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Parkinson's disease (PD) shows high heterogeneity with regard to the underlying molecular pathogenesis involving multiple pathways and mechanisms. Diagnosis is still challenging and rests entirely on clinical features. Thus, there is an urgent need for robust diagnostic biofluid markers. Untargeted metabolomics allows establishing low-molecular compound biomarkers in a wide range of complex diseases by the measurement of various molecular classes in biofluids such as blood plasma, serum, and cerebrospinal fluid (CSF). Here, we applied untargeted high-resolution mass spectrometry to determine plasma and CSF metabolite profiles. We semiquantitatively determined small-molecule levels (<= 1.5 kDa) in the plasma and CSF from early PD patients (disease duration 0-4 years; n = 80 and 40, respectively), and sex-and age-matched controls (n = 76 and 38, respectively). We performed statistical analyses utilizing partial least square and random forest analysis with a 70/30 training and testing split approach, leading to the identification of 20 promising plasma and 14 CSF metabolites. The semetabolites differentiated the test set with an AUC of 0.8 (plasma) and 0.9 (CSF). Characteristics of the metabolites indicate perturbations in the glycerophospholipid, sphingolipid, and amino acid metabolism in PD, which underscores the high power of metabolomic approaches. Further studies will enable to develop a potential metabolite-based biomarker panel specific for PD
Primary progressive multiple sclerosis (PPMS) shows a highly variable disease progression with poor prognosis and a characteristic accumulation of disabilities in patients. These hallmarks of PPMS make it difficult to diagnose and currently impossible to efficiently treat. This study aimed to identify plasma metabolite profiles that allow diagnosis of PPMS and its differentiation from the relapsing remitting subtype (RRMS), primary neurodegenerative disease (Parkinson’s disease, PD), and healthy controls (HCs) and that significantly change during the disease course and could serve as surrogate markers of multiple sclerosis (MS)-associated neurodegeneration over time. We applied untargeted high-resolution metabolomics to plasma samples to identify PPMS-specific signatures, validated our findings in independent sex- and age-matched PPMS and HC cohorts and built discriminatory models by partial least square discriminant analysis (PLS-DA). This signature was compared to sex- and age-matched RRMS patients, to patients with PD and HC. Finally, we investigated these metabolites in a longitudinal cohort of PPMS patients over a 24-month period. PLS-DA yielded predictive models for classification along with a set of 20 PPMS-specific informative metabolite markers. These metabolites suggest disease-specific alterations in glycerophospholipid and linoleic acid pathways. Notably, the glycerophospholipid LysoPC(20:0) significantly decreased during the observation period. These findings show potential for diagnosis and disease course monitoring, and might serve as biomarkers to assess treatment efficacy in future clinical trials for neuroprotective MS therapies.
Femtosecond-Pulsed laser written and etched fiber bragg gratings for fiber-optical biosensing
(2018)
We present the development of a label-free, highly sensitive fiber-optical biosensor for online detection and quantification of biomolecules. Here, the advantages of etched fiber Bragg gratings (eFBG) were used, since they induce a narrowband Bragg wavelength peak in the reflection operation mode. The gratings were fabricated point-by-point via a nonlinear absorption process of a highly focused femtosecond-pulsed laser, without the need of prior coating removal or specific fiber doping. The sensitivity of the Bragg wavelength peak to the surrounding refractive index (SRI), as needed for biochemical sensing, was realized by fiber cladding removal using hydrofluoric acid etching. For evaluation of biosensing capabilities, eFBG fibers were biofunctionalized with a single-stranded DNA aptamer specific for binding the C-reactive protein (CRP). Thus, the CRP-sensitive eFBG fiber-optical biosensor showed a very low limit of detection of 0.82 pg/L, with a dynamic range of CRP detection from approximately 0.8 pg/L to 1.2 mu g/L. The biosensor showed a high specificity to CRP even in the presence of interfering substances. These results suggest that the proposed biosensor is capable for quantification of CRP from trace amounts of clinical samples. In addition, the adaption of this eFBG fiber-optical biosensor for detection of other relevant analytes can be easily realized.