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Endocannabinoids (ECs) are potent lipid mediators with high physiological relevance. They are involved in a wide variety of diseases like depression or multiple sclerosis and are closely connected to metabolic parameters in humans. Therefore, their suitability as a biomarker in different (patho-)physiological conditions is discussed intensively and predominantly investigated by analyzing systemic concentrations in easily accessible matrices like blood. Carefully designed pre-analytical sample handling is of major importance for high-quality data, but harmonization is not achieved yet. Whole blood is either processed to serum or plasma before the onset of analytical workflows and while knowledge about pre-analytical challenges in plasma handling is thorough they were not systematically investigated for serum.
Therefore, the ECs AEA and 2-AG, and closely related EC-like substances 1-AG, DHEA, and PEA were examined by LC-MS/MS in serum samples of nine healthy volunteers employing different pre-analytical sample handling protocols, including prolonged coagulation, and storage after centrifugation at room temperature (RT) or on ice. Furthermore, all analytes were also assessed in plasma samples obtained from the same individuals at the same time points to investigate the comparability between those two blood-based matrices regarding obtained concentrations and their 2-AG/1-AG ratio.
This study shows that ECs and EC-like substances in serum samples were significantly higher than in plasma and are especially prone to ex vivo changes during initial and prolonged storage for coagulation at RT. Storage on ice after centrifugation is less critical. However, storage at RT further increases 1-AG and 2-AG concentrations, while also lowering the already reduced 2-AG/1-AG ratio due to isomerization. Thus, avoidance of prolonged processing at RT can increase data quality if serum as the matrix of choice is unavoidable. However, serum preparation in itself is expected to initiate changes of physiological concentrations as standard precautionary measures like fast and cooled processing can only be utilized by using plasma, which should be the preferred matrix for analyses of ECs and EC-like substances.
Myotonic dystrophy type 1 (DM1) lacks non-invasive and easy to measure biomarkers, still largely relying on semi-quantitative tests for diagnostic and prognostic purposes. Muscle biopsies provide valuable data, but their use is limited by their invasiveness. microRNA (miRNAs) are small non-coding RNAs regulating gene expression that are also present in biological fluids and may serve as diseases biomarkers. Thus, we tested plasma miRNAs in the blood of 36 DM1 patients and 36 controls. First, a wide miRNA panel was profiled in a patient subset, followed by validation using all recruited subjects. We identified a signature of nine deregulated miRNAs in DM1 patients: eight miRNAs were increased (miR-133a, miR-193b, miR-191, miR-140-3p, miR-454, miR-574, miR-885-5p, miR-886-3p) and one (miR-27b) was decreased. Next, the levels of these miRNAs were used to calculate a "DM1-miRNAs score". We found that both miR-133a levels and DM1-miRNAs score discriminated DM1 from controls significantly and Receiver-Operator Characteristic curves displayed an area under the curve of 0.94 and 0.97, respectively. Interestingly, both miR-133a levels and DM1-miRNAs score displayed an inverse correlation with skeletal muscle strength and displayed higher values in more compromised patients. In conclusion, we identified a characteristic plasma miRNA signature of DM1. Although preliminary, this study indicates miRNAs as potential DM1 humoral biomarkers.