A standardised methodology for the extraction and quantification of cell-free DNA in cerebrospinal fluid and application to evaluation of Alzheimer's disease and brain cancers.
N Biotechnol. 2022 Oct 3:S1871-6784(22)00055-3. doi: 10.1016/j.nbt.2022.10.001. Epub ahead of print. PMID: 36202346.
|Authors/Editors:||Takousis P, Devonshire AS, Redshaw N, von Baumgarten L, Whale AS, Jones GM, Fernandez-Gonzalez A, Martin J, Foy CA, Alexopoulos P, Huggett JF, Perneczky R.|
Cerebrospinal fluid (CSF) is a source of diagnostic biomarkers for a range of neurological conditions. Cell-free DNA (cfDNA) is detected in CSF and differences in the concentration of cell-free mitochondrial DNA have been reported in studies of neurodegenerative disorders including Alzheimer’s disease (AD). However, the influence of pre-analytical steps has not been investigated for cfDNA in CSF and there is no standardised approach for quantification of total cfDNA (copies of nuclear genome or mitochondria-derived gene targets). In this study, the suitability of four extraction methods was evaluated: QIAamp Circulating Nucleic Acid (Qiagen), Quick-cfDNA Serum & Plasma (Zymo), NucleoSnap® DNA Plasma (Macherey-Nagel) and Plasma/Serum Circulating DNA Purification Mini (Norgen) kits, for cfDNA extraction from CSF of controls and AD dementia patients, utilising a spike-in control for extraction efficiency and fragment size. One of the optimal extraction methods was applied to a comparison of cfDNA concentrations in CSF from control subjects, AD dementia and primary and secondary brain tumour patients. Extraction efficiency based on spike-in recovery was similar in all three groups whilst both endogenous mitochondrial and nucleus-derived cfDNA was significantly higher in CSF from cancer patients compared to control and AD groups, which typically contained < 100 genome copies/mL. This study shows that it is feasible to measure low concentration nuclear and mitochondrial gene targets in CSF and that normalisation of extraction yield can help control pre-analytical variability influencing biomarker measurements.