Considerations for powering a clinical proteomics study: Normal variability in the human plasma proteome.

Proteomics is increasingly being applied to the human plasma proteome to identify biomarkers of disease for use in non-invasive assays. 2-D DIGE, simultaneously analysing thousands of protein spots quantitatively and maintaining protein isoform information, is one technique adopted. Sufficient numbers of samples must be analysed to achieve statistical power; however, few reported studies have analysed inherent variability in the plasma proteome by 2-D DIGE to allow power calculations. This study analysed plasma from 60 healthy volunteers by 2-D DIGE. Two samples were taken, 7 days apart, allowing estimation of sensitivity of detection of differences in spot intensity between two groups using either a longitudinal (paired) or non-paired design. Parameters for differences were: two-fold normalised volume change, α of 0.05 and power of 0.8. Using groups of 20 samples, alterations in 1742 spots could be detected with longitudinal sampling, and in 1206 between non-paired groups. Interbatch gel variability was small relative to the detection parameters, indicating robustness and reproducibility of 2-D DIGE for analysing large sample sets. In summary, 20 samples can allow detection of a large number of proteomic alterations by 2-D DIGE in human plasma, the sensitivity of detecting differences was greatly improved by longitudinal sampling and the technology was robust across batches.