Die allgemeine Rachianästhesie

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A caspase-6-cleaved fragment of Glial Fibrillary Acidic Protein as a potential serological biomarker of CNS injury after cardiac arrest

Blood levels of Glial Fibrillary Acidic protein (GFAP) reflect processes associated with different types of CNS injury. Evidence suggests that GFAP is cleaved by caspases during CNS injury, hence positioning GFAP fragments as potential biomarkers of injury-associated processes. We set out to develop an assay detecting the neo-epitope generated by caspase-6 cleavage of GFAP (GFAP-C6), and to assess the ability of GFAP-C6 to reflect pathological processes in patients suffering a cardiac arrest and subsequent global cerebral ischemia. Anti-GFAP-C6 antibodies recognized their specific target sequence, and dilution and spike recoveries in serum were within limits of ±20% reflecting high precision and accuracy of measurements. Intra- and inter-assay CVs were below limits of 10% and 15%, respectively. Serological levels of GFAP-C6 were significantly elevated 72 hours after CA (Mean±SD) (20.39±10.59 ng/mL) compared to time of admission (17.79±10.77 ng/mL, p<0.0001), 24 hours (17.40±7.99 ng/mL, p<0.0001) and 48 hours (17.87±8.56 ng/mL, p<0.0001) after CA, but were not related to neurological outcome at day 180. GFAP-C6 levels at admission, 24, 48, and 72 hours after cardiac arrest correlated with two proteolytic fragments of tau, tau-A (r = 0.30, r = 0.40, r = 0.50, r = 0.53, p < 0.0001) and tau-C (r = 54, r = 0.48, r = 0.55, r = 0.54, p < 0.0001), respectively. GFAP-C6 levels did not correlate with other markers of CNS damage; total tau, NSE and S100B. In conclusion, we developed the first assay detecting a caspase-6 cleaved fragment of GFAP in blood. Increased levels at 72 hours after cardiac arrest as well as moderate correlations between GFAP-C6 and two other blood biomarkers of neurodegeneration suggest the ability of GFAP-C6 to reflect pathological processes of the injured brain. Investigations into the potential of GFAP-C6 in other types of CNS injury are warranted

The potential of pathological protein fragmentation in blood-based biomarker development for dementia - with emphasis on Alzheimer's disease

The diagnosis of dementia is challenging and early stages are rarely detected limiting the possibilities for early interven-tion. Another challenge is the overlap in the clinical features across the different dementia types leading to difficulties in the differential diagnosis. Identifying biomarkers that can detect the pre-dementia stage and allow differential diagnosis could provide an opportunity for timely and optimal intervention strategies. Also, such biomarkers could help in selection and inclusion of the right patients in clinical trials of both Alzheimer’s disease and other dementia treatment candidates.The cerebrospinal fluid (CSF) has been the most investigated source of biomarkers and several candidate proteins have been identified. However, looking solely at protein levels is too simplistic to provide enough detailed information to differentiate between dementias, as there is a significant crossover between the proteins involved in the different types of dementia. Additionally, CSF sampling makes these biomarkers challenging for presymptomatic identification. We need to focus on disease-specific protein fragmentation to find a fragment pattern unique for each separate dementia type – a form of protein fragmentology. Targeting protein fragments generated by disease-specific combinations of proteins and proteases opposed to detecting the intact protein could reduce the overlap between diagnostic groups as the extent of processing as well as which proteins and proteases constitute the major hallmark of each dementia type differ. In addition, the fragments could be detectable in blood as they may be able to cross the blood-brain-barrier due to their smaller size. In this review, the potential of the fragment-based biomarker discovery for dementia diagnosis and prognosis is discussed, especially highlighting how the knowledge from CSF protein biomarkers can be used to guide blood-based biomarker development