Biology subjects

Goeschel, L.

Publications and source records attributed to Goeschel, L..

2 recordsLinked to original sources

bioRxiv2024

A candidate reference method for the quantification of α-synuclein in cerebrospinal fluid using an SI traceable primary calibrator and multiple reaction monitoring

Objectives-synuclein aggregation is an indicator of neurodegenerative diseases such as Parkinsons disease (PD) and recent advances have suggested that this protein could serve as a potential biomarker. It has been indicated that soluble and oligomeric -synuclein in biological fluids could have diagnostic applications for PD. Clinical laboratories currently rely on antibody-based assays to detect -synuclein. These assays have limited specificity, low sensitivity and poor inter-lab reproducibility, which prevents the validation of -synuclein as a biomarkers. This study aims to fill the unmet need for the standardisation of clinical measurements for -synuclein. MethodsWe report the first candidate reference method for -synuclein, using an SI traceable primary calibrator for -synuclein and isotope dilution mass spectrometry. The primary calibrator was traceably quantified utilising a combination of amino acid analysis and nuclear magnetic resonance. A targeted sample clean-up procedure involving a non-denaturing Lys-C digestion and solid-phase extraction allowed for the sensitive detection of multiple proteotypic -synuclein peptides in cerebrospinal fluid (CSF) samples. ResultsThe candidate reference method procedure showed linearity across three orders of magnitude, covering the physiological levels of -synuclein in CSF (LOQ = 0.1 ng/g). The method was used to quantify a cohort of CSF samples and the measurements were correlated with immunoassay-based quantifications. ConclusionsThe SI traceable quantification of -synuclein in complex biological matrices means that the role of this protein can be further elucidated in synucleinopathies. This candidate reference method would lead to the harmonisation of -synuclein measurements, which may allow for development of high throughput clinical tests.

biochemistry↗

bioRxiv2023

Macromolecule modelling for improved metabolite quantification using short echo time brain 1H-MRS at 3 T and 7 T: The PRaMM Model

PurposeTo improve reliability of metabolite quantification at both, 3 T and 7 T, we propose a novel parametrized macromolecules quantification model (PRaMM) for brain 1H MRS, in which the ratios of macromolecule peak intensities are used as soft constraints. MethodsFull- and metabolite-nulled spectra were acquired in three different brain regions with different ratios of grey and white matter from six healthy volunteers, at both 3 T and 7 T. Metabolite-nulled spectra were used to identify highly correlated macromolecular signal contributions and estimate the ratios of their intensities. These ratios were then used as soft constraints in the proposed PRaMM model for quantification of full spectra. The PRaMM model was validated by comparison with a single component macromolecule model and a macromolecule subtraction technique. Moreover, the influence of the PRaMM model on the repeatability and reproducibility compared to those other methods was investigated. ResultsThe developed PRaMM model performed better than the two other approaches in all three investigated brain regions. Several estimates of metabolite concentration and their Cramer-Rao lower bounds were affected by the PRaMM model reproducibility, and repeatability of the achieved concentrations were tested by evaluating the method on a second repeated acquisitions dataset. While the observed effects on both metrics were not significant, the fit quality metrics were improved for the PRaMM method (p[≤]0.0001). Minimally detectable changes are in the range 0.5 - 1.9 mM and percent coefficients of variations are lower than 10% for almost all the clinically relevant metabolites. Furthermore, potential overparameterization was ruled out. ConclusionHere, the PRaMM model, a method for an improved quantification of metabolites was developed, and a method to investigate the role of the MM background and its individual components from a clinical perspective is proposed.

neuroscience↗