineralization, releasing carbon to the atmosphere. In contrast, eroded petrogenic organic carbon that gets transferred back to the ocean and reburied does not affect atmospheric carbon content.
Mountain ranges play a key role in this transfer since they can source vast amounts of sediment including particulate organic carbon. Globally, the export of both, biospheric and petrogenic organic carbon has been linked to sediment export. Additionally, short transfer times from mountains to the ocean and high sediment concentrations have been shown to increase the likelihood of organic carbon burial. While the importance of mountain ranges in the organic carbon cycle is now widely recognized, the processes acting within mountain ranges to influence the storage, cycling and mobilization of organic carbon, as well as carbon fluxes from mountain ranges remain poorly constrained.
In this thesis, I employ different methods to assess the nature and fate of particulate organic carbon in mountain belts, ranging from the molecular to regional landscape scale. These studies are located along the Trans-Himalayan Kali Gandaki River in Central Nepal. This river traverses all major geological and climatic zones of the Himalaya, from the dry northern Tibetan plateau to the high-relief, monsoon dominated steep High Himalaya and the lower relief and abundant vegetation of the Lesser Himalayan region.
First, I document how biospheric organic matter has accumulated during the Holocene in the headwaters of the Kali Gandaki River valley, by combining compound specific isotope measurements with different dating methods and grain size data, and investigate the stability of this organic carbon reservoir on millennial timescales. I show, that around 1.6 ka an eco-geomorphic tipping point occurred leading to a destabilization of the landscape resulting in today’s high erosion rates and the excavation of the aged organic carbon reservoir. This study highlights the climatic and geomorphic controls on biospheric organic carbon storage and release from mountain ranges.
Second, I systematically investigate the spatial variation of particulate organic carbon fluxes across the Himalaya along the Kali Gandaki River, using bulk stable and radioactive isotopes combined with a new Bayesian modeling approach. The detailed dataset allows the distinction of aged and modern biospheric organic carbon as well as petrogenic organic carbon across the Himalayan mountain range and the investigation of the role of climatic and geomorphic factors in their riverine export. The data suggest a decoupling of the particulate organic carbon from the sediment yield along the Kali Gandaki River, partially driven by climatic and geomorphic processes. In contrast to the suspended sediment, a large part of the particulate organic carbon exported by the river originates from the Tibetan part of the catchment and is dominated by petrogenic organic carbon derived from Jurassic shales with only minor contributions of modern and aged biospheric organic carbon. These findings emphasize the importance of organic carbon source distribution and erosion mechanisms in determining the organic carbon export from mountain ranges.
In a third step, I explore the potential of ultra-high resolution mass spectrometry for particulate organic carbon transport studies. I have generated a novel and unprecedented high-resolution molecular dataset, which contains up to 103 molecular formulas of the lipid fraction of particulate organic matter for modern and aged biospheric carbon, petrogenic organic carbon and river sediments. First, I test if this dataset can be used to better resolve different organic carbon sources and to identify new geochemical tracers. Using multivariate statistics, I identify up to 10² characteristic molecular formulas for the major organic carbon sources in the upper part of the Kali Gandaki catchment, and trace their transfer from the surrounding landscape into the river sediment. Second, I test the potential of the molecular dataset to trace molecular transformations along source-to-sink pathways. I identify changes in molecular metrics derived from the dataset, which are characteristic of transformation processes during incorporation of litter into soil, the aging of soil material, and the mobilization of the organic carbon into the river. These two studies demonstrate that high-resolution molecular datasets open a promising analytical window on particulate organic carbon and can provide novel insights into the composition, sourcing and transformation of riverine particulate organic carbon.
Collectively, these studies advance our understanding of the processes contributing to the storage and mobilization of organic carbon in the Central Himalaya, the mountain belt that dominates global erosional fluxes. They do so by identifying the major sources of particulate organic carbon to the Trans-Himalayan Kali Gandaki River, by elucidating their sensitivity to climate and geomorphic processes, and by identifying some of the transformations of this material on the molecular scale. As a result, the thesis demonstrates that the amount and composition of organic carbon routed from mountain belts is a function of the dynamic interactions of geologic, biologic, geomorphic and climatic processes within the mountain belt. This understanding will ultimately help in answering whether the build-up and erosion of mountain ranges over geological time represents a net carbon source or sink to the atmosphere. Beyond this, the thesis contributes to our technical ability to characterize organic matter and attribute it to sources by scoping the potential of high-end molecular analysis.