Biobanking Cerebrospinal Fluid: Biomarkers of Neurological Disease

Cerebrospinal fluid (CSF) is a valuable source for biomarker discovery because its composition changes to reflect the pathophysiology of diseases. This is because of the proximity of CSF to the brain and its interactions, or communication, with the brain. CSF contains brain-specific proteins and metabolites reflective of normal and pathological processes within the brain. Therefore, the quality of a study is directly impacted by quality control in biobanking. Willemse and Teunissen recently reviewed current biobanking of CSF.¹

CSF biobanking is unique in that there are fewer CSF samples of healthy controls than in other tissues. This is because ethics committees have raised concerns about performing lumbar punctures on healthy volunteers. Furthermore, CSF has a different cellular and biochemical composition than blood, leading to different protein stability, which results in greater variation. The most pertinent factors to control for in CSF biobanking are those related to the patient and to processing.

Patient-related factors affecting quality of banked CSF include patient misidentification, which the authors suggest can be improved by linking electronic patient records to biobank databases. Additionally, 2-D bar coding will allow for samples to be retrieved automatically, further reducing user error. Furthermore, Willemse and Teunissen raise concerns that factors such as fasting, smoking, alcohol use, caffeine intake and exercise may cause fluctuations in CSF molecules, and that therefore these should be documented at collection. They also suggest that diurnal fluctuations may produce relevant changes, and that therefore the time a CSF sample was collected should similarly be recorded.

The authors further define a set of guidelines for CSF processing and biobanking to reduce pre-analytical error. They include:

CSF volume can affect biomarker concentration because there is a concentration gradient of cells and molecules between the ventricular and lumbar CSF. Therefore, they recommend researchers collect standard volumes of CSF for biobanking or, at a minimum, record the total volume.
Puncture location should be recorded because some peptides are present in different concentrations, depending on location.
If a CSF sample has been contaminated with blood during collection, researchers should perform an erythrocyte count. Counts up to 500/μL may be used for biomarker studies.
Although needle gauge does not affect biomarker concentrations, smaller gauge needles carry a lower risk of post–lumbar puncture headaches.
Some proteins can adhere to plastic materials used in the lab. Polypropylene collection tubes and harmonization of tubes between samples may prevent aberration of biomarker concentration. As a further safeguard, the authors recommend transferring CSF between tubes as little as possible because this also decreases the protein concentration of a sample. Similarly, they apply this principle to the tubes used for aliquoting.
The concentration of a biomarker in blood can influence its concentration in CSF, and therefore researchers should collect matched serum samples.
Serum and plasma can be processed at room temperature for most studies. However, if a researcher’s intent is to sample RNA from CSF immune cells, samples should be spun immediately or stored at 4°C until processing.
Standard spinning conditions are 400 g for 10 minutes at room temperature for CSF if the intention is to collect cells, otherwise between 1,800 g and 2,200 g for 10 minutes at room temperature.
The authors suggest standardizing the time delay between withdrawal, spinning and freezing.
Split samples into small aliquots to avoid freeze-thaw cycles and freeze at −80°C.

As collaboration and the number of multi-center trials increase, Willemse and Teunissen note that standardization of CSF biobanking will allow researchers to perform high-quality biomarker studies.

References

1. Willemse, E. A. J. and Teunissen, C. E. (2015) “Biobanking of cerebrospinal fluid for biomarker analysis in neurological diseases,” Advances in Experimental Medicine and Biology, 864, (pp. 79-93).