NEW YORK (360Dx) – A team led by researchers at the University of Tübingen in Germany has identified a metabolite that could be useful for uncovering sample handling errors contributing to preanalytical variability in studies of blood.
In a study published last month in Clinical Chemistry, the researchers used mass spectrometry-based metabolomics to determine that elevated levels of the molecule (4E,14Z)-sphingadienine-C18-1-phosphate (S1P-d18:2) could serve as a marker for detecting samples that were likely not processed or stored within the time ranges recommended by standard operating procedures.
While many of the analytes tested for in existing clinical assays are able to withstand delays in processing and storing, such delays present a potential problem for research into new markers, said Rainer Lehmann, a professor at the University of Tübingen and the senior author on the study.
"Most of the really classical, routine parameters are very stable," he said. "But if samples are collected and stored in a biobank, and you take them out to measure a new parameter that is not so stable in the pre-analytical state, [and you do that] without knowing the quality of the sample collection, then that could really be a problem."
Currently, Lehmann added, there are no widely used methods for testing whether blood samples were processed and stored within acceptable time limits.
"Really, the only way currently is, you provide a standard operating procedure instructing the people how to collect the blood, and then you hope they do it that way," he said. "There's no real way to assess in a quantitative way what has happened to your whole blood sample from when it is taken to the time it is centrifuged and the serum and plasma are separated."
Lehmann and his team hypothesized that changes in metabolite levels in patient blood samples might allow them to identify samples that had not been processed properly. To test this notion, they performed metabolomic profiling of blood from 30 subjects selected from the healthy control arm of a prediabetes study. Upon drawing the blood, it was either immediately processed and then stored at -80°C, cooled to 4°C and kept at that temperature for two or four hours before processing and storage, or left out for two or four hours at room temperature before processing and storage at -80° C.
Of the 1,843 ion masses identified in the discovery stage of the study, 9.2 percent and 16.1 percent exhibited large concentration changes in the samples left out for two and four hours, respectively. In the samples that were immediately cooled to 4°C, 0.5 percent and 1.8 percent of ion masses exhibited large concentration changes in the samples processed at two and four hours, respectively.
From this analysis, they identified 188 metabolites that could potentially identify samples that had experienced delays in processing. Of these, the most promising were S1P-d18:2 and lactate. Further investigations into lactate found, however, that it was not suitable as a marker, as it was significantly increased in some samples from patients with sepsis and who had undergone cardiopulmonary resuscitation, as well as in some subjects who had undertaken strenuous exercise as part of a circuit training study. On the other hand, S1P-d18:2 remained stable under these conditions, indicating it could potentially serve as a biomarker for blood quality control even in samples taken from patients experiencing extreme physiological conditions.
Lehmann and his colleagues ran a series of validation studies to further establish whether S1P-d18:2 could effectively identify improperly collected samples. In an experiment looking at 79 samples, S1P-d18:2 levels distinguished between those left at room temperature for four hours and those immediately cooled to 4°C and then processed at four hours, with an area under the curve of 0.99.
In a study looking at the effect of long-term storage on S1P-d18:2 levels, the researchers found no difference in concentrations of the metabolite in 100 plasma samples stored for six months and 50 samples stored for five years at the same biobank.
They also looked at S1P-d18:2 concentrations in more than 800 serum samples collected during a multicenter research trial studying liver diseases. These samples were all processed according to the same protocol, except for a set stored at one particular biobank, which used a similar but slightly different protocol. The S1P-d18:2 concentrations were consistent across these samples, as would be expected based on the protocols used. Additionally, the researchers noted, the fact that none of the liver diseases produced changes in S1P-d18:2 levels provided further confirmation of the marker's robustness.
Lehmann said he and his colleagues would like to commercialize the marker for assessing adherence to sample collection protocols but have no concrete plans at the moment. He added that he would be interested in partnering with or licensing the marker to an outside firm.
Both the discovery and validation phases of the work were done using mass spec, and Lehmann said that while it might be possible to develop an immunoassay to the marker, he hoped that forthcoming clinical mass spec platforms like Thermo Fisher Scientific's Cascadion system would allow clinicians and clinical researchers to test routinely for S1P-d18:2 using mass spec.
In addition to time-to-processing, Lehmann's lab is also exploring biomarkers for detecting hemolyzed blood samples, which he said is another major issue affecting clinical samples.
"We have numbers that suggest that around 3 percent of all samples coming into the [clinical] laboratory are hemolyzed," he said. "So it would be nice if it was possible in one [mass spec] run to control both for hemolysis and exposure to room temperature, which I think are the two major issue that affect the sample quality in the clinic."