Refine
Has Fulltext
- no (3) (remove)
Year of publication
- 2018 (3) (remove)
Document Type
- Article (1)
- Doctoral Thesis (1)
- Review (1)
Language
- English (3)
Is part of the Bibliography
- yes (3) (remove)
Keywords
- Biomarker (3) (remove)
Institute
Nowadays, the role of trace elements (TE) is of growing interest because dyshomeostasis of selenium (Se), manganese (Mn), zinc (Zn), and copper (Cu) is supposed to be a risk factor for several diseases. Thereby, research focuses on identifying new biomarkers for the TE status to allow for a more reliable description of the individual TE and health status. This review mirrors a lack of well-defined, sensitive, and selective biomarkers and summarizes technical limitations to measure them. Thus, the capacity to assess the relationship between dietary TE intake, homeostasis, and health is restricted, which would otherwise provide the basis to define adequate intake levels of single TE in both healthy and diseased humans. Besides that, our knowledge is even more limited with respect to the real life situation of combined TE intake and putative interactions between single TE.
Objective: Fibroblast growth factor (FGF)21 is promptly induced by short fasting in animal models to regulate glucose and fat metabolism. Data on FGF21 in humans are inconsistent and FGF21 has not yet been investigated in old patients with cachexia, a complex syndrome characterized by inflammation and weight loss. The aim of this study was to explore the association of FGF21 with cachexia in old patients compared with their healthy counterparts. Methods: Serum FGF21 and its inactivating enzyme fibroblast activation protein (FAP)-cc were measured with enzyme-linked immunoassays. Cachexia was defined as >= 5% weight loss in the previous 3 mo and concurrent anorexia (Council on Nutrition appetite questionnaire). Results: We included 103 patients with and without cachexia (76.9 +/- 5.2 y of age) and 56 healthy controls (72.9 +/- 5.9 y of age). Cachexia was present in 16.5% of patients. These patients had significantly higher total FGF21 levels than controls (952.1 +/- 821.3 versus 525.2 +/- 560.3 pg/mL; P= 0.012) and the lowest FGF21 levels (293.3 +/- 150.9 pg/mL) were found in the control group (global P < 0.001). Although FAP-alpha did not differ between the three groups (global P = 0.082), bioactive FGF21 was significantly higher in patients with cachexia (global P = 0.002). Risk factor-adjusted regression analyses revealed a significant association between cachexia and total ((beta = 649.745 pg/mL; P < 0.001) and bioactive FGF21 (beta = 393.200 pg/mL; P <0.001), independent of sex, age, and body mass index. Conclusions: Patients with cachexia exhibited the highest FGF21 levels. Clarification is needed to determine whether this is an adaptive response to nutrient deprivation in disease-related cachexia or whether the increased FGF21 values contribute to the catabolic state. (C) 2018 Elsevier Inc. All rights reserved.
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.